Cyborg | Teen Titans Wiki | FANDOM powered by Wikia

It’s not in the circuitry, is it? It’s not the machine that resists you; it’s me, my spirit! That’s the part you can’t break! I don’t need you to make me a man! I already am one! Cyborg to an overwhelmed Brother BloodCyborgVoiceKhary Payton (English), Ken Uo (Japanese), Daniel Lob (French), Tobias Kluckert (German), Roberto Draghetti (Italian), Kim So-hyung (Korean), Zoltn Dzsa (Hungarian), Onur Glcolu (Turkish)Real name

Victor “Vic” Stone

Elinore Stone (mother, deceased)Silas Stone (father)Tucker Stone (grandfather)Maude Stone (grandmother)

Eating Food,Electronic Gadgets,Fourth of July,Listening to Music,Playing Practical Jokes,Science Fiction Movies,Sports Video Games,Watching TV, Hanging Out With Beast Boy, Playing basketball with Robin, Playing chess with Raven, Lifting weights with Starfire

Brother BloodAnyone who abuses his technology,Being half machine,Gizmo,Losing battles,Not being strong enough,Not Having the remote for the TV,Tofu,Beast Boy losing things,Being ignored by Beast Boy, Starfire’s singing and cookingBeing kicked out of his house

A body made up of entirely robotic systems granting him superhuman strength, resilience to damage, capability to fix many appliances, unsurpassed knowledge of technology and robotics, a cannon built into his arm that can shoot sonic blasts, and numeral other gadgets built into his body

Sonic Cannons built into his arms and numerous other gadgets installed throughout his body

Cyborg (sometimes “Cy”) is the half-cybernetic half-man, chief technological expert and one of the five founding members of the Teen Titans.

Cyborg was a promising strong teenage athlete named Victor Stone before an accident that killed his mother and injured him so severely that his father replaced the damaged body parts with cybernetics to keep his son alive. But since these mechanical parts were not inconspicuous, he was shunned by his home environment and his friends, which frustrated him greatly.

One night, Cyborg took to the streets wearing a hoodie to cover his cybernetic parts, where he ran into the new arrivals Robin and Beast Boy fighting a rather violent alien girl, who was actually a fugitive from a prisoner transport. Soon, Cyborg joined by the mystery girl Raven, the youngsters teamed up to defeat the girl’s alien captors and formed a permanent team to combat villainy. Cyborg constructed the Titans Tower and its systems from a Gordanian landing ship, and the team moved into its new headquarters. From that point on, Cyborg served as the team’s chief technician, constructing their primary vehicles such as the T-Car and T-Ship.

Cyborg wearing a hoodie to hide his cybernetics.

In the series’ third season, Cyborg used the alias of Stone and a pair of holographic rings to infiltrate the H.I.V.E. Academy, which was at that time administered and mind-controlled by Brother Blood.

The Titans exposed and foiled his scheme to utilize a new superweapon called the Ion Amplifier, but in the process, Cyborg unknowingly had the construction plans for his cybernetics copied by Blood, who used them to build new superweapons. Outraged, Cyborg declared a personal vendetta on Blood and confronted him personally when he attempted to employ a gigantic sonic cannon from an undersea base. However, Blood’s martial arts skills got the better of him, and he won only with Bumblebee’s assistance, who was at that time infiltrating the H.I.V.E. with the help of Aqualad. In order to hunt down Blood and other supervillains more efficiently, Cyborg helped Bumblebee and Aqualad establish and outfit an Eastern branch of the Titans, with Speedy and Ms y Menos joining the ranks. Soon, they were attacked by Blood and an army of modeled robots, but apparently, Cyborg managed to repel them all. Met with a proposal to remain and become the leader of the Titans East, Cyborg decided to stay with his new team.

Cyborg as his original “human” self

At one point, Cyborg attempted to upgrade himself by installing a super-processor chip called Maximum-7 (or Max-7) into his cybernetic brain. Initially, it did work for his benefit, boosting his physical and mental processing speed well beyond his former capacities. But when the Titans first engaged Billy Numerous and were unable to catch him, a frustrated and obsessive Cyborg began shutting down his human personality in order to increase the Max-7’s efficiency, which had the detrimental effect of making him more and more a robot, and eventually, this conflict between human and cybernetic nature led to a short-circuit which nearly killed him. The other Titans managed to remove the chip before this could happen, and now, Cyborg restored to his true self, devised a successful plan which brought down Numerous for good.

In the comic series based on the TV show, Cyborg meets a young teaching volunteer by the name of Sarah Simms. Despite several rocky times they have since formed a very close romance.

Cyborg eating meat

Cyborg is a very outgoing, cool, and fun-loving character who likes to enjoy life, especially since he found friends who consider him a person, not a freak. He is upbeat, smart, funny, and cheerful, but serious and heroic when he needs to be. He likes to enjoy playing video games, tinkering with technological gizmos and eating. He also tends to be stubborn at times and has had some serious arguments with Robin in the past, but he does make a capable second-in-command in Robin’s absence. He also frequently bickers with Beast Boy, mostly about the latter’s culinary taste and habit of misplacing all manners of personal items, though the two entertain a close friendship.

Cyborg often plays the protective big brother role of the team, getting quite serious when they are upset and does whatever he can to make them feel better. He is never hesitant to put Beast Boy in his place when he thinks the younger Titan is being inconsiderate of Raven’s or Starfire’s feelings. Likewise, Raven and Starfire also do the same for Cyborg, evident in “Car Trouble” and “Deception”.

Much like the other Titans, Cyborg does not take betrayal lightly. He hates losing battles, especially to seemingly insignificant opponents. Their first defeat from Terra made him extremely angry with himself, because he had a chance to take a shot but didn’t. He has been known to display emotions of anger (which he often takes out on his friends), frustration, and becoming depressed.

Cyborg’s replacement robot dressed up

One facet of personal vulnerability is Cyborg’s great personal pride in his inventions and constructions. For this reason, he tends to foster an immense dislike for anyone abusing his technology for selfish reasons, especially Gizmo and Brother Blood, and to be overprotective of his most personal projects, like the T-Car.[1][2][3][4]

He also possesses a tremendous appetite, and he will consume any edibles within his reach when hungry. His favorite food is barbecue and he also especially enjoys other meat, milkshakes, pizza, and waffles. The only food he would not voluntarily touch is Starfire’s cooking and tofu (especially since Beast Boy goes to great lengths to try and make him eat it) although he once mistakenly ate the alien meat substitute.

As revealed in Troq, Cyborg has a personal dislike for bigots as shown when he became disgusted with Val-Yor when he found out what he had really be calling Starfire.

However, he can be surprised when Beast Boy adopts a more serious persona as shown when he took note of the latter’s behavior when reuniting with the Doom Patrol. He was even more surprised Beast Boy went with them to defeat their old enemies. This likely showed him Beast Boy merely puts up an act, as he had no problem with Beast Boy’s leadership when fighting the Brotherhood of Evil.

Despite this, Cyborg can sometime show his immature side with Beast Boy as they also enjoy playing their favorite game they made up “Stankball”.

Cyborg and Raven fixing the T-Car

Raven and Cyborg have a fairly stable and healthy relationship. They had very few episodes dedicated to mostly the two of them, but this is likely because the two of them have always been fairly close and comfortable around each other. Cyborg, despite being the Titan most similar to Beast Boy, is more mature than he is and is more considerate of Raven’s preferences. Raven, for her part, reciprocates this, as she is more patient with than she is with Beast Boy.

Cyborg often looks out for Raven, making sure that Beast Boy does not go over the top to annoy her or hurt her feelings. In “Nevermore”, was especially serious with Beast Boy, reminding him that he shouldn’t be messing with her following the prior night’s events, and made sure he went to apologize. Even though he tried to get Raven to play Stank Ball with him and Beast Boy, she clearly stated she doesn’t want to play, which made Beast Boy angry. He called her creepy, with Raven still listening, and told him to leave her be, knowing she wanted to be alone.

In the Teen Titans Go! comics, Cyborg, on Christmas, bought Raven an antique bookcase he knew she wanted, causing Raven to become uncharacteristically elated and showing an appreciation for her tastes and hobbies.

When they first met, Raven felt as if she did not fit in, but Cyborg reassures her that she fits in just fine. Even though they fight occasionally, they maintain a healthy friendship.

Despite sometimes being a bit inconsiderate of Cyborg’s feelings, Raven never intends to hurt him emotionally. This is evident in “Car Trouble”, where she initially dismissed ‘s dismay over his stolen T-Car by telling him “Calm down, it’s just a car.” which made rather angry. However, she ultimately realizes it’s her fault, and goes to comfort him and help him get his car back. Although Cyborg was forced to destroy it, Raven goes as far as to help him rebuild it, further proving their close friendship.

When is the only one left with Raven in “Fear Itself”, he likely knew she was afraid, and tried to reassure her that they’ll get through the ordeal. being the last Titan to disappear that night may further hint at his big brother role to Raven, being protective of her when she wanted to save Starfire when there was no possible way to.

Cyborg is shown to often be more understanding of Raven than the other Titans, as he respects her desires to be alone but still tries to include her when he can. Raven, in turn, seems to accept as he is without question and accepts his enthusiasm for his hobbies, even if she does not share it.

Cyborg makes Raven smile more than anyone else in the series. Her biggest smiles, at least, two episodes centering around Cyborg’s troubles.

Cyborg and Robin fighting

It is revealed that Cyborg is Robin’s second-in-command.

Starfire and Cyborg are incredibly close. Their relationship is much like an older brother and younger sister, and is really protective over her. They hardly ever get angry at each other, however, in “Final Exam”, does lose his temper and hurt Starfire. Despite this, the two have remained extremely close throughout the series.

Cyborg had helped Starfire greatly in “How Long is Forever?” when she was pushed forward in time. Even after so many years, Cyborg cared deeply for Starfire’s well-being. In the series, Cyborg seems to act like the big brother to Starfire, and Starfire looks up to him.

The two often like to lift weights together, and despite countless times having witnessed Starfire’s impressive strength, is still shocked when she is able to lift heavier weights than he is with relative ease. They are the strongest in the team physically, as their physical prowess far outmatches Robin’s, Raven’s, and even Beast Boy’s.

Cyborg and Starfire have a practically mirrored personality, both being cheerful yet considerate of others’ feelings, and they seemed to get along well from the very beginning.

In the episode, “Troq”, Cyborg was the first one to learn the meaning of the word Val Yor had been calling Starfire, (Troq, which is a slur for literally “nothing”). Because he initially misinterpreted Starfire’s explanation that it meant nothing, he went to call her that, which hurt her deeply. But after learning that it literally meant nothing, went to comfort her. Being half-robot, knows exactly what it is like to be mistreated just for how you look, and completely empathized with her. He then told Robin, who was equally outraged.

Cyborg also makes note of Starfire’s close relationship with Robin, and in “Stranded”, he even teased Robin, calling Starfire his girlfriend. And when Starfire and Robin had their first real kiss in the final movie-episode of the series, Trouble in Tokyo, voiced his approval, saying, “Well, it’s about time.”

Cyborg with cannons

This ability has its own cons though. His entire power cell and the whole power of Titans’ Tower is only just enough to make one blast. This is why he only uses it in desperation, and it is much like an ultimate form, much like Beast Boy’s Werebeast form and Raven’s white form.

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Franky | One Piece Wiki | FANDOM powered by Wikia

FrankyJapanese Name:

FrankyFrankie (originally)

“Iron Man” Franky[15][4] is the shipwright of the Straw Hat Pirates.

A cyborg from Water 7, he was originally the leader of the Franky Family, a group of ship dismantlers.[2] He is originally from South Blue [16], but left 32 years ago as a four-year-old child. He was originally named “Cutty Flam”[17] until he threw away his original name for his nickname per the request ofIceburg to hide his identity.[18]

Franky and his followers were originally enemies of the Straw Hats at the beginning of the Water 7 Arc, until circumstances forced them to become allies at the end of the same arc and the Enies Lobby Arc. At the request of the Franky Family, Franky decided to join the Straw Hats to fulfill his dream of creating and riding a ship capable of circumnavigating the world, the Thousand Sunny.

He is the eighth member of the Straw Hat crew and the seventh to join Luffy’s crew.[19] He currently has a bounty of 94,000,000.[4] Previously going by the epithet, “Cyborg” Franky, he has since gained the new nickname, “Iron Man”.

As a direct result of the modifications that he conducted upon himself as well as the years spent as a ship dismantler, bounty hunter, and street thug in Water 7, Franky is a powerfully built man with a height of at least seven feet, making him the second-tallest member of the Straw Hat crew. His forearms are relatively enormous while his biceps are comparably small. His chest is well-toned with large abs and pectoral muscles.He has brightly-colored blue hair and blue star tattoos on his forearms. Franky’s eyebrows are rather long and stern, and he has three prominent lower Matsuge on each eye. His chin is very angular and tapers off in three pointed clefts. Franky has an equally angular prosthetic nose made of iron with several rivets and jagged edges, the only replacement part of his exterior body that is not covered in artificial skin.

Before being hit by the Puffing Tom, Franky’s forearms were normal-sized and his overall height was comparably smaller than his cyborg-enhanced self would be. He also had an ordinary nose and chin, both of which were later badly broken in the accident, causing him to repair them with iron.

His choice of clothing usually comprises of a swim briefs, which causes people to call him a pervert, and an open loud Hawaiian “Aloha” shirt with a large golden chain necklace around his neck. It is rare for him to button up his shirt, have long sleeves, and wear pants or footwear unless the situation calls for it, or someone makes him do so. He also does not like it when people tamper with his look, as seen when Nami’s mind was inside his body and she tried to button up his Hawaiian shirt, which made Franky upset.

Before becoming a cyborg, Franky went half-dressed simply because he wanted to. Now, his cyborg body is built in a way that covering himself up actually limits him from accessing its features (long sleeves prevent him from using weapons installed on his arms, a buttoned shirt stops him from accessing his chest panels, pants keep him from using features on his legs that cause them to separate or expand, shoes are a hindrance for the same reason and also redundant because his feet are toughened with iron). If in a battle, Franky will strip down for the sake of using his weapons or wear specially modified clothing that can transform along with him. Conversely, Franky always makes sure to cover his back (hence, he wears a shirt) because it is a weak spot- it is still flesh and blood, the only part of his body he cannot reach and modify. Unfortunately, Franky is still susceptible to cold and can suffer chills from his half-nakedness.[20]

Duringhis first appearance in the Water 7 Arc,Franky wore a masked costume as adisguise so no one could identify him while he bought wood from the Adam tree off the black market.[21] After discardingthis disguise, for the rest of the arc all the way up to the end of the Post-Enies Lobby Arc, he wore a red Hawaiian shirt, with lime green palm trees decorating it.

During the Thriller Bark Arc, Franky wore a yellow shirt with purple trident-like symbols on the sides anda large one on back.

Near the end of the previous arc all the way up to the Sabaody Archipelago Arc, Franky switched to wearing a purple version of his Hawaiian shirt.

During the Straw Hats separation, Franky wore a red coat to protect himself from the cold while on Baldimore,but after blowing up Vegapunk’s laboratory, the skinon hisface and frontal body was burned off, revealing his metal endoskeleton underneath, which he covered up with a tiger skin rug due to scaring people who looked at him.

He alsohas a pair of sunglasses, which he usually wears when things start to get serious.

Over the two years he was on his own, Franky used Vegapunk’s blueprints to drasticallyreconfigure his body, repairing the damage he accidentally caused to himself and replacing some old functions his body used to have with better and more powerful implements.Franky’s hair is now controllable, and can change different styles instantly by pushing his nose for more than three seconds. While he used to wear it up in a pompadour style and can still do such, he now tends to keep his hair retracted and sport a buzz cut, or otherwise experiment with different hairstyles, sometimes changing his hairstyle to a theme which fits the circumstances he finds himself in.

He also has two stitch-mark scars on his torso running down from the back of his neck indicating that he had sewn his skin back on.

He appears to have made modifications to his eyes as well. What appears to be his eyes are actually lenses that resemble human eyes over a pair of robotic eyes underneath. His left eye was seen with inverse coloration and with a glowing red pupil after his battle with Senor Pink, after being knocked around so muchit caused the lens over the eye to fall out.[22]Once the fighting against the Donquixote Pirates had come to a close and Franky had some downtime to repair himself, he installed a replacement lens.[23]

His shoulders, torso, and arms are also much bigger than before, and with studded hands that look almost robotic in appearance, but he also revealed that inside of his huge arms he still has a set of normal-sized robotic hands. He now appears to be wearing metal rigged suspenders. He has replaced his elbows with large, light blue hinges, his shoulders with a large red ball and socket joint with “BF-37” written on them, and his forearms with large, light blue cubes, with his trademark star tattoo being split by an edge. Surprisingly, Franky’s forearms also have hair on them even though they are clearly robotic, and his large robot hands can even wear gloves. These new features house upgrades he gave himself during the timeskip.

He now wears a red coconut tree-motived Hawaiian shirt and red swim briefs.While on Punk Hazard, he was given a large double-breasted black coat by Kin’emon for the cold. When he was able to change into winter attire, he put on a sky blue double-breasted coat with”BF 37″ written on the front and back, and paired it with a dark navy blue scarf with red polka dots.

During the Dressrosa Arc Franky wore a white dress shirt and black suit jacket, a bowler hat, as well as his typical speedos. He initially had his hair in two long pigtails. After Dressrosa Operation: SOP began, he reformed his hair to resemble a cannon, which comically was only cosmetic.

After the battle against the Doflamingo Family, he wore a white tank top with ‘Corrida’ written across it. He also reformed his hair to resemble Usopp’s hat during the Dressrosa Arc.

During theZou Arc, Franky wore a black v-neck t-shirt with four symbols on it arranged in a square pattern (An “I”, “H”, “T”, and a sun-like symbol). He reformed his hair into an undercut style similar in appearance to Smoker’s Post-Timeskip hairstyle. Later on, he re-styles it again to resemble a blue whale.

In the WanoCountry Arc,Franky wears a dark blueyukata workmancoat with kanji on the vee of the chestandsymbols around the belt. He has red cloth draped around his shoulders and his hair is reformed to resemble a hammer.

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Amber Case: We are all cyborgs now | TED Talk

Technology is evolving us, says Amber Case, as we become a screen-staring, button-clicking new version of homo sapiens. We now rely on “external brains” (cell phones and computers) to communicate, remember, even live out secondary lives. But will these machines ultimately connect or conquer us? Case offers surprising insight into our cyborg selves.

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Cyborg | Definition of Cyborg by Merriam-Webster

Examples of cyborg in a Sentence

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These example sentences are selected automatically from various online news sources to reflect current usage of the word ‘cyborg.’ Views expressed in the examples do not represent the opinion of Merriam-Webster or its editors. Send us feedback.

1960, in the meaning defined above

cybernetic + organism

Last Updated

6 Dec 2018

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Cyborg (comics) – Wikipedia

Victor Stone is the son of Silas Stone and Elinore Stone, scientists who use him as a test subject for various intelligence enhancement projects. While these treatments are ultimately successful and Victor’s IQ subsequently grows to genius levels, he grows to resent his treatment.

Victor strikes up a friendship with Ron Evers, a young miscreant who leads him into trouble with the law. This is the beginning of a struggle in which Victor strives for independence, engaging in pursuits of which his parents disapprove, such as athletics and abandoning his studies. Victor’s association with underage criminals leads him down a dark path in which he is often injured, but he still lives a “normal” life in which he is able to make his own decisions. However, this rebellious path does not bury Victor’s conscience considering that he refuses to participate in Evers’ grandiose plans of racially motivated terrorism.

Victor’ situation changes radically when he visits his parents’ lab where experiments in inter-dimensional access are done. At that moment of his entry, an aggressive gelatinous creature was accidentally pulled through and Victor’s mother is killed by it. It then turned on Victor and he was severely injured by its attack before his father was able to send it back to its native dimension.

With his wife dead and his son mutilated, unconscious and near death from the incident, Silas is driven to taken advantage of prototype medical prosthetic research he has access to treat Victor. Unfortunately, Victor only regains consciousness after the extensive artificial limbs and implants were installed in his body without his consent. Victor was horrified at the discovery of the metallic components, which involve most of the left side of his head and face, and raged that he would rather have died than be such a victim of his father’s manipulations.

Although his bitterness remained for some time, Victor eventually calmed down enough to successfully adjust to his implants physically. He found himself rejected by the public because of his implants, including his girlfriend, who would later thoughtlessly blurt out that she would prefer he had died instead of being in that state. However, Victor’s conscience was unbowed, as evidenced by the fact that when Evers tried to manipulate him into participating in a terrorist attack on the United Nations, Victor decided to equip himself with his weaponized attachments and stop him on the top of United Nations Headquarters.

When Raven assembles the Teen Titans, Victor joins initially for the benefit of a support group of kindred spirits and freaks, and has remained with that group ever since.[1] Fortunately, Victor eventually finds additional new civilian friends of better character such as a group of juveniles who are adjusting to their own prosthetics and idolize him because of his fancy parts and his exciting adventures. It also turns out that their beautiful teacher Sarah Simms, who has often assisted Cyborg and the Titans, admires him as well.

Another person who sees past the cybernetic shell is Dr. Sarah Charles, a S.T.A.R. Labs scientist who helps him to recuperate after having his cybernetic parts replaced. Cyborg and Dr. Charles date for some time and she, along with Changeling, keeps trying to reach him when he is seemingly mindless following the severe injuries he incurs during the “Titans Hunt” storyline.

Although Cyborg’s body was repaired by a team of Russian scientists after the missile crash he had been in, albeit with more mechanical parts than previously, his mind was not. Eventually, his mind was restored by an alien race of computer intelligences called the Technis, created from the sexual union of Swamp Thing and a machine-planet when Swamp Thing was travelling through space. Cyborg, however, had to remain with the Technis both to maintain his mind and because, in return for restoring him, he had to teach them about humanity. He took the name Cyberion, and gradually started becoming less human in outlook, connecting entirely to the Technis planet.

Eventually, Cyberion returned to Earth, establishing a Technis construct on the moon and a smaller base on Earth. With Vic’s consciousness dormant, but his desire for companionship controlling the actions of the Technis’ planet, it began kidnapping former Titans members, his conscious mind so suppressed that he was not only searching for deceased Titans, but even sent one probe looking for himself as Cyborg. He ended up plugging them into virtual reality scenarios, representing what he believed to be their “perfect worlds”; for example, Beast Boy was back with the Doom Patrol, Damage was spending time being congratulated by the Justice Society as a true hero, and Nightwing was confronted by a Batman who actually smiled and offered to talk about their relationship. Although the Titans were freed, there was a strong disagreement between them and the Justice League over what action to take; the League believed that there was nothing left of Victor to save, whereas the Titans were willing to try, culminating in a brief battle, where the Atom and Catwoman (who had followed the Justice League to investigate) sided with the League while the Flash fought with the Titans. While Vic was distracted trying to aid his friends, a Titans team consisting of Changeling and the original five Titans were sent by Raven to try making contact with Vic’s human side, while Superman, Wonder Woman, Green Lantern, the Martian Manhunter, Power Girl, Captain Marvel, and Mary Marvel moved the moon back to its proper place. Eventually, thanks primarily to Changeling’s encouragement, and Omen and Raven holding Vic together long enough to come up with a plan, Vic’s consciousness was restored, and “downloaded” into the Omegadrome, a morphing war-suit belonging to former Titan Minion. In the wake of this event, the Titans reformed and Vic was part of the new group.[1] However, he felt less human than ever before.

Shortly after this, Nightwing revealed he had cloned Vic’s body, and by flowing the Omegadrome through the clone, Vic regained his human form, but still had the abilities of the Omegadrome. He often used the Omegadrome to recreate his original look in battle. With his newfound humanity, Vic took a leave of absence, moving first to L.A. with Beast Boy and then to Central City. While in Central City, Vic was involved in one of the Thinker’s schemes, helping Wally hack the Thinker’s attempt to plug himself into the minds of Central City’s population so that Wally could outthink his opponent, though Vic lost the abilities of the Omegadrome in the process.

Vic mentored the new incarnation of the Teen Titans, consisting mainly of sidekicks, most of whom have taken over the identities of former members (i.e. Tim Drake, the third Robin, instead of Dick Grayson, the original Robin and Titans leader), as well as stalwarts such as Starfire, Raven, and Beast Boy, where they have fought enemies such as Deathstroke, Brother Blood, Doctor Light, The Titans Tomorrow, and a brainwashed Superboy and Indigo during a team up with the Outsiders in the Insiders storyline. In the end, Cyborg was the only one capable of standing up to Dr. Light, thanks to his solar shields, although he makes it clear that he only won the fight because the rest of the Titans had softened Light up first.

During the 20052006 storyline “Infinite Crisis”, Cyborg joined Donna’s New Cronus team that went to investigate a hole in the universe that was found during the Rann-Thanagar War. He left Beast Boy in charge of the Titans while he was gone. They arrived at the reset center of the universe and with the help of assorted heroes aided in the defeat of Alexander Luthor, who was attempting to recreate the multiverse and build a perfect Earth from it.

According to 52 Week 5, Cyborg was fused together with Firestorm after returning to Earth. This was caused by the energy ripples caused by Alexander Luthor Jr. which altered the Zeta Ray Beams the heroes were going to use to return home.

After being severely damaged during the events of “Infinite Crisis”, Cyborg was rebuilt over time in thanks to Tower caretakers Wendy and Marvin. He awoke a year later to find a wholly different Teen Titans being led by Robin, the only member from the team he formed prior to going into space. He is still a member of the team, but feels that Kid Devil and Ravager are hardly worthy Titans, and thus is attempting to find a way to reform “the real Titans”.

After the team along with the Doom Patrol defeated the Brotherhood of Evil, Cyborg asked Beast Boy to rejoin the Titans, but Gar refused, saying that his skills were needed with the Doom Patrol. After returning to Titans Tower, Cyborg began reviewing the security tapes during the last year, in which it appears that he was looked to by all the Titans of the past year for a shoulder to lean on, despite being in a coma-like state.

It appears that although Cyborg has returned to the team, the role of leader is now in the hands of Robin. He does however retain the position of statesman amongst the team and occasionally plays second-in-command.

In Justice League of America (vol. 2) #3, Batman, Wonder Woman, and Superman agree that Cyborg should be offered membership in the new Justice League. However, following a battle against Amazo, Green Lantern and Black Canary take over the formation of the JLA, and Cyborg is not amongst the roster.

In the Teen Titans East one-shot, Cyborg gathered together a new team of Titans. During a training exercise, the group was attacked by Trigon, and Cyborg was blasted by a giant energy beam. He was last seen in a crater, with only his head and torso remaining.

In the aftermath of Trigon’s assault in the Titans East one shot, Cyborg has been placed into a special hoverchair while he recuperates. Cyborg’s body is completely repaired in Titans #5. Soon after, the resurrected and unbalanced Jericho enters Cyborg’s body, using him to manipulate the defenses at Titans Tower to kill the Teen Titans. Jericho’s plans are foiled when Static, the newest Teen Titan, uses his electrical powers to overload the Tower’s systems, causing feedback that knocks Jericho out of Cyborg.[3] After recovering, Cyborg pretends to still have Jericho inside of him, in order to draw out Vigilante, who was currently targeting Jericho. The plot works too well when Vigilante appears and shoots Cyborg in the head.[4]

In an unspecified time during the Teen Titans comics, a man with enhancements similar to Cyborg’s attacks Dr. Sarah Charles on the day of her wedding to Deshaun, a young scientist. Cyborg rushes in for the save, discovering how Deshaun, connected to Project M, has sold the technology used to turn Stone into Cyborg to the military. He also finds that the enhanced man was Ron Evers, once Vic’s best friend now turned terrorist, who was seeking vengeance for the soldiers used as test subjects. After Cyborg manages to calm down his friend and discovers the truth: Mr. Orr, revealed as the mastermind behind Project M’s cyborg research, brings his Stone-derived best subjects: the current Equus, an armored form of the Wildebeest, and a cyberized man sporting enhancements even more powerful than Stone’s current ones called Cyborg 2.0.

Cyborg 2.0 turns out to be the Titans Tomorrow Cyborg 2.0, snatched from his proper timeline and cajoled by Orr into fighting his younger self for the possession of their shared technology and Orr’s permission to use it in the battlefield. Cyborg is soon forced to fight simultaneously against the Phantom Limbs, an elite force of soldiers crippled in the Middle East and restored by his tech, and the Cyborg Revenge Squad, a broader formation composed of the Fearsome Five, Magenta, Girder, the Thinker, and Cyborgirl. Although the Cyborg Revenge Squad soon gains the upper hand, with the help of his fellow Titans Cyborg is able to hold his own in combat, reverse engineer on the fly some of the future technology used by Cyborg 2.0, and enhance his own body enough to win against Mr. Orr. He later decides to get a new lease in life, forgiving Deshaun and Sarah Charles on their wedding day for abusing his technology, resuming dating Sarah Simms and having the Phantom Limbs fitted with new, non-military, prosthetics. It is however implied the Phantom Limbs, unwilling to see Stone’s offer as a sign of good will, are trying to get back their weaponized prosthetics and wait for a rematch.

During the events of Blackest Night, Cyborg joins with Starfire, Beast Boy, and several other heroes to form an emergency team to fight off the army of dead Titans who have been reanimated as Black Lanterns. He later joins in the final battle at Coast City.

Following the dissolution of the current JLA after Justice League: Cry for Justice, Cyborg is invited by Donna to join Kimiyo Hoshi’s new Justice League.[5] He befriends Red Tornado, and claims that he has come up with a plan to make him indestructible.[6]

After a battle with Doctor Impossible’s gang, Cyborg is forced to take a leave of absence from the team in order to not only help rebuild Red Tornado, but also help Roy Harper, who had his arm severed by Prometheus.[7] During this time, Victor leads Superboy and Kid Flash to the city of Dakota to rescue the Teen Titans, who had been defeated and captured by Holocaust.[8] The Titans emerge victorious from the battle after Kid Flash uses his powers to send Holocaust plummeting into the Earth’s inner core.[9]

Despite apparently being written off the team, writer James Robinson explained that Cyborg will continue to have a presence on the JLA, and will even be given a co-feature in the back of the book for Justice League of America #4850.[10] In the co-feature, Cyborg battles Red Tornado after he has been driven insane by the power of the Starheart. In the midst of the battle, a flashback reveals that Victor had rebuilt Red Tornado using self-replicating nanites similar to the ones that Prometheus infected Roy with after cutting off his arm, thus making the android indestructible.[11] Cyborg manages to free Red Tornado his power matrix.[12]

Cyborg briefly appears in Justice League: Generation Lost, where he is shown helping Wonder Woman and Starfire search for Maxwell Lord after his resurrection.[13]

Following an adventure in another dimension, Static is left powerless, and Miss Martian is rendered comatose. Cyborg stops the powerless Static from returning to Dakota, and instead tells him that he and a scientist named Rochelle Barnes will be taking him to Cadmus Labs to find a way to get his powers back and awaken Miss Martian. As Static packs up his belongings, Cyborg and Rochelle have a conversation which reveals that they are lying to Static, and have an ulterior motive for taking the two Titans to Cadmus.[14]

He later appears in the final two issues of The Return of Bruce Wayne, where he helps his former teammate Red Robin in his attempt to stop Bruce Wayne from inadvertently unleashing an apocalyptic explosion of Omega Energy.

Cyborg and Red Tornado later travel to the moon alongside Doctor Light, Animal Man, Congorilla, Zauriel, Tasmanian Devil and Bulleteer as part of an emergency group of heroes gathered to assist the Justice League in their battle against Eclipso. Shortly into the battle, Cyborg and the others are taken over by Eclipso and are turned against their JLA comrades.[15] The reserve JLA members are all freed after Eclipso is defeated.[16]

As of August 2011, Cyborg is featured as one of the main characters in a new Justice League ongoing series written by Geoff Johns and drawn by Jim Lee as part of DC’s The New 52 relaunch. Johns has said of Cyborg, “He represents all of us in a lot of ways. If we have a cellphone and we’re texting on it, we are a cyborgthat’s what a cyborg is, using technology as an extension of ourselves.”[17]

The first storyline takes place five years in the past and details the revised origin of the original Justice League. Victor Stone appears as a high school football star who is heavily sought after by a number of college scouts, but apparently has a distant relationship with his father, Silas. After winning a big game, Victor is shown calling his father and angrily telling him that he broke his promise and missed yet another one of his son’s games.[18] Later Victor appears at S.T.A.R. Labs where his father works. The scientists appear to be working on the Mother Box that Superman came in contact with from the Parademon. Victor engages in another argument with his father and tells him that the scouts were there to give him full scholarships to college. When asking if his father will ever appear at any of his games, his father replies “No.” Just then the Mother Box explodes, killing the other scientists and destroying most of Victor’s body while Victor’s father looks on in horror.[19] Silas does everything he can for Victor’s survival. He along with Sarah Charles, and T. O. Morrow go in “The Red Room” in S.T.A.R. labs which contains every piece of technology from around the world. Silas attempts to treat Victor with something that has never been attempted before and he is seen injecting Victor with some type of nanites and having Dr. Morrow put the robotic pieces on Victor (devices such as: a Promethean skin graft, Doctor William Magnus’ responsometer, Anthony Ivo’s A-maze operating system, The classified and prototypical B-maze operating system and Ryan Choi’s White Dwarf Stabilizer). Vic’s life is saved and the energies from the motherbox are incorporated into his new form as Cyborg. This allows Victor to access the vast New Gods data library and discover Darkseid’s true invasion plans.[20]

In the following issue we see Victor as Cyborg. As the issue opens Victor cannot feel his hands or legs. He sees himself for the first time with his robotic parts and is panicked by his new body. Suddenly, Parademons burst into the red room and leap toward Sarah Charles. However, Cyborg’s defense systems react, automatically weaponizing his arm into a sound cannon from which he fires his powerful white noise cannon, disintegrating the two Parademons and blasting a gigantic hole in the Star Labs building. After saving Sarah’s life Victor asks his father what has happened to him, his father tells him that he couldn’t let him die. Cyborg obviously distraught exclaims, “You did this to me.” and flees, despite Silas’ plea for him to wait. Later in the street Cyborg sees a woman being set upon by a group of Parademons. He leaps to the woman’s aid, punching the parademon. However, in ensuing scuffle Cyborg inadvertently absorbs some of the Parademon’s components giving him access to Boom Tube technology. This new ability automatically transports or teleports Victor to where Superman, Batman, Wonder Woman, Flash, Green Lantern, and Aquaman are fighting the Parademons, moments before Darkseid arrives. Cyborg fights alongside the other heroes against Darkseid and his Parademons, but despite their best efforts Darkseid proves to be too strong. Cyborg is able to reverse engineer the alien boom tube technology and with a considerable amount of stress on his systems he is able to teleport all the invading aliens including Darkseid off the planet, saving the Earth. After sending Darkseid back where he came from, Cyborg helps to found the Justice League.

Victor has not begun any process of reconciliation with his father, who is primarily concerned with Victor’s mechanics rather than his humanity. Cyborg primarily focuses on his super-heroics, aiding Batman and others when he can and monitoring crime through his cybernetics. After the villain David Graves makes an attack against the Justice League, Cyborg and his teammates travel to the Valley of Souls. There he learns that he walks the line between life and death. He sees a false apparition of his human self that tries to convince him that Victor Stone is dead and Cyborg is just an imitation. Victor quickly sees past this ruse, and he and the rest of the Justice League defeat Graves. We learn through a conversation with Flash, that Cyborg questions his humanity now that he is part machine and that he lives on the Watch Tower, the Justice League’s headquarters.[21] Flash cracks a joke in an attempt to lighten the mood and assure Cyborg he is still human. During the Throne of Atlantis storyline, Cyborg at first rejects an upgrade his father has that would allow him to operate underwater at the price of his remaining lung which to him would mean sacrificing more of his humanity.[22] However following the capture of the rest of the Justice League by Orm who sentenced them to the bottom of the ocean, Cyborgas he calls in reserves to hold off Orm’s forcesreluctantly accepts the upgrade.[23] This allows him and Mera to rescue the others.[24]

During the “Trinity War” storyline, Cyborg gets a visual of Shazam heading to Kahndaq, to which Batman assembles the Justice League with the help from Zatanna to meet in Kahndaq to stop Shazam.[25] Following the supposed death of Doctor Light in Kahndaq, Batman tells Superman that Cyborg and Martian Manhunter are doing an autopsy to prove his death was not Superman’s fault.[26] As Wonder Woman leads the Justice League Dark to go look for Pandora, Cyborg is among the superheroes that remain at A.R.G.U.S. while Batman, Flash, Aquaman, Shazam, Steve Trevor, the Justice League of America, Zatanna, and Phantom Stranger go to stop Wonder Woman.[27] Cyborg was present when Atom tells him, Superman, Element Woman and Firestorm the true purpose of the creation of the Justice League of America and that she was spying on the Justice League which is how the Justice League of America ended up in Kahndaq.[28] When the Crime Syndicate arrives on Prime Earth, Cyborg’s old prosthetic parts combine to form a robot called Grid (who is operated by a sentient computer virus).[29] During the Forever Evil event, after Batman and Catwoman drop Cyborg off to his father in Detroit,[30] he makes the choice to willingly receive a new cybernetic body and helps his father and Dr. Morrow create one that is slimmer in appearance so Cyborg could look more human.[31] Working together with the Metal Men created by Doc Magus, Cyborg succeeds in shutting down Grid.[32]

Afterwards Cyborg helped newcomer to the group Shazam fit in with the league as the rest set out to find Power ring’s missing accessory which flew off after the death of the former wearer.[33] While on monitor duty he and Shazam experiment with some of his magical powers to aid in finding the ring after joking of having an Xbox in his left shoulder; only for the young ward to conjure up a ping pong table, which they play while having spare time on their hands.[34] Eventually the call goes out and everyone in the league mobilizes to secure the new rampaging Power Ring before the Doom Patrol does.[35] After coaxing Billy into action against Jessica Cruis, Victor moves in to interface with the ring itself, finding out a great deal about the ring of Volthoom and his current host, only to be forcefully thrown out after the ring entity rejects him by causing his systems to short circuit, removing him from the battle.[36] He is last seen recovering at S.T.A.R. Labs, after Shazam rushed him to the med bay, following the power ring crisis. Cyborg wondered what he saw within the ring, after his dad warned him interfacing with it again could trap him in it forever.[37]

An incident involving Batman’s son, Damian Wayne, during the “Robin Rises Alpha & Omega” story arc in Batman, led up to most of the justice League battling against Glorious Godfrey and a Parademon horde from Apokolips when they captured the chaos shard and the sarcophagus of Damian, before retreating back home.[38] All the league members present, Cyborg included, state to an adamant Bruce Wayne that running headlong into unmarked X-factor territory for a suicide mission was less than ideal, considering the consequences that could befall earth. This eventually culminates with Batman hijacking Cyborg’s teleportation systems, to zip up to the Watchtower in an attempt to retrieve an experimental and highly dangerous combat suit, in order to mete out his agenda; But Cyborg manages to block his administrative access so that he, Shazam, Aquaman, Wonder Woman, Lex and Cold could physically restrain him, causing Batman to begrudgingly give up and retire to the batcave.[39]

After the Bat left, the rest of the Bat Family turned up asking Victor for help with some digitized doppelgangers of baddies that Bruce initially set up in order to distract the League, destabilize watchtower security to secure the Hellbat, and eventually use a personal Mother Box (secured from a Parademon kept in cold storage) to vacate to Apokolips.[40] After making his way to the Batcave to meet with them, he’s directed over to a console which enabled him to directly access the Batcomputer’s more sophisticated systems. However, it was all a ruse utilizing a preemptive countermeasure devised by Batman tailored to Cyborg’s specific weaknesses. Cyborg was temporarily incapacitated and was set into a VR simulation where he relived his more peaceful days in college, while Batgirl went to work on his Motherbox in order to secure a path towards Apokolips and chase after their father. But Victor eventually snapped out of his dream haze and followed them through, angered that they used him in such a way.[40] Cyborg traveled along with Titus, who hitched a ride on his leg, to catch up with the rest of the Batman Family. They all then have a run in with the scavengers of Armegeddo who quickly vacate after some Apokoliptian Hunger Dogs make their way onto the scene. They eventually catch up with the armor-clad Dark Knight ripping his way through a sizable chunk of Apokolips’s forces singlehandedly. Jason Tim and Barbara show Batman the Robin Medals Alfred gave them in order to remind him of his purpose, causing him to snap out of his berserker rage and note that Cyborg had reluctantly accompanied them to Hell itself. Having made their way into Darkseid’s citadel where Kalibak was readying his Chaos Cannon to fire again, the caped crusaders kept Darkseid’s forces occupied while Cyborg made short work of the massive war engine, literally tearing it in half. But when he went to set a timed self-destruct sequence within the Apokoliptian computers, Vic suffered a catastrophic feedback that fried most of his internal systems leaving him inoperable just as Darkseid himself made his appearance.[41]

While Batman fought and held Darkseid off, Cyborg ran Batgirl through a crash course on how to hot wire his own Motherbox. Since Darkseid smashed Batman’s Boom Tube generator, Cyborg was their only chance off Apokolips. After successfully jury-rigging his internal systems, Cyborg and the rest of the Bat rogues made a hasty exit stage left as Bruce powered his recovered fragment of the Chaos Shard with Darkseid’s Omega Effect, blasting Darkseid against a wall to cover their escape.[42] In the aftermath, Cyborg, who is still unable to facilitate himself, wonders what is going on as Damian Wayne is successfully revived, however a second anomaly cranks out of the Boom Tube that was opened and Kalibak comes charging through it. With Kalibak occupied by the rest of the gang, Vic tries his best to reestablish his downed systems. He is successful and gains control over the still-open tube as Batman readies the Batplane. As Batman rams his jet into the evil New God sending him careening back to Apokolips, Cyborg closes the portal banishing Darksied’s first born for good. With the threat over, Cyborg heads back topside to inform the rest of the league of what all transpired and stating he has JL business to attend to.[43]

An eponymous ongoing series, by writer David F. Walker and artist Ivan Reis, debuted in July 2015.[44]

This article needs to be updated. Please update this article to reflect recent events or newly available information. (August 2017)

As of Rebirth, he is a part of the relaunched Justice League bi-monthly series as well as his own solo monthly series. It is unclear whether he has the ability of flight in Rebirth.

During Dark Nights: Metal, he is captured by the alternate Batmen of the Dark Multiverse, who attempt to hack him in order to learn the secrets of his teammates. As the crisis escalates, Cyborg is confronted by the controlling consciousness of other Mother Boxes, who claim that he will only gain the power to overcome the Dark Batmen if he fully surrenders to the Mother Box that powers his body at the cost of the transformation deleting his old personality. He is nearly tempted to give in to this transformation, but the appearance of Raven’s soul-self convinces him to hold on to himself while partially succumbing to the transformation. This allows him to free his teammates and ‘hack’ the multiverse as they travel to find new allies in the battle against the Dark Batmen.

Following this and the Justice League: No Justice miniseries, the Justice League series was cancelled after 43 issues and was relaunched into a new monthly series and Cyborg will also be featured as part of a separate Justice League faction that is part of the new Justice League Odyssey series. In addition, Cyborg’s own solo monthly series was also cancelled and ended in June 2018 with the release of Issue 23.[45]

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Cyborg (comics) – Wikipedia

Cyborg (Character) – Comic Vine

Current EventsOriginVictor Stone

Victor Stone is the son of Silas and Elinore Stone, two STAR Labs scientists intent on using their research to improve mankind. Silas and Elinore scientific adventures often estranged their son, as they would sometime dedicate more time and toward their work, oppose to him. The two even used their son as a test subject for intelligence-boosting experimentation. While the successful experiment granted Victor a genius-level intellect, he resented his parents for treating him more like a lab subject oppose to a son.

Vic’s resentment caused him to steer away from science and math in high school. Instead, he pursued an interest in athletics, much to his father’s disdain. His life changed profoundly during a visit to STAR Labs to meet up with his parents, who were busy conducting inter-dimensional experiments. The experiment accidentally allowed a protoplasmic creature into the lab. Silas managed to return the creature to its home dimension, but not before it had slain Elinore and severely injured Victor. Desperate to save his son’s life, Silas used untested cybernetic enhancements to rebuild and reconstruct Victor’s body. He succeeded, but didn’t anticipate Victor’s horror and anger at what he had done.

Cyborg was created by Marv Wolfman and George Perez

The reaction of others to his new form made Vic even more resentful, and he isolated himself from his former life as much as possible by moving to Hell’s Kitchen. It was in this bad neighborhood that Raven found Vic and invited him to join the Teen Titans. After the team formed, Vic found a place where he was accepted and appreciated, despite his inhuman appearance. His father, still feeling guilt over what he made his son go through, constructed the Titan’s Tower for his son and his companions. Victor would remain a steadfast member of the Titans for a long time, serving not only as a hero but as a primary supplemental tech source for the team.

After the events of Flashpoint, DC Comics relaunched their entire comic catalog. In this continuity, Cyborg is now one of the seven founding members of the Justice League (replacing the Martian Manhunter), having never served with Teen Titan. He makes his first appearance in Justice League #1 but not as part of the team. In fact, he’s a high school football player who hasn’t even become “Cyborg” yet. After the Darkseid invasion, Victor was gravely injured and later cybernetically enhanced by his father.

Due to the events of Forever Evil, Cyborg gets an upgraded armor that appears to be much slimmer.

Tragedy struck when the Wildebeest Society captured the Titans and more shocking that the leader of the group was their teammate Jericho. Vic was launched in a rocket along with several members and crashed landed in Russia where he was seriously injured and damaged. The Russian scientists with the help of Red Star rebuilt Vic but due to such heavy brain trauma he had become no more than a walking robot with a human appearance. After several months, Vic’s mind started to regain his memories but when the race known as the Technis came to Earth looking for a way to integrate with society and save their race. Cyborg sacrificed himself for both the Earth and the Technis was was rebuilt into Cyberion.

Cyberion became their protector as they traveled throughout the galaxy. Some time later, Cyberion was reunited with his former teammates and engaged in an interstellar conflict which resulted in the destruction of Tamaran. But there was triumph to be found in tragedy: The Titans were able to restore Raven – who was reborn in a golden spirit form. Following that, Raven, Minion and Garfield Logan elected to remain in space as traveling companions to Cyberion. Frightened by Cyberion’s total embrace of technology, Gar left his friend and returned to earth. Jarras Minion also had doubts about Cyberion’s new attitude and decided to leave as well. Jarras, a sworn pacifist, made Victor a gift of his Omegadrome war suit before he left. The Omegadrome allowed Victor to try to carry out his Technis Imperative: To recreate the planet Technis at all costs.

Having collected a planet-size assortment of technological debris, Cyberion journeyed to Earth to turn its moon into a new Technis world and populate it with his Titans allies. The JLA and the Titans first clashed, then united, to prevent Cyberion from destroying the planet while saving Vic’s soul and downloading it into Minion’s morphing battlesuit, the Omegadrome. Vic was later offered a human body if he would help Vandal Savage harvest Addie Kane’s immortal blood. Before he could make a decision, Starfire destroyed Addie’s body, thus robbing Vic of the chance to make a choice. Also, Vic had to remain a member of the team, per a deal that Nightwing made with Batman.

Following the events of his Technis Imperative, the JLA only trusted Vic to remain free if the Titans kept a watchful eye on him. Feeling like he owed his old friend a debt, Nightwing worked constantly to find a cure for Vic’s condition. With Jesse Quick’s help, Victor was given a new lease on organic life with a body cloned from cell samples harvested by the Russian scientists who once spared him.

Though his mind and cybernetic abilities were still encapsulated in the Omegadrome, Victor inhabited a truly biological body. And for the first time in years, Cyborg knew what it is to live and feel and breathe unaided by mechanized parts. Embarking on a new life, Victor Stone left the Titans for the West Coast. Vic Stone later aided the Flash during the “Our Worlds At War” crisis. At that time, Vic started using the golden Omegadrome to morph into a cybernetic form. Cyborg decided to return to adventuring and settled in Keystone City, home of the Flash. But when Vic Stone linked with the evil computerized Thinker in an attempt to stop him from taking over the city, his body became mechanically paralyzed – reverting him to his silver cyborg form.

Shortly afterward, a mysterious android from the future known as Indigo attacked the Titans and Young Justice , resulting in the apparent deaths of Troia and Omen. At Troia’s funeral, Nightwing disbanded this version of the Titans. Meanwhile, members of Young Justice, especially Wonder Girl, felt responsible for the tragic deaths. This led Wonder Girl, Robin, Impulse and Superboy to form a new group of Teen Titans under the guidance of the more experienced Cyborg, Starfire and Beast Boy.

Cyborg, who was damaged in the battle caused by Indigo, has since received an upgrade in his cybernetic parts. He would experience the formation and reformation of the Titans multiple times, mentoring some versions of the team and even starting a short-lived team of his own. But he would always return to the companionship of his original Titans teammates, even to the extent of joining several of them in the Justice League of America.

After the Infinite Crisis Cyborg was fused to Firestorm and entered into a coma. When he finally woke up, he learned that the Teen Titans had dramatically changed. Wonder Girl, Speedy, Kid Flash, Raven, and Beast Boy had left the team; Starfire was lost in space; and Superboy was dead. Along with Robin, Kid Devil, Ravager, and Wonder Girl (who had just rejoined) he started a quest for Raven.

Vic Stone is a star wide receiver for the Ford Titans, a high school football team. He has an interest in super human activities but is more focused on going to college, earning a football scholarship, and hoping his father makes it to his games. Vic and his father have a distant relationship and after missing several games, Victor finally ventures to S.T.A.R Labs to confront him. Silas tells his son that given the current state of metahumans starting to show up around the planet, Vic’s love for football is going to become irrelevant at some point. Discouraged, Victor begins to leave when everything takes a tragic turn, as a Mother Box unit springs to life and opens a Boom Tube. Victor and several scientists are fatally injured or killed by the boom tube energy.

Not intending to lose his son the same way he lost his wife, Silas outfits Vic with experimental bionics that have been reverse engineered from alien technology found around the globe. With aid from T.O. Morrow and Sarah Charles, Vic’s life is saved and the energies from the motherbox are incorporated into his new form as Cyborg. This allows Victor to access the vast New Gods data library and discover Darkseid’s true invasion plans. After aiding in sending Darkseid back where he came from, Cyborg helps to found the Justice League. He has not begun any process of reconciliation with his father, who is primarily concerned with Victor’s mechanics rather than his humanity.

After the villain David Graves makes an attack against the Justice League, Cyborg and his team mates travel to the valley of souls. There he learns that he walks the line between life and death–meaning that part of his soul has left his body. He sees a false apparition of his human self that tries to convince him that Victor Stone is dead and Cyborg is just an imitation. Victor quickly sees past this ruse, and he and the rest of the Justice League defeat Graves. The situation lead to Vic embracing who he has become, not a young man who has lost his humanity, but a man who has learned to be a hero through shocking means. Allowing Vic to start to forgive his father, as he knows his father was just trying to save his life.

To help retrieve Superman and Wonder Woman from the depths of the ocean floor, Victor upgraded his suit to have an Environmental Mode that allows him to operate underwater. He then commenced a world wide League recruitment initiate to combat the Atlanteans hostiles

At the conclusion of the Trinity War, all of Victor’s cybernetics were brutally ripped from his body as Grid, a software virus deeply embedded into Victor’s cybernetics, revealed itself. The virus was planted by Atomica to help the Crime Syndicate of America. Atomica told Cyborg about what she did the Justice League and Justice League of America/ She also told him that she was the one that poisoned Superman and put the green Kryptonite in his nervous system where she trigger his heat vision, which killed Dr. Light. Cyborg was upset to hear this happening and all of a sudden she told Cyborg that he also betrayed the Justice League and it was Grid that was in his body. Cyborg body turned in to him as the Justice League and Justice League of America watched in horror and where all in shock to see this happening and that the Crime Syndicate of America was taking over the world they where from Earth 3. Atomica was a spy on both teams and she had all their plans. She was planning for the CSA to come and attack the various Justice Leagues.

Cyborg is kept alive with the help of Simon Baz and Batman. Batman and Catwoman manage to escape and bring along Cyborg to S.T.A.R. Labs to get the help of Victor’s father Silas. Silas is initially reluctant to turn his son back to Cyborg once again for fear of hurting him but Victor pushes him to do so saying that this time it is his choice and he must help stop the Crime Syndicate. Cyborg is given an upgraded more slimmer armor. Cyborg goes to enlist the help of Doctor Will Magnus so that he can revive the Metal Men and fight the Crime Syndicate.

Magnus is also initially unwilling to revive the Metal Men as they were deemed failures the first time, but Cyborg convinces him to do so. The team is once again brought together and they join Cyborg in an attempt to fight. Cyborg directly confronts Grid while the Metal Men help fight the Secret Society members that were with him. Cyborg and Grid both enter the digital world where they do battle with each other. Grid initially appears to have the upper hand in the battle attempting to exploit Cyborg’s human side. However, Cyborg states that he has embraced his tech side and that he is the bridge between human and tech. He manages to shut down Grid and goes into the fallen watchtower where he helps Batman use Wonder Woman’s lasso to free the Justice League teams from the Firestorm matrix.

Cyborg possesses cybernetic enhancements that provide superhuman strength, endurance and durability. Cyborg can also interface with computers. Built into his body-armor were an infrared eye, computer generator, sound amplifier, and special programming adapters that allowed him to interface with other body extensions.

Shape-Change: Cyborg has virtually unlimited shape-changing abilities that allow him to mimic road, air or space vehicles and even reshape his entire body or parts of it to form such complex shapes such as a tank.

Superhuman Strength: At optimal capacity, Vic can lift/press in excess of four metric tons. If he pushes himself, he can even exceed five tons, but not without causing severe stress to his cybernetic components. Recently Victor breaks apart Kalibak’s Chaos Cannon used to destroy planets.

Superhuman Speed/Agility: He possesses a degree of superspeed.

Flight

Sensor Systems/superhuman Senses:. Due cybernetic enhancements their five senses were increased to superhuman levels.

Superhuman Stamina: Victor doesn’t need to sleep,eat or drink. Adding the Environmental Mode (that replaced his last lung) no longer has the need to breathe, and can operate in any area that has no oxygen in space or as in underwater.

Superhuman Durability: The nature of Cyborg’s body provides offers protection against physical and energy attacks,being able to withstand the pressures of the deepest parts of the oceans.

Computer Interfacing: Cyborg is connected with all Earth’s computers and satellites including government agencies, secret service (CIA,MI-6…) and even the Batcomputer.

Technopathy: Since is linked with Earth’s computers and satellites Victor can control any type of technology that have connection with the Internet as well control any form of electronic communication,allowing it to manipulate data or rearrange security privileges. Recently demonstrated the ability to hear Brainiac’s drones communicating with each other.

Teleportation – Cyborg can use Boom Tubes to transport himself and the League to anywhere n Earth and in the Universe,since is stated Darkseid use it to cross dimensions,however one out of every thousand ‘jumps’ results in transporting himself and whoever is with him to Apokolips. Recently installed a silent mode to not be noticed by others,not even Superman couldn’t note him coming.

Integrated Weapons: He had various types of weapons integrated into his cybernetic parts.

When Reverse Flash goes back in time and messes with the timeline, the DC Universe turns into a very different place where the world’s greatest heroes are not how we know them to be. In this timeline Cyborg is America’s greatest hero, and he is based in Detroit where he has his headquarters. When the Amazons and the Atlanteans go to war, Cyborg tries to gather a group of Earth’s superhumans to help stop the war that has ravaged half of Europe. No one joins his group when they find that Batman (Thomas Wayne) has no interest. But before long Barry Allen arrives and convinces Wayne otherwise, and the three set off to gather an army.

Stage actor Ray Fisher portrays the character in the upcoming Batman v Superman: Dawn of Justice film. In a brief cameo, Victor’s mangled body is shown being bonded with a Mother Box during one of his father’s experiments.

Ray Fisher reprises his role in the live-action Justice League movie. This movie is directed by Zack Snyder and Joss Whedon, who served as the post-production director of this movie after Snyder stepped down from directing duties. This movie was released on November 17th, 2017.

In this film, Cyborg initially refuses to join the team, though after his father, Silas Stone, is captured, he voluntarily pitches in. He successfully saves his father from the hands of Steppenwolf, and escapes from the water tower from which he resided in. When Superman returned, his offense system kicked in and attacked Superman, which triggered the Man of Steel to fight the League.

Cyborg also played a crucial role in the final act, where he began to separate the Mother Boxes that had formed “The Unity”. With the help of Superman, he succeeded.

Cyborg appears in Justice League: Doom in a major role. The film marks the first time Cyborg has been portrayed as a member of the Justice League in any non-comic form of media. He is voiced by Bumper Robinson. In the film, Cyborg first appears after Batman asks for his help in discovering how the Royal Flush Gang are pulling off a series of impossible heists. Cyborg later rescues Wonder Woman after she is poisoned by Cheetah, and ends up being brought along during the subsequent attempt to rescue the other JLA members. After saving Superman from a Kryptonite bullet, Cyborg helps the Justice League during the final battle against Vandal Savage and his Legion of Doom. After the League saves the Earth from a massive solar flare, Cyborg is officially inducted into the Justice League as the team’s newest member.

He was voiced by Bumper Robinson

Cyborg appears in Justice League: The Flashpoint Paradox, an adaptation of Flashpoint. In the film, Cyborg is a member of the League. In the alternate timeline the bulk of the film takes place in, he is depicted as the world’s top hero, since Kal-El never became Superman and most of the rest of the League never came to resemble their classic forms.

He was voiced by Michael B. Jordan.

Cyborg appears in JLA Adventures: Trapped In Time, voiced by Avery Kidd Waddell.

In Justice League: War, based off of the New 52 Justice League Origins comic book by Geoff Johns, Cyborg appears as one of the founding members of the Justice League in light of the invasion of Darkseid. Victor Stone was originally a talented high school football quarterback but has a troubled relationship with his father Silas due to his father’s lack of support for his football playing career. In frustration, Cyborg grabs one of the boom tubes asking whether his work is more important than his own son. The boom tubes suddenly activate at that moment and engulfs Victor. In a last ditch effort to save his son’s life, Silas grafts technology from the red room and successfully saves his son’s life but at the cost of making him a Cyborg at the same time. Cyborg helps the rest of the Justice League in battling Darkseid and his Parademons, with Cyborg having access to almost any technological interface he is able to open up the boom tubes to send them back to Apokolips. At the end of the film, the newly formed Justice League team is introduced to the world and Cyborg seems to have embraced his new role more as he sees his father nod in approval. Cyborg was voiced by Shemar Moore.

Cyborg appears alongside his Justice League teammates in the sequel to Justice League: War, titled: Justice League: Throne of Atlantis. The film is based off of the New 52 comic book story line of the same name and was released in 2015. Shemar Moore reprised his role.

Cyborg appears in Batman Unlimited: Monster Mayhem, voiced by Khary Payton.

Cyborg appears in Justice League vs. Teen Titans, with Shemar Moore once again reprising his role. In the film, it’s shown that he relates more closely to the Titans, as they are closer in age to him.

Cyborg appeared in The Super Powers Team: Galactic Guardians from 1985 to 1986. He was voiced by Ernie Hudson. Cyborg’s origin was told via a medical journal read by Dr. Martin Stein saying Cyborg was a promising decathlon athlete until an accident destroyed most of his body and his father replaced part of his body with machine parts. Also, he is not a Titan. He becomes fast friends with fellow teammate Firestorm. He is an affiliate of the Justice League of America under Superman. In the introductory episode to Cyborg, “The Seeds of Doom”, Cyborg’s abilities save Earth from Darkseid’s seeds, but as Superman warns, make Darkseid a dangerous enemy to Cyborg, so Cyborg joins the League.

Cyborg appears in the Teen Titans animated series, voiced by Khary Payton. This version of Cyborg is very similar to his comic book counterpart. His nickname is “Cy”, and like his teammates, in the animated series Cyborg is never referred to by his given name; however, he does take the alias “Stone” (based on his real last name) in the Season 3 episode “Deception”. The two main differences are his design and that he is more easygoing than his comics counterpart. His head is considerably more rounded and bald (based on his Titans Hunt counterpart), and his mechanical parts are bulkier. His primary weapon is a sonic cannon housed in his forearm; initially he uses only his right arm to fire, but later episodes reveal that his left arm has an identical cannon built into it as well. Other on-board weapons and tools, such as an acetylene torch, a remote-operated video camera, and several missile launchers, can be deployed as needed, and his arms and legs are detachable.

Cyborg is the Titans’ chief technician and gadgeteer. He is responsible for the construction of the Titan Tower’s electronic and security systems and the team’s main vehicles, the T-Car and the T-Ship. His most dominant personality faults featured in the series are his enormous appetite and a tendency to be overly vain about his work as a result, he fosters a special dislike for those who abuse his devices irresponsibly, especially Gizmo and Brother Blood. On occasion, Cyborg acts as the team’s second-in-command, but he tends to butt heads with Robin on rather trivial matters. In “Cyborg the Barbarian”, he was sent back to 3,000 B.C. There, he met a woman named Sarasim and fell in love with her. The relationship ended when Cyborg was brought back to his own time.

Cyborg’s age is never specified, but he mentions in “Deception” that he never had a chance to finish high school due to circumstances that made him what he is. The only time Cyborg’s personal history has been discussed is in “Deception”, in which he discusses his involuntary cyborg status with Starfire, and in the 4th season episode “The End: Part 2”. In this episode, Trigon creates duplicates of Cyborg, Starfire, and Beast Boy. These duplicates reflect the dark side of each character. During the fight between Cyborg and his duplicate, the dark duplicate says harmful things about Cyborgs mother and her death.

Cyborg appeared in the 15th episode of the fifth season of Smallville on the 16th February 2006 and is played by Lee Thompson Young. In this version, Victor is a former Metropolis High School football star. He is involved in a car accident that kills him, supposedly, and the rest of his family. However, he is secretly rebuilt by Cyntechnics scientists including Dr. Alistair Krieg, who experimented on a group of test subjects. Victor was the only test subject to survive the experiments. Cyntechnics was bought up by LuthorCorp shortly before Victor’s escape. Lex denies any knowledge of Cyntechnics’ secretive activities.

Although Victor’s cybernetic enhancements are entirely on the inside [under his skin] instead of exoskeletal as they are in the comics and other media, a shot of Clark Kent’s X-ray vision reveals that Victor’s cranial armor covers the same-shaped area as it does in the comics. He also bleeds a dark fluid as he does in the comics. Smallville never uses the name “Cyborg” in his first appearance. Instead, Victor refers to his enhancements as bionic.

Lee Thompson Young reprises his role of Cyborg in the season 6 episode “Justice”, episode about Green Arrow gathering together a group of individuals to combat Lex Luthor and his experiments. The episode premiered on 18 January 2007. In this episode, Victor has finally taken the name “Cyborg”, as Green Arrow’s team uses code names. Also on the team are Aquaman and Impulse. While Victor was last seen with a girlfriend named Katherine, he explains that his mechanical parts put a strain on the relationship. After their eventual break up, Victor states that it was Green Arrow who kept him from committing suicide. The episode also shows Cyborg wearing a stylized silver vest and black pants, and utilizing further enhancements Green Arrow gave him. One of his new functions allows him to hack into and disable security systems. While connecting to machines, Cyborg’s left eye glows red.

Teen Titans Go!

Cyborg appears as a member of the Teen Titans in this more humorous take on the DC Universe.

Cyborg appears as a playable character in Lego Batman 2. He has a laser eye and the ability to pull magnetic legos.

Cyborg appears as a playable character in the game. He appears to be a combination of a power/gadget character in game.

Read more:

Cyborg (Character) – Comic Vine

Artificial intelligence – Wikipedia

Intelligence demonstrated by machines

In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[1] More in detail, Kaplan and Haenlein define AI as a systems ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.[2] Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.

The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition, a phenomenon known as the AI effect, leading to the quip in Tesler’s Theorem, “AI is whatever hasn’t been done yet.”[4] For instance, optical character recognition is frequently excluded from “artificial intelligence”, having become a routine technology.[5] Modern machine capabilities generally classified as AI include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go),[7] autonomously operating cars, and intelligent routing in content delivery networks and military simulations.

Borrowing from the management literature, Kaplan and Haenlein classify artificial intelligence into three different types of AI systems: analytical, human-inspired, and humanized artificial intelligence.[8] Analytical AI has only characteristics consistent with cognitive intelligence generating cognitive representation of the world and using learning based on past experience to inform future decisions. Human-inspired AI has elements from cognitive as well as emotional intelligence, understanding, in addition to cognitive elements, also human emotions considering them in their decision making. Humanized AI shows characteristics of all types of competencies (i.e., cognitive, emotional, and social intelligence), able to be self-conscious and self-aware in interactions with others.

Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism,[9][10] followed by disappointment and the loss of funding (known as an “AI winter”),[11][12] followed by new approaches, success and renewed funding.[10][13] For most of its history, AI research has been divided into subfields that often fail to communicate with each other.[14] These sub-fields are based on technical considerations, such as particular goals (e.g. “robotics” or “machine learning”),[15] the use of particular tools (“logic” or artificial neural networks), or deep philosophical differences.[16][17][18] Subfields have also been based on social factors (particular institutions or the work of particular researchers).[14]

The traditional problems (or goals) of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects.[15] General intelligence is among the field’s long-term goals.[19] Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics. The AI field draws upon computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many others.

The field was founded on the claim that human intelligence “can be so precisely described that a machine can be made to simulate it”.[20] This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction and philosophy since antiquity.[21] Some people also consider AI to be a danger to humanity if it progresses unabated.[22] Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment.[23]

In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.[24][13]

Thought-capable artificial beings appeared as storytelling devices in antiquity,[25] and have been common in fiction, as in Mary Shelley’s Frankenstein or Karel apek’s R.U.R. (Rossum’s Universal Robots).[26] These characters and their fates raised many of the same issues now discussed in the ethics of artificial intelligence.[21]

The study of mechanical or “formal” reasoning began with philosophers and mathematicians in antiquity. The study of mathematical logic led directly to Alan Turing’s theory of computation, which suggested that a machine, by shuffling symbols as simple as “0” and “1”, could simulate any conceivable act of mathematical deduction. This insight, that digital computers can simulate any process of formal reasoning, is known as the ChurchTuring thesis.[27] Along with concurrent discoveries in neurobiology, information theory and cybernetics, this led researchers to consider the possibility of building an electronic brain. Turing proposed that “if a human could not distinguish between responses from a machine and a human, the machine could be considered “intelligent”.[28] The first work that is now generally recognized as AI was McCullouch and Pitts’ 1943 formal design for Turing-complete “artificial neurons”.

The field of AI research was born at a workshop at Dartmouth College in 1956.[30] Attendees Allen Newell (CMU), Herbert Simon (CMU), John McCarthy (MIT), Marvin Minsky (MIT) and Arthur Samuel (IBM) became the founders and leaders of AI research.[31] They and their students produced programs that the press described as “astonishing”: computers were learning checkers strategies (c. 1954)[33] (and by 1959 were reportedly playing better than the average human),[34] solving word problems in algebra, proving logical theorems (Logic Theorist, first run c. 1956) and speaking English.[35] By the middle of the 1960s, research in the U.S. was heavily funded by the Department of Defense[36] and laboratories had been established around the world.[37] AI’s founders were optimistic about the future: Herbert Simon predicted, “machines will be capable, within twenty years, of doing any work a man can do”. Marvin Minsky agreed, writing, “within a generation… the problem of creating ‘artificial intelligence’ will substantially be solved”.[9]

They failed to recognize the difficulty of some of the remaining tasks. Progress slowed and in 1974, in response to the criticism of Sir James Lighthill and ongoing pressure from the US Congress to fund more productive projects, both the U.S. and British governments cut off exploratory research in AI. The next few years would later be called an “AI winter”,[11] a period when obtaining funding for AI projects was difficult.

In the early 1980s, AI research was revived by the commercial success of expert systems,[39] a form of AI program that simulated the knowledge and analytical skills of human experts. By 1985, the market for AI had reached over a billion dollars. At the same time, Japan’s fifth generation computer project inspired the U.S and British governments to restore funding for academic research.[10] However, beginning with the collapse of the Lisp Machine market in 1987, AI once again fell into disrepute, and a second, longer-lasting hiatus began.[12]

In the late 1990s and early 21st century, AI began to be used for logistics, data mining, medical diagnosis and other areas.[24] The success was due to increasing computational power (see Moore’s law), greater emphasis on solving specific problems, new ties between AI and other fields (such as statistics, economics and mathematics), and a commitment by researchers to mathematical methods and scientific standards.[40] Deep Blue became the first computer chess-playing system to beat a reigning world chess champion, Garry Kasparov, on 11 May 1997.

In 2011, a Jeopardy! quiz show exhibition match, IBM’s question answering system, Watson, defeated the two greatest Jeopardy! champions, Brad Rutter and Ken Jennings, by a significant margin. Faster computers, algorithmic improvements, and access to large amounts of data enabled advances in machine learning and perception; data-hungry deep learning methods started to dominate accuracy benchmarks around 2012.[43] The Kinect, which provides a 3D bodymotion interface for the Xbox 360 and the Xbox One, uses algorithms that emerged from lengthy AI research[44] as do intelligent personal assistants in smartphones.[45] In March 2016, AlphaGo won 4 out of 5 games of Go in a match with Go champion Lee Sedol, becoming the first computer Go-playing system to beat a professional Go player without handicaps.[7][46] In the 2017 Future of Go Summit, AlphaGo won a three-game match with Ke Jie,[47] who at the time continuously held the world No. 1 ranking for two years.[48][49] This marked the completion of a significant milestone in the development of Artificial Intelligence as Go is an extremely complex game, more so than Chess.

According to Bloomberg’s Jack Clark, 2015 was a landmark year for artificial intelligence, with the number of software projects that use AI within Google increased from a “sporadic usage” in 2012 to more than 2,700 projects. Clark also presents factual data indicating that error rates in image processing tasks have fallen significantly since 2011.[50] He attributes this to an increase in affordable neural networks, due to a rise in cloud computing infrastructure and to an increase in research tools and datasets.[13] Other cited examples include Microsoft’s development of a Skype system that can automatically translate from one language to another and Facebook’s system that can describe images to blind people.[50] In a 2017 survey, one in five companies reported they had “incorporated AI in some offerings or processes”.[51][52] Around 2016, China greatly accelerated its government funding; given its large supply of data and its rapidly increasing research output, some observers believe it may be on track to becoming an “AI superpower”.[53][54]

A typical AI perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[1] An AI’s intended goal function can be simple (“1 if the AI wins a game of Go, 0 otherwise”) or complex (“Do actions mathematically similar to the actions that got you rewards in the past”). Goals can be explicitly defined, or can be induced. If the AI is programmed for “reinforcement learning”, goals can be implicitly induced by rewarding some types of behavior and punishing others.[a] Alternatively, an evolutionary system can induce goals by using a “fitness function” to mutate and preferentially replicate high-scoring AI systems; this is similar to how animals evolved to innately desire certain goals such as finding food, or how dogs can be bred via artificial selection to possess desired traits. Some AI systems, such as nearest-neighbor, instead reason by analogy; these systems are not generally given goals, except to the degree that goals are somehow implicit in their training data. Such systems can still be benchmarked if the non-goal system is framed as a system whose “goal” is to successfully accomplish its narrow classification task.[57]

AI often revolves around the use of algorithms. An algorithm is a set of unambiguous instructions that a mechanical computer can execute.[b] A complex algorithm is often built on top of other, simpler, algorithms. A simple example of an algorithm is the following recipe for optimal play at tic-tac-toe:

Many AI algorithms are capable of learning from data; they can enhance themselves by learning new heuristics (strategies, or “rules of thumb”, that have worked well in the past), or can themselves write other algorithms. Some of the “learners” described below, including Bayesian networks, decision trees, and nearest-neighbor, could theoretically, if given infinite data, time, and memory, learn to approximate any function, including whatever combination of mathematical functions would best describe the entire world. These learners could therefore, in theory, derive all possible knowledge, by considering every possible hypothesis and matching it against the data. In practice, it is almost never possible to consider every possibility, because of the phenomenon of “combinatorial explosion”, where the amount of time needed to solve a problem grows exponentially. Much of AI research involves figuring out how to identify and avoid considering broad swaths of possibilities that are unlikely to be fruitful.[59] For example, when viewing a map and looking for the shortest driving route from Denver to New York in the East, one can in most cases skip looking at any path through San Francisco or other areas far to the West; thus, an AI wielding an pathfinding algorithm like A* can avoid the combinatorial explosion that would ensue if every possible route had to be ponderously considered in turn.[61]

The earliest (and easiest to understand) approach to AI was symbolism (such as formal logic): “If an otherwise healthy adult has a fever, then they may have influenza”. A second, more general, approach is Bayesian inference: “If the current patient has a fever, adjust the probability they have influenza in such-and-such way”. The third major approach, extremely popular in routine business AI applications, are analogizers such as SVM and nearest-neighbor: “After examining the records of known past patients whose temperature, symptoms, age, and other factors mostly match the current patient, X% of those patients turned out to have influenza”. A fourth approach is harder to intuitively understand, but is inspired by how the brain’s machinery works: the artificial neural network approach uses artificial “neurons” that can learn by comparing itself to the desired output and altering the strengths of the connections between its internal neurons to “reinforce” connections that seemed to be useful. These four main approaches can overlap with each other and with evolutionary systems; for example, neural nets can learn to make inferences, to generalize, and to make analogies. Some systems implicitly or explicitly use multiple of these approaches, alongside many other AI and non-AI algorithms;[62] the best approach is often different depending on the problem.[64]

Learning algorithms work on the basis that strategies, algorithms, and inferences that worked well in the past are likely to continue working well in the future. These inferences can be obvious, such as “since the sun rose every morning for the last 10,000 days, it will probably rise tomorrow morning as well”. They can be nuanced, such as “X% of families have geographically separate species with color variants, so there is an Y% chance that undiscovered black swans exist”. Learners also work on the basis of “Occam’s razor”: The simplest theory that explains the data is the likeliest. Therefore, to be successful, a learner must be designed such that it prefers simpler theories to complex theories, except in cases where the complex theory is proven substantially better. Settling on a bad, overly complex theory gerrymandered to fit all the past training data is known as overfitting. Many systems attempt to reduce overfitting by rewarding a theory in accordance with how well it fits the data, but penalizing the theory in accordance with how complex the theory is. Besides classic overfitting, learners can also disappoint by “learning the wrong lesson”. A toy example is that an image classifier trained only on pictures of brown horses and black cats might conclude that all brown patches are likely to be horses. A real-world example is that, unlike humans, current image classifiers don’t determine the spatial relationship between components of the picture; instead, they learn abstract patterns of pixels that humans are oblivious to, but that linearly correlate with images of certain types of real objects. Faintly superimposing such a pattern on a legitimate image results in an “adversarial” image that the system misclassifies.[c][67][68][69]

Compared with humans, existing AI lacks several features of human “commonsense reasoning”; most notably, humans have powerful mechanisms for reasoning about “nave physics” such as space, time, and physical interactions. This enables even young children to easily make inferences like “If I roll this pen off a table, it will fall on the floor”. Humans also have a powerful mechanism of “folk psychology” that helps them to interpret natural-language sentences such as “The city councilmen refused the demonstrators a permit because they advocated violence”. (A generic AI has difficulty inferring whether the councilmen or the demonstrators are the ones alleged to be advocating violence.)[72][73][74] This lack of “common knowledge” means that AI often makes different mistakes than humans make, in ways that can seem incomprehensible. For example, existing self-driving cars cannot reason about the location nor the intentions of pedestrians in the exact way that humans do, and instead must use non-human modes of reasoning to avoid accidents.[75][76][77]

The overall research goal of artificial intelligence is to create technology that allows computers and machines to function in an intelligent manner. The general problem of simulating (or creating) intelligence has been broken down into sub-problems. These consist of particular traits or capabilities that researchers expect an intelligent system to display. The traits described below have received the most attention.[15]

Early researchers developed algorithms that imitated step-by-step reasoning that humans use when they solve puzzles or make logical deductions.[78] By the late 1980s and 1990s, AI research had developed methods for dealing with uncertain or incomplete information, employing concepts from probability and economics.[79]

These algorithms proved to be insufficient for solving large reasoning problems, because they experienced a “combinatorial explosion”: they became exponentially slower as the problems grew larger.[59] In fact, even humans rarely use the step-by-step deduction that early AI research was able to model. They solve most of their problems using fast, intuitive judgements.[80]

Knowledge representation[81] and knowledge engineering[82] are central to classical AI research. Some “expert systems” attempt to gather together explicit knowledge possessed by experts in some narrow domain. In addition, some projects attempt to gather the “commonsense knowledge” known to the average person into a database containing extensive knowledge about the world. Among the things a comprehensive commonsense knowledge base would contain are: objects, properties, categories and relations between objects;[83] situations, events, states and time;[84] causes and effects;[85] knowledge about knowledge (what we know about what other people know);[86] and many other, less well researched domains. A representation of “what exists” is an ontology: the set of objects, relations, concepts, and properties formally described so that software agents can interpret them. The semantics of these are captured as description logic concepts, roles, and individuals, and typically implemented as classes, properties, and individuals in the Web Ontology Language.[87] The most general ontologies are called upper ontologies, which attempt to provide a foundation for all other knowledge[88] by acting as mediators between domain ontologies that cover specific knowledge about a particular knowledge domain (field of interest or area of concern). Such formal knowledge representations can be used in content-based indexing and retrieval,[89] scene interpretation,[90] clinical decision support,[91] knowledge discovery (mining “interesting” and actionable inferences from large databases),[92] and other areas.[93]

Among the most difficult problems in knowledge representation are:

Intelligent agents must be able to set goals and achieve them.[100] They need a way to visualize the futurea representation of the state of the world and be able to make predictions about how their actions will change itand be able to make choices that maximize the utility (or “value”) of available choices.[101]

In classical planning problems, the agent can assume that it is the only system acting in the world, allowing the agent to be certain of the consequences of its actions.[102] However, if the agent is not the only actor, then it requires that the agent can reason under uncertainty. This calls for an agent that can not only assess its environment and make predictions, but also evaluate its predictions and adapt based on its assessment.[103]

Multi-agent planning uses the cooperation and competition of many agents to achieve a given goal. Emergent behavior such as this is used by evolutionary algorithms and swarm intelligence.[104]

Machine learning, a fundamental concept of AI research since the field’s inception,[105] is the study of computer algorithms that improve automatically through experience.[106][107]

Unsupervised learning is the ability to find patterns in a stream of input, without requiring a human to label the inputs first.[108] Supervised learning includes both classification and numerical regression, which requires a human to label the input data first. Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories. Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change.[107] Both classifiers and regression learners can be viewed as “function approximators” trying to learn an unknown (possibly implicit) function; for example, a spam classifier can be viewed as learning a function that maps from the text of an email to one of two categories, “spam” or “not spam”. Computational learning theory can assess learners by computational complexity, by sample complexity (how much data is required), or by other notions of optimization.[109] In reinforcement learning[110] the agent is rewarded for good responses and punished for bad ones. The agent uses this sequence of rewards and punishments to form a strategy for operating in its problem space.

Natural language processing[111] (NLP) gives machines the ability to read and understand human language. A sufficiently powerful natural language processing system would enable natural-language user interfaces and the acquisition of knowledge directly from human-written sources, such as newswire texts. Some straightforward applications of natural language processing include information retrieval, text mining, question answering[112] and machine translation.[113] Many current approaches use word co-occurrence frequencies to construct syntactic representations of text. “Keyword spotting” strategies for search are popular and scalable but dumb; a search query for “dog” might only match documents with the literal word “dog” and miss a document with the word “poodle”. “Lexical affinity” strategies use the occurrence of words such as “accident” to assess the sentiment of a document. Modern statistical NLP approaches can combine all these strategies as well as others, and often achieve acceptable accuracy at the page or paragraph level, but continue to lack the semantic understanding required to classify isolated sentences well. Besides the usual difficulties with encoding semantic commonsense knowledge, existing semantic NLP sometimes scales too poorly to be viable in business applications. Beyond semantic NLP, the ultimate goal of “narrative” NLP is to embody a full understanding of commonsense reasoning.[114]

Machine perception[115] is the ability to use input from sensors (such as cameras (visible spectrum or infrared), microphones, wireless signals, and active lidar, sonar, radar, and tactile sensors) to deduce aspects of the world. Applications include speech recognition,[116] facial recognition, and object recognition.[117] Computer vision is the ability to analyze visual input. Such input is usually ambiguous; a giant, fifty-meter-tall pedestrian far away may produce exactly the same pixels as a nearby normal-sized pedestrian, requiring the AI to judge the relative likelihood and reasonableness of different interpretations, for example by using its “object model” to assess that fifty-meter pedestrians do not exist.[118]

AI is heavily used in robotics.[119] Advanced robotic arms and other industrial robots, widely used in modern factories, can learn from experience how to move efficiently despite the presence of friction and gear slippage.[120] A modern mobile robot, when given a small, static, and visible environment, can easily determine its location and map its environment; however, dynamic environments, such as (in endoscopy) the interior of a patient’s breathing body, pose a greater challenge. Motion planning is the process of breaking down a movement task into “primitives” such as individual joint movements. Such movement often involves compliant motion, a process where movement requires maintaining physical contact with an object.[122][123] Moravec’s paradox generalizes that low-level sensorimotor skills that humans take for granted are, counterintuitively, difficult to program into a robot; the paradox is named after Hans Moravec, who stated in 1988 that “it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility”.[124][125] This is attributed to the fact that, unlike checkers, physical dexterity has been a direct target of natural selection for millions of years.[126]

Moravec’s paradox can be extended to many forms of social intelligence.[128][129] Distributed multi-agent coordination of autonomous vehicles remains a difficult problem.[130] Affective computing is an interdisciplinary umbrella that comprises systems which recognize, interpret, process, or simulate human affects. Moderate successes related to affective computing include textual sentiment analysis and, more recently, multimodal affect analysis (see multimodal sentiment analysis), wherein AI classifies the affects displayed by a videotaped subject.[134]

In the long run, social skills and an understanding of human emotion and game theory would be valuable to a social agent. Being able to predict the actions of others by understanding their motives and emotional states would allow an agent to make better decisions. Some computer systems mimic human emotion and expressions to appear more sensitive to the emotional dynamics of human interaction, or to otherwise facilitate humancomputer interaction.[135] Similarly, some virtual assistants are programmed to speak conversationally or even to banter humorously; this tends to give nave users an unrealistic conception of how intelligent existing computer agents actually are.[136]

Historically, projects such as the Cyc knowledge base (1984) and the massive Japanese Fifth Generation Computer Systems initiative (19821992) attempted to cover the breadth of human cognition. These early projects failed to escape the limitations of non-quantitative symbolic logic models and, in retrospect, greatly underestimated the difficulty of cross-domain AI. Nowadays, the vast majority of current AI researchers work instead on tractable “narrow AI” applications (such as medical diagnosis or automobile navigation).[137] Many researchers predict that such “narrow AI” work in different individual domains will eventually be incorporated into a machine with artificial general intelligence (AGI), combining most of the narrow skills mentioned in this article and at some point even exceeding human ability in most or all these areas.[19][138] Many advances have general, cross-domain significance. One high-profile example is that DeepMind in the 2010s developed a “generalized artificial intelligence” that could learn many diverse Atari games on its own, and later developed a variant of the system which succeeds at sequential learning.[139][140][141] Besides transfer learning,[142] hypothetical AGI breakthroughs could include the development of reflective architectures that can engage in decision-theoretic metareasoning, and figuring out how to “slurp up” a comprehensive knowledge base from the entire unstructured Web. Some argue that some kind of (currently-undiscovered) conceptually straightforward, but mathematically difficult, “Master Algorithm” could lead to AGI. Finally, a few “emergent” approaches look to simulating human intelligence extremely closely, and believe that anthropomorphic features like an artificial brain or simulated child development may someday reach a critical point where general intelligence emerges.[144][145]

Many of the problems in this article may also require general intelligence, if machines are to solve the problems as well as people do. For example, even specific straightforward tasks, like machine translation, require that a machine read and write in both languages (NLP), follow the author’s argument (reason), know what is being talked about (knowledge), and faithfully reproduce the author’s original intent (social intelligence). A problem like machine translation is considered “AI-complete”, because all of these problems need to be solved simultaneously in order to reach human-level machine performance.

There is no established unifying theory or paradigm that guides AI research. Researchers disagree about many issues.[146] A few of the most long standing questions that have remained unanswered are these: should artificial intelligence simulate natural intelligence by studying psychology or neurobiology? Or is human biology as irrelevant to AI research as bird biology is to aeronautical engineering?[16]Can intelligent behavior be described using simple, elegant principles (such as logic or optimization)? Or does it necessarily require solving a large number of completely unrelated problems?[17]

In the 1940s and 1950s, a number of researchers explored the connection between neurobiology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter’s turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton University and the Ratio Club in England.[147] By 1960, this approach was largely abandoned, although elements of it would be revived in the 1980s.

When access to digital computers became possible in the middle 1950s, AI research began to explore the possibility that human intelligence could be reduced to symbol manipulation. The research was centered in three institutions: Carnegie Mellon University, Stanford and MIT, and as described below, each one developed its own style of research. John Haugeland named these symbolic approaches to AI “good old fashioned AI” or “GOFAI”.[148] During the 1960s, symbolic approaches had achieved great success at simulating high-level thinking in small demonstration programs. Approaches based on cybernetics or artificial neural networks were abandoned or pushed into the background.[149]Researchers in the 1960s and the 1970s were convinced that symbolic approaches would eventually succeed in creating a machine with artificial general intelligence and considered this the goal of their field.

Economist Herbert Simon and Allen Newell studied human problem-solving skills and attempted to formalize them, and their work laid the foundations of the field of artificial intelligence, as well as cognitive science, operations research and management science. Their research team used the results of psychological experiments to develop programs that simulated the techniques that people used to solve problems. This tradition, centered at Carnegie Mellon University would eventually culminate in the development of the Soar architecture in the middle 1980s.[150][151]

Unlike Simon and Newell, John McCarthy felt that machines did not need to simulate human thought, but should instead try to find the essence of abstract reasoning and problem-solving, regardless of whether people used the same algorithms.[16] His laboratory at Stanford (SAIL) focused on using formal logic to solve a wide variety of problems, including knowledge representation, planning and learning.[152] Logic was also the focus of the work at the University of Edinburgh and elsewhere in Europe which led to the development of the programming language Prolog and the science of logic programming.[153]

Researchers at MIT (such as Marvin Minsky and Seymour Papert)[154] found that solving difficult problems in vision and natural language processing required ad-hoc solutionsthey argued that there was no simple and general principle (like logic) that would capture all the aspects of intelligent behavior. Roger Schank described their “anti-logic” approaches as “scruffy” (as opposed to the “neat” paradigms at CMU and Stanford).[17] Commonsense knowledge bases (such as Doug Lenat’s Cyc) are an example of “scruffy” AI, since they must be built by hand, one complicated concept at a time.[155]

When computers with large memories became available around 1970, researchers from all three traditions began to build knowledge into AI applications.[156] This “knowledge revolution” led to the development and deployment of expert systems (introduced by Edward Feigenbaum), the first truly successful form of AI software.[39] A key component of the system architecture for all expert systems is the knowledge base, which stores facts and rules that illustrate AI.[157] The knowledge revolution was also driven by the realization that enormous amounts of knowledge would be required by many simple AI applications.

By the 1980s, progress in symbolic AI seemed to stall and many believed that symbolic systems would never be able to imitate all the processes of human cognition, especially perception, robotics, learning and pattern recognition. A number of researchers began to look into “sub-symbolic” approaches to specific AI problems.[18] Sub-symbolic methods manage to approach intelligence without specific representations of knowledge.

This includes embodied, situated, behavior-based, and nouvelle AI. Researchers from the related field of robotics, such as Rodney Brooks, rejected symbolic AI and focused on the basic engineering problems that would allow robots to move and survive.[158] Their work revived the non-symbolic viewpoint of the early cybernetics researchers of the 1950s and reintroduced the use of control theory in AI. This coincided with the development of the embodied mind thesis in the related field of cognitive science: the idea that aspects of the body (such as movement, perception and visualization) are required for higher intelligence.

Within developmental robotics, developmental learning approaches are elaborated upon to allow robots to accumulate repertoires of novel skills through autonomous self-exploration, social interaction with human teachers, and the use of guidance mechanisms (active learning, maturation, motor synergies, etc.).[159][160]

Interest in neural networks and “connectionism” was revived by David Rumelhart and others in the middle of the 1980s.[163] Artificial neural networks are an example of soft computingthey are solutions to problems which cannot be solved with complete logical certainty, and where an approximate solution is often sufficient. Other soft computing approaches to AI include fuzzy systems, evolutionary computation and many statistical tools. The application of soft computing to AI is studied collectively by the emerging discipline of computational intelligence.[164]

Much of traditional GOFAI got bogged down on ad hoc patches to symbolic computation that worked on their own toy models but failed to generalize to real-world results. However, around the 1990s, AI researchers adopted sophisticated mathematical tools, such as hidden Markov models (HMM), information theory, and normative Bayesian decision theory to compare or to unify competing architectures. The shared mathematical language permitted a high level of collaboration with more established fields (like mathematics, economics or operations research).[d] Compared with GOFAI, new “statistical learning” techniques such as HMM and neural networks were gaining higher levels of accuracy in many practical domains such as data mining, without necessarily acquiring semantic understanding of the datasets. The increased successes with real-world data led to increasing emphasis on comparing different approaches against shared test data to see which approach performed best in a broader context than that provided by idiosyncratic toy models; AI research was becoming more scientific. Nowadays results of experiments are often rigorously measurable, and are sometimes (with difficulty) reproducible.[40][165] Different statistical learning techniques have different limitations; for example, basic HMM cannot model the infinite possible combinations of natural language. Critics note that the shift from GOFAI to statistical learning is often also a shift away from Explainable AI. In AGI research, some scholars caution against over-reliance on statistical learning, and argue that continuing research into GOFAI will still be necessary to attain general intelligence.

AI has developed a large number of tools to solve the most difficult problems in computer science. A few of the most general of these methods are discussed below.

Many problems in AI can be solved in theory by intelligently searching through many possible solutions:[174] Reasoning can be reduced to performing a search. For example, logical proof can be viewed as searching for a path that leads from premises to conclusions, where each step is the application of an inference rule.[175] Planning algorithms search through trees of goals and subgoals, attempting to find a path to a target goal, a process called means-ends analysis.[176] Robotics algorithms for moving limbs and grasping objects use local searches in configuration space.[120] Many learning algorithms use search algorithms based on optimization.

Simple exhaustive searches[177] are rarely sufficient for most real-world problems: the search space (the number of places to search) quickly grows to astronomical numbers. The result is a search that is too slow or never completes. The solution, for many problems, is to use “heuristics” or “rules of thumb” that prioritize choices in favor of those that are more likely to reach a goal and to do so in a shorter number of steps. In some search methodologies heuristics can also serve to entirely eliminate some choices that are unlikely to lead to a goal (called “pruning the search tree”). Heuristics supply the program with a “best guess” for the path on which the solution lies.[178] Heuristics limit the search for solutions into a smaller sample size.

A very different kind of search came to prominence in the 1990s, based on the mathematical theory of optimization. For many problems, it is possible to begin the search with some form of a guess and then refine the guess incrementally until no more refinements can be made. These algorithms can be visualized as blind hill climbing: we begin the search at a random point on the landscape, and then, by jumps or steps, we keep moving our guess uphill, until we reach the top. Other optimization algorithms are simulated annealing, beam search and random optimization.[179]

Evolutionary computation uses a form of optimization search. For example, they may begin with a population of organisms (the guesses) and then allow them to mutate and recombine, selecting only the fittest to survive each generation (refining the guesses). Classic evolutionary algorithms include genetic algorithms, gene expression programming, and genetic programming.[180] Alternatively, distributed search processes can coordinate via swarm intelligence algorithms. Two popular swarm algorithms used in search are particle swarm optimization (inspired by bird flocking) and ant colony optimization (inspired by ant trails).[181][182]

Logic[183] is used for knowledge representation and problem solving, but it can be applied to other problems as well. For example, the satplan algorithm uses logic for planning[184] and inductive logic programming is a method for learning.[185]

Several different forms of logic are used in AI research. Propositional logic[186] involves truth functions such as “or” and “not”. First-order logic[187] adds quantifiers and predicates, and can express facts about objects, their properties, and their relations with each other. Fuzzy set theory assigns a “degree of truth” (between 0 and 1) to vague statements such as “Alice is old” (or rich, or tall, or hungry) that are too linguistically imprecise to be completely true or false. Fuzzy logic is successfully used in control systems to allow experts to contribute vague rules such as “if you are close to the destination station and moving fast, increase the train’s brake pressure”; these vague rules can then be numerically refined within the system. Fuzzy logic fails to scale well in knowledge bases; many AI researchers question the validity of chaining fuzzy-logic inferences.[e][189][190]

Default logics, non-monotonic logics and circumscription[95] are forms of logic designed to help with default reasoning and the qualification problem. Several extensions of logic have been designed to handle specific domains of knowledge, such as: description logics;[83] situation calculus, event calculus and fluent calculus (for representing events and time);[84] causal calculus;[85] belief calculus;[191] and modal logics.[86]

Overall, qualitiative symbolic logic is brittle and scales poorly in the presence of noise or other uncertainty. Exceptions to rules are numerous, and it is difficult for logical systems to function in the presence of contradictory rules.[193]

Many problems in AI (in reasoning, planning, learning, perception, and robotics) require the agent to operate with incomplete or uncertain information. AI researchers have devised a number of powerful tools to solve these problems using methods from probability theory and economics.[194]

Bayesian networks[195] are a very general tool that can be used for a large number of problems: reasoning (using the Bayesian inference algorithm),[196] learning (using the expectation-maximization algorithm),[f][198] planning (using decision networks)[199] and perception (using dynamic Bayesian networks).[200] Probabilistic algorithms can also be used for filtering, prediction, smoothing and finding explanations for streams of data, helping perception systems to analyze processes that occur over time (e.g., hidden Markov models or Kalman filters).[200] Compared with symbolic logic, formal Bayesian inference is computationally expensive. For inference to be tractable, most observations must be conditionally independent of one another. Complicated graphs with diamonds or other “loops” (undirected cycles) can require a sophisticated method such as Markov Chain Monte Carlo, which spreads an ensemble of random walkers throughout the Bayesian network and attempts to converge to an assessment of the conditional probabilities. Bayesian networks are used on Xbox Live to rate and match players; wins and losses are “evidence” of how good a player is. AdSense uses a Bayesian network with over 300 million edges to learn which ads to serve.

A key concept from the science of economics is “utility”: a measure of how valuable something is to an intelligent agent. Precise mathematical tools have been developed that analyze how an agent can make choices and plan, using decision theory, decision analysis,[201] and information value theory.[101] These tools include models such as Markov decision processes,[202] dynamic decision networks,[200] game theory and mechanism design.[203]

The simplest AI applications can be divided into two types: classifiers (“if shiny then diamond”) and controllers (“if shiny then pick up”). Controllers do, however, also classify conditions before inferring actions, and therefore classification forms a central part of many AI systems. Classifiers are functions that use pattern matching to determine a closest match. They can be tuned according to examples, making them very attractive for use in AI. These examples are known as observations or patterns. In supervised learning, each pattern belongs to a certain predefined class. A class can be seen as a decision that has to be made. All the observations combined with their class labels are known as a data set. When a new observation is received, that observation is classified based on previous experience.[204]

A classifier can be trained in various ways; there are many statistical and machine learning approaches. The decision tree[205] is perhaps the most widely used machine learning algorithm. Other widely used classifiers are the neural network,[207]k-nearest neighbor algorithm,[g][209]kernel methods such as the support vector machine (SVM),[h][211]Gaussian mixture model,[212] and the extremely popular naive Bayes classifier.[i][214] Classifier performance depends greatly on the characteristics of the data to be classified, such as the dataset size, distribution of samples across classes, the dimensionality, and the level of noise. Model-based classifiers perform well if the assumed model is an extremely good fit for the actual data. Otherwise, if no matching model is available, and if accuracy (rather than speed or scalability) is the sole concern, conventional wisdom is that discriminative classifiers (especially SVM) tend to be more accurate than model-based classifiers such as “naive Bayes” on most practical data sets.[215]

Neural networks, or neural nets, were inspired by the architecture of neurons in the human brain. A simple “neuron” N accepts input from multiple other neurons, each of which, when activated (or “fired”), cast a weighted “vote” for or against whether neuron N should itself activate. Learning requires an algorithm to adjust these weights based on the training data; one simple algorithm (dubbed “fire together, wire together”) is to increase the weight between two connected neurons when the activation of one triggers the successful activation of another. The net forms “concepts” that are distributed among a subnetwork of shared[j] neurons that tend to fire together; a concept meaning “leg” might be coupled with a subnetwork meaning “foot” that includes the sound for “foot”. Neurons have a continuous spectrum of activation; in addition, neurons can process inputs in a nonlinear way rather than weighing straightforward votes. Modern neural nets can learn both continuous functions and, surprisingly, digital logical operations. Neural networks’ early successes included predicting the stock market and (in 1995) a mostly self-driving car.[k] In the 2010s, advances in neural networks using deep learning thrust AI into widespread public consciousness and contributed to an enormous upshift in corporate AI spending; for example, AI-related M&A in 2017 was over 25 times as large as in 2015.[218][219]

The study of non-learning artificial neural networks[207] began in the decade before the field of AI research was founded, in the work of Walter Pitts and Warren McCullouch. Frank Rosenblatt invented the perceptron, a learning network with a single layer, similar to the old concept of linear regression. Early pioneers also include Alexey Grigorevich Ivakhnenko, Teuvo Kohonen, Stephen Grossberg, Kunihiko Fukushima, Christoph von der Malsburg, David Willshaw, Shun-Ichi Amari, Bernard Widrow, John Hopfield, Eduardo R. Caianiello, and others.

The main categories of networks are acyclic or feedforward neural networks (where the signal passes in only one direction) and recurrent neural networks (which allow feedback and short-term memories of previous input events). Among the most popular feedforward networks are perceptrons, multi-layer perceptrons and radial basis networks.[220] Neural networks can be applied to the problem of intelligent control (for robotics) or learning, using such techniques as Hebbian learning (“fire together, wire together”), GMDH or competitive learning.[221]

Today, neural networks are often trained by the backpropagation algorithm, which had been around since 1970 as the reverse mode of automatic differentiation published by Seppo Linnainmaa,[222][223] and was introduced to neural networks by Paul Werbos.[224][225][226]

Hierarchical temporal memory is an approach that models some of the structural and algorithmic properties of the neocortex.[227]

To summarize, most neural networks use some form of gradient descent on a hand-created neural topology. However, some research groups, such as Uber, argue that simple neuroevolution to mutate new neural network topologies and weights may be competitive with sophisticated gradient descent approaches. One advantage of neuroevolution is that it may be less prone to get caught in “dead ends”.[228]

Deep learning is any artificial neural network that can learn a long chain of causal links. For example, a feedforward network with six hidden layers can learn a seven-link causal chain (six hidden layers + output layer) and has a “credit assignment path” (CAP) depth of seven. Many deep learning systems need to be able to learn chains ten or more causal links in length.[229] Deep learning has transformed many important subfields of artificial intelligence, including computer vision, speech recognition, natural language processing and others.[230][231][229]

According to one overview,[232] the expression “Deep Learning” was introduced to the Machine Learning community by Rina Dechter in 1986[233] and gained traction afterIgor Aizenberg and colleagues introduced it to Artificial Neural Networks in 2000.[234] The first functional Deep Learning networks were published by Alexey Grigorevich Ivakhnenko and V. G. Lapa in 1965.[235][pageneeded] These networks are trained one layer at a time. Ivakhnenko’s 1971 paper[236] describes the learning of a deep feedforward multilayer perceptron with eight layers, already much deeper than many later networks. In 2006, a publication by Geoffrey Hinton and Ruslan Salakhutdinov introduced another way of pre-training many-layered feedforward neural networks (FNNs) one layer at a time, treating each layer in turn as an unsupervised restricted Boltzmann machine, then using supervised backpropagation for fine-tuning. Similar to shallow artificial neural networks, deep neural networks can model complex non-linear relationships. Over the last few years, advances in both machine learning algorithms and computer hardware have led to more efficient methods for training deep neural networks that contain many layers of non-linear hidden units and a very large output layer.[238]

Deep learning often uses convolutional neural networks (CNNs), whose origins can be traced back to the Neocognitron introduced by Kunihiko Fukushima in 1980.[239] In 1989, Yann LeCun and colleagues applied backpropagation to such an architecture. In the early 2000s, in an industrial application CNNs already processed an estimated 10% to 20% of all the checks written in the US.[240]Since 2011, fast implementations of CNNs on GPUs havewon many visual pattern recognition competitions.[229]

CNNs with 12 convolutional layers were used in conjunction with reinforcement learning by Deepmind’s “AlphaGo Lee”, the program that beat a top Go champion in 2016.[241]

Early on, deep learning was also applied to sequence learning with recurrent neural networks (RNNs)[242] which are in theory Turing complete[243] and can run arbitrary programs to process arbitrary sequences of inputs. The depth of an RNN is unlimited and depends on the length of its input sequence; thus, an RNN is an example of deep learning.[229] RNNs can be trained by gradient descent[244][245][246] but suffer from the vanishing gradient problem.[230][247] In 1992, it was shown that unsupervised pre-training of a stack of recurrent neural networks can speed up subsequent supervised learning of deep sequential problems.[248]

Numerous researchers now use variants of a deep learning recurrent NN called the long short-term memory (LSTM) network published by Hochreiter & Schmidhuber in 1997.[249] LSTM is often trained by Connectionist Temporal Classification (CTC).[250] At Google, Microsoft and Baidu this approach has revolutionised speech recognition.[251][252][253] For example, in 2015, Google’s speech recognition experienced a dramatic performance jump of 49% through CTC-trained LSTM, which is now available through Google Voice to billions of smartphone users.[254] Google also used LSTM to improve machine translation,[255] Language Modeling[256] and Multilingual Language Processing.[257] LSTM combined with CNNs also improved automatic image captioning[258] and a plethora of other applications.

AI, like electricity or the steam engine, is a general purpose technology. There is no consensus on how to characterize which tasks AI tends to excel at.[259] While projects such as AlphaZero have succeeded in generating their own knowledge from scratch, many other machine learning projects require large training datasets.[260][261] Researcher Andrew Ng has suggested, as a “highly imperfect rule of thumb”, that “almost anything a typical human can do with less than one second of mental thought, we can probably now or in the near future automate using AI.”[262] Moravec’s paradox suggests that AI lags humans at many tasks that the human brain has specifically evolved to perform well.[126]

Games provide a well-publicized benchmark for assessing rates of progress. AlphaGo around 2016 brought the era of classical board-game benchmarks to a close. Games of imperfect knowledge provide new challenges to AI in the area of game theory.[263][264] E-sports such as StarCraft continue to provide additional public benchmarks.[265][266] There are many competitions and prizes, such as the Imagenet Challenge, to promote research in artificial intelligence. The most common areas of competition include general machine intelligence, conversational behavior, data-mining, robotic cars, and robot soccer as well as conventional games.[267]

The “imitation game” (an interpretation of the 1950 Turing test that assesses whether a computer can imitate a human) is nowadays considered too exploitable to be a meaningful benchmark.[268] A derivative of the Turing test is the Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA). As the name implies, this helps to determine that a user is an actual person and not a computer posing as a human. In contrast to the standard Turing test, CAPTCHA is administered by a machine and targeted to a human as opposed to being administered by a human and targeted to a machine. A computer asks a user to complete a simple test then generates a grade for that test. Computers are unable to solve the problem, so correct solutions are deemed to be the result of a person taking the test. A common type of CAPTCHA is the test that requires the typing of distorted letters, numbers or symbols that appear in an image undecipherable by a computer.

Proposed “universal intelligence” tests aim to compare how well machines, humans, and even non-human animals perform on problem sets that are generic as possible. At an extreme, the test suite can contain every possible problem, weighted by Kolmogorov complexity; unfortunately, these problem sets tend to be dominated by impoverished pattern-matching exercises where a tuned AI can easily exceed human performance levels.[270][271]

AI is relevant to any intellectual task. Modern artificial intelligence techniques are pervasive and are too numerous to list here. Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence; this phenomenon is described as the AI effect.

High-profile examples of AI include autonomous vehicles (such as drones and self-driving cars), medical diagnosis, creating art (such as poetry), proving mathematical theorems, playing games (such as Chess or Go), search engines (such as Google search), online assistants (such as Siri), image recognition in photographs, spam filtering, predicting flight delays,[274] prediction of judicial decisions[275] and targeting online advertisements.[276][277]

With social media sites overtaking TV as a source for news for young people and news organisations increasingly reliant on social media platforms for generating distribution,[278] major publishers now use artificial intelligence (AI) technology to post stories more effectively and generate higher volumes of traffic.[279]

AI is being applied to the high cost problem of dosage issueswhere findings suggested that AI could save $16 billion. In 2016, a ground breaking study in California found that a mathematical formula developed with the help of AI correctly determined the accurate dose of immunosuppressant drugs to give to organ patients.[280]

Artificial intelligence is breaking into the healthcare industry by assisting doctors. According to Bloomberg Technology, Microsoft has developed AI to help doctors find the right treatments for cancer.[281] There is a great amount of research and drugs developed relating to cancer. In detail, there are more than 800 medicines and vaccines to treat cancer. This negatively affects the doctors, because there are too many options to choose from, making it more difficult to choose the right drugs for the patients. Microsoft is working on a project to develop a machine called “Hanover”. Its goal is to memorize all the papers necessary to cancer and help predict which combinations of drugs will be most effective for each patient. One project that is being worked on at the moment is fighting myeloid leukemia, a fatal cancer where the treatment has not improved in decades. Another study was reported to have found that artificial intelligence was as good as trained doctors in identifying skin cancers.[282] Another study is using artificial intelligence to try and monitor multiple high-risk patients, and this is done by asking each patient numerous questions based on data acquired from live doctor to patient interactions.[283] One study was done with transfer learning, the machine performed a diagnosis similarly to a well-trained ophthalmologist, and could generate a decision within 30 seconds on whether or not the patient should be referred for treatment, with more than 95% percent accuracy.[284]

According to CNN, a recent study by surgeons at the Children’s National Medical Center in Washington successfully demonstrated surgery with an autonomous robot. The team supervised the robot while it performed soft-tissue surgery, stitching together a pig’s bowel during open surgery, and doing so better than a human surgeon, the team claimed.[285] IBM has created its own artificial intelligence computer, the IBM Watson, which has beaten human intelligence (at some levels). Watson not only won at the game show Jeopardy! against former champions,[286] but was declared a hero after successfully diagnosing a woman who was suffering from leukemia.[287]

Advancements in AI have contributed to the growth of the automotive industry through the creation and evolution of self-driving vehicles. As of 2016[update], there are over 30 companies utilizing AI into the creation of driverless cars. A few companies involved with AI include Tesla, Google, and Apple.[288]

Many components contribute to the functioning of self-driving cars. These vehicles incorporate systems such as braking, lane changing, collision prevention, navigation and mapping. Together, these systems, as well as high performance computers, are integrated into one complex vehicle.[289]

Recent developments in autonomous automobiles have made the innovation of self-driving trucks possible, though they are still in the testing phase. The UK government has passed legislation to begin testing of self-driving truck platoons in 2018.[290] Self-driving truck platoons are a fleet of self-driving trucks following the lead of one non-self-driving truck, so the truck platoons aren’t entirely autonomous yet. Meanwhile, the Daimler, a German automobile corporation, is testing the Freightliner Inspiration which is a semi-autonomous truck that will only be used on the highway.[291]

One main factor that influences the ability for a driver-less automobile to function is mapping. In general, the vehicle would be pre-programmed with a map of the area being driven. This map would include data on the approximations of street light and curb heights in order for the vehicle to be aware of its surroundings. However, Google has been working on an algorithm with the purpose of eliminating the need for pre-programmed maps and instead, creating a device that would be able to adjust to a variety of new surroundings.[292] Some self-driving cars are not equipped with steering wheels or brake pedals, so there has also been research focused on creating an algorithm that is capable of maintaining a safe environment for the passengers in the vehicle through awareness of speed and driving conditions.[293]

Another factor that is influencing the ability for a driver-less automobile is the safety of the passenger. To make a driver-less automobile, engineers must program it to handle high-risk situations. These situations could include a head-on collision with pedestrians. The car’s main goal should be to make a decision that would avoid hitting the pedestrians and saving the passengers in the car. But there is a possibility the car would need to make a decision that would put someone in danger. In other words, the car would need to decide to save the pedestrians or the passengers.[294] The programming of the car in these situations is crucial to a successful driver-less automobile.

Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation. The use of AI in banking can be traced back to 1987 when Security Pacific National Bank in US set-up a Fraud Prevention Task force to counter the unauthorised use of debit cards. Programs like Kasisto and Moneystream are using AI in financial services.

Banks use artificial intelligence systems today to organize operations, maintain book-keeping, invest in stocks, and manage properties. AI can react to changes overnight or when business is not taking place.[295] In August 2001, robots beat humans in a simulated financial trading competition.[296] AI has also reduced fraud and financial crimes by monitoring behavioral patterns of users for any abnormal changes or anomalies.[297]

The use of AI machines in the market in applications such as online trading and decision making has changed major economic theories.[298] For example, AI based buying and selling platforms have changed the law of supply and demand in that it is now possible to easily estimate individualized demand and supply curves and thus individualized pricing. Furthermore, AI machines reduce information asymmetry in the market and thus making markets more efficient while reducing the volume of trades. Furthermore, AI in the markets limits the consequences of behavior in the markets again making markets more efficient. Other theories where AI has had impact include in rational choice, rational expectations, game theory, Lewis turning point, portfolio optimization and counterfactual thinking.

In video games, artificial intelligence is routinely used to generate dynamic purposeful behavior in non-player characters (NPCs). In addition, well-understood AI techniques are routinely used for pathfinding. Some researchers consider NPC AI in games to be a “solved problem” for most production tasks. Games with more atypical AI include the AI director of Left 4 Dead (2008) and the neuroevolutionary training of platoons in Supreme Commander 2 (2010).[299][300]

Worldwide annual military spending on robotics rose from US$5.1 billion in 2010 to US$7.5 billion in 2015.[301][302] Military drones capable of autonomous action are widely considered a useful asset. In 2017, Vladimir Putin stated that “Whoever becomes the leader in (artificial intelligence) will become the ruler of the world”.[303][304] Many artificial intelligence researchers seek to distance themselves from military applications of AI.[305]

For financial statements audit, AI makes continuous audit possible. AI tools could analyze many sets of different information immediately. The potential benefit would be the overall audit risk will be reduced, the level of assurance will be increased and the time duration of audit will be reduced.[306]

It is possible to use AI to predict or generalize the behavior of customers from their digital footprints in order to target them with personalized promotions or build customer personas automatically.[307] A documented case reports that online gambling companies were using AI to improve customer targeting.[308]

Moreover, the application of Personality computing AI models can help reducing the cost of advertising campaigns by adding psychological targeting to more traditional sociodemographic or behavioral targeting.[309]

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Artificial intelligence – Wikipedia

Artificial Intelligence – Journal – Elsevier

This journal has partnered with Heliyon, an open access journal from Elsevier publishing quality peer reviewed research across all disciplines. Heliyons team of experts provides editorial excellence, fast publication, and high visibility for your paper. Authors can quickly and easily transfer their research from a Partner Journal to Heliyon without the need to edit, reformat or resubmit.>Learn more at Heliyon.com

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Artificial Intelligence – Journal – Elsevier

Benefits & Risks of Artificial Intelligence – Future of Life …

Many AI researchers roll their eyes when seeing this headline:Stephen Hawking warns that rise of robots may be disastrous for mankind. And as many havelost count of how many similar articles theyveseen.Typically, these articles are accompanied by an evil-looking robot carrying a weapon, and they suggest we should worry about robots rising up and killing us because theyve become conscious and/or evil.On a lighter note, such articles are actually rather impressive, because they succinctly summarize the scenario that AI researchers dontworry about. That scenario combines as many as three separate misconceptions: concern about consciousness, evil, androbots.

If you drive down the road, you have a subjective experience of colors, sounds, etc. But does a self-driving car have a subjective experience? Does it feel like anything at all to be a self-driving car?Although this mystery of consciousness is interesting in its own right, its irrelevant to AI risk. If you get struck by a driverless car, it makes no difference to you whether it subjectively feels conscious. In the same way, what will affect us humans is what superintelligent AIdoes, not how it subjectively feels.

The fear of machines turning evil is another red herring. The real worry isnt malevolence, but competence. A superintelligent AI is by definition very good at attaining its goals, whatever they may be, so we need to ensure that its goals are aligned with ours. Humans dont generally hate ants, but were more intelligent than they are so if we want to build a hydroelectric dam and theres an anthill there, too bad for the ants. The beneficial-AI movement wants to avoid placing humanity in the position of those ants.

The consciousness misconception is related to the myth that machines cant have goals.Machines can obviously have goals in the narrow sense of exhibiting goal-oriented behavior: the behavior of a heat-seeking missile is most economically explained as a goal to hit a target.If you feel threatened by a machine whose goals are misaligned with yours, then it is precisely its goals in this narrow sense that troubles you, not whether the machine is conscious and experiences a sense of purpose.If that heat-seeking missile were chasing you, you probably wouldnt exclaim: Im not worried, because machines cant have goals!

I sympathize with Rodney Brooks and other robotics pioneers who feel unfairly demonized by scaremongering tabloids,because some journalists seem obsessively fixated on robots and adorn many of their articles with evil-looking metal monsters with red shiny eyes. In fact, the main concern of the beneficial-AI movement isnt with robots but with intelligence itself: specifically, intelligence whose goals are misaligned with ours. To cause us trouble, such misaligned superhuman intelligence needs no robotic body, merely an internet connection this may enable outsmarting financial markets, out-inventing human researchers, out-manipulating human leaders, and developing weapons we cannot even understand. Even if building robots were physically impossible, a super-intelligent and super-wealthy AI could easily pay or manipulate many humans to unwittingly do its bidding.

The robot misconception is related to the myth that machines cant control humans. Intelligence enables control: humans control tigers not because we are stronger, but because we are smarter. This means that if we cede our position as smartest on our planet, its possible that we might also cede control.

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Benefits & Risks of Artificial Intelligence – Future of Life …

What is AI (artificial intelligence)? – Definition from …

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.

AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an AI system that is designed and trained for a particular task. Virtual personal assistants, such as Apple’s Siri, are a form of weak AI. Strong AI, also known as artificial general intelligence, is an AI system with generalized human cognitive abilities. When presented with an unfamiliar task, a strong AI system is able to find a solution without human intervention.

Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings, as well as access to Artificial Intelligence as a Service (AIaaS) platforms. AI as a Service allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment. Popular AI cloud offerings include Amazon AI services, IBM Watson Assistant, Microsoft Cognitive Services and Google AI services.

While AI tools present a range of new functionality for businesses,the use of artificial intelligence raises ethical questions. This is because deep learning algorithms, which underpin many of the most advanced AI tools, are only as smart as the data they are given in training. Because a human selects what data should be used for training an AI program, the potential for human bias is inherent and must be monitored closely.

Some industry experts believe that the term artificial intelligence is too closely linked to popular culture, causing the general public to have unrealistic fears about artificial intelligence and improbable expectations about how it will change the workplace and life in general. Researchers and marketers hope the label augmented intelligence, which has a more neutral connotation, will help people understand that AI will simply improve products and services, not replace the humans that use them.

Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, categorizes AI into four types, from the kind of AI systems that exist today to sentient systems, which do not yet exist. His categories are as follows:

AI is incorporated into a variety of different types of technology. Here are seven examples.

Artificial intelligence has made its way into a number of areas. Here are six examples.

The application of AI in the realm of self-driving cars raises security as well as ethical concerns. Cars can be hacked, and when an autonomous vehicle is involved in an accident, liability is unclear. Autonomous vehicles may also be put in a position where an accident is unavoidable, forcing the programming to make an ethical decision about how to minimize damage.

Another major concern is the potential for abuse of AI tools. Hackers are starting to use sophisticated machine learning tools to gain access to sensitive systems, complicating the issue of security beyond its current state.

Deep learning-based video and audio generation tools also present bad actors with the tools necessary to create so-called deepfakes, convincingly fabricated videos of public figures saying or doing things that never took place.

Despite these potential risks, there are few regulations governing the use AI tools, and where laws do exist, the typically pertain to AI only indirectly. For example, federal Fair Lending regulations require financial institutions to explain credit decisions to potential customers, which limit the extent to which lenders can use deep learning algorithms, which by their nature are typically opaque. Europe’s GDPR puts strict limits on how enterprises can use consumer data, which impedes the training and functionality of many consumer-facing AI applications.

In 2016, the National Science and Technology Council issued a report examining the potential role governmental regulation might play in AI development, but it did not recommend specific legislation be considered. Since that time the issue has received little attention from lawmakers.

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What is AI (artificial intelligence)? – Definition from …

A.I. Artificial Intelligence – Wikipedia

A.I. Artificial Intelligence, also known as A.I., is a 2001 American science fiction drama film directed by Steven Spielberg. The screenplay by Spielberg and screen story by Ian Watson were based on the 1969 short story “Supertoys Last All Summer Long” by Brian Aldiss. The film was produced by Kathleen Kennedy, Spielberg and Bonnie Curtis. It stars Haley Joel Osment, Jude Law, Frances O’Connor, Brendan Gleeson and William Hurt. Set in a futuristic post-climate change society, A.I. tells the story of David (Osment), a childlike android uniquely programmed with the ability to love.

Development of A.I. originally began with producer-director Stanley Kubrick, after he acquired the rights to Aldiss’ story in the early 1970s. Kubrick hired a series of writers until the mid-1990s, including Brian Aldiss, Bob Shaw, Ian Watson, and Sara Maitland. The film languished in protracted development for years, partly because Kubrick felt computer-generated imagery was not advanced enough to create the David character, who he believed no child actor would convincingly portray. In 1995, Kubrick handed A.I. to Spielberg, but the film did not gain momentum until Kubrick’s death in 1999. Spielberg remained close to Watson’s film treatment for the screenplay.

The film divided critics, with the overall balance being positive, and grossed approximately $235 million. The film was nominated for two Academy Awards at the 74th Academy Awards, for Best Visual Effects and Best Original Score (by John Williams).

In a 2016 BBC poll of 177 critics around the world, Steven Spielberg’s A.I. Artificial Intelligence was voted the eighty-third greatest film since 2000.[3] A.I. is dedicated to Stanley Kubrick.

In the late 22nd century, rising sea levels from global warming have wiped out coastal cities such as Amsterdam, Venice, and New York and drastically reduced the world’s population. A new type of robots called Mecha, advanced humanoids capable of thought and emotion, have been created.

David, a Mecha that resembles a human child and is programmed to display love for his owners, is given to Henry Swinton and his wife Monica, whose son Martin, after contracting a rare disease, has been placed in suspended animation and not expected to recover. Monica feels uneasy with David, but eventually warms to him and activates his imprinting protocol, causing him to have an enduring childlike love for her. David is befriended by Teddy, a robotic teddy bear that belonged to Martin.

Martin is cured of his disease and brought home. As he recovers, he grows jealous of David. He tricks David into entering the parents’s bedroom at night and cutting off a lock of Monica’s hair. This upsets the parents, particularly Henry, who fears David intended to injure them. At a pool party, one of Martin’s friends pokes David with a knife, activating David’s self-protection programming. David grabs Martin and they fall into the pool. Martin is saved from drowning, but Henry persuades Monica to return David to his creators for destruction. Instead, she abandons David and Teddy in the forest. She warns David to avoid all humans, and tells him to find other unregistered Mecha who can protect him.

David is captured for an anti-Mecha “Flesh Fair”, where obsolete, unlicensed Mecha are destroyed before cheering crowds. David is placed on a platform with Gigolo Joe, a male prostitute Mecha who is on the run after being framed for murder. Before the pair can be destroyed with acid, the crowd, thinking David is a real boy, begins booing and throwing things at the show’s emcee. In the chaos, David and Joe escape. Since Joe survived thanks to David, he agrees to help him find Blue Fairy, whom David remembers from The Adventures of Pinocchio, and believes can turn him into a real boy, allowing Monica to love him and take him home.

Joe and David make their way to the decadent resort town of Rouge City, where “Dr. Know”, a holographic answer engine, directs them to the top of Rockefeller Center in the flooded ruins of Manhattan. There, David meets a copy of himself and destroys it. He then meets Professor Hobby, his creator, who tells David he was built in the image of the professor’s dead son David. The engineers are thrilled by his ability to have a will without being programmed. He reveals they have been monitoring him to see how he progresses and altered Dr. Know to guide him to Manhattan, back to the lab he was created in. David finds more copies of him, as well as female versions called Darlene, that have been made there.

Disheartened, David lets himself fall from a ledge of the building. He is rescued by Joe, flying an amphibicopter he has stolen from the police who were pursuing him. David tells Joe he saw the Blue Fairy underwater, and wants to go down to meet her. Joe is captured by the authorities, who snare him with an electromagnet. Before he is pulled up, he activates the amphibicopter’s dive function for David, telling him to remember him for he declares “I am, I was.” David and Teddy dive to see the Fairy, which turns out to be a statue at the now-sunken Coney Island. The two become trapped when the Wonder Wheel falls on their vehicle. David repeatedly asks the Fairy to turn him into a real boy. Eventually the ocean freezes and David’s power source is depleted.

Two thousand years later, humans are extinct, and Manhattan is buried under glacial ice. The Mecha have evolved into an advanced silicon-based form called Specialists. They find David and Teddy, and discover they are original Mecha who knew living humans, making them special. The Specialists revive David and Teddy. David walks to the frozen Fairy statue, which collapses when he touches it. The Mecha use David’s memories to reconstruct the Swinton home. David asks the Specialists if they can make him human, but they cannot. However, he insists they recreate Monica from DNA from the lock of her hair, which Teddy has kept. The Mecha warn David that the clone can live for only a day, and that the process cannot be repeated. David spends the next day with Monica and Teddy. Before she drifts off to sleep, Monica tells David she has always loved him. Teddy climbs onto the bed and watches the two lie peacefully together.

Kubrick began development on an adaptation of “Super-Toys Last All Summer Long” in the late 1970s, hiring the story’s author, Brian Aldiss, to write a film treatment. In 1985, Kubrick asked Steven Spielberg to direct the film, with Kubrick producing.[6] Warner Bros. agreed to co-finance A.I. and cover distribution duties.[7] The film labored in development hell, and Aldiss was fired by Kubrick over creative differences in 1989.[8] Bob Shaw briefly served as writer, leaving after six weeks due to Kubrick’s demanding work schedule, and Ian Watson was hired as the new writer in March 1990. Aldiss later remarked, “Not only did the bastard fire me, he hired my enemy [Watson] instead.” Kubrick handed Watson The Adventures of Pinocchio for inspiration, calling A.I. “a picaresque robot version of Pinocchio”.[7][9]

Three weeks later, Watson gave Kubrick his first story treatment, and concluded his work on A.I. in May 1991 with another treatment of 90 pages. Gigolo Joe was originally conceived as a G.I. Mecha, but Watson suggested changing him to a male prostitute. Kubrick joked, “I guess we lost the kiddie market.”[7] Meanwhile, Kubrick dropped A.I. to work on a film adaptation of Wartime Lies, feeling computer animation was not advanced enough to create the David character. However, after the release of Spielberg’s Jurassic Park, with its innovative computer-generated imagery, it was announced in November 1993 that production of A.I. would begin in 1994.[10] Dennis Muren and Ned Gorman, who worked on Jurassic Park, became visual effects supervisors,[8] but Kubrick was displeased with their previsualization, and with the expense of hiring Industrial Light & Magic.[11]

“Stanley [Kubrick] showed Steven [Spielberg] 650 drawings which he had, and the script and the story, everything. Stanley said, ‘Look, why don’t you direct it and I’ll produce it.’ Steven was almost in shock.”

Producer Jan Harlan, on Spielberg’s first meeting with Kubrick about A.I.[12]

In early 1994, the film was in pre-production with Christopher “Fangorn” Baker as concept artist, and Sara Maitland assisting on the story, which gave it “a feminist fairy-tale focus”.[7] Maitland said that Kubrick never referred to the film as A.I., but as Pinocchio.[11] Chris Cunningham became the new visual effects supervisor. Some of his unproduced work for A.I. can be seen on the DVD, The Work of Director Chris Cunningham.[13] Aside from considering computer animation, Kubrick also had Joseph Mazzello do a screen test for the lead role.[11] Cunningham helped assemble a series of “little robot-type humans” for the David character. “We tried to construct a little boy with a movable rubber face to see whether we could make it look appealing,” producer Jan Harlan reflected. “But it was a total failure, it looked awful.” Hans Moravec was brought in as a technical consultant.[11]Meanwhile, Kubrick and Harlan thought A.I. would be closer to Steven Spielberg’s sensibilities as director.[14][15] Kubrick handed the position to Spielberg in 1995, but Spielberg chose to direct other projects, and convinced Kubrick to remain as director.[12][16] The film was put on hold due to Kubrick’s commitment to Eyes Wide Shut (1999).[17] After the filmmaker’s death in March 1999, Harlan and Christiane Kubrick approached Spielberg to take over the director’s position.[18][19] By November 1999, Spielberg was writing the screenplay based on Watson’s 90-page story treatment. It was his first solo screenplay credit since Close Encounters of the Third Kind (1977).[20] Spielberg remained close to Watson’s treatment, but removed various sex scenes with Gigolo Joe. Pre-production was briefly halted during February 2000, because Spielberg pondered directing other projects, which were Harry Potter and the Philosopher’s Stone, Minority Report and Memoirs of a Geisha.[17][21] The following month Spielberg announced that A.I. would be his next project, with Minority Report as a follow-up.[22] When he decided to fast track A.I., Spielberg brought Chris Baker back as concept artist.[16]

The original start date was July 10, 2000,[15] but filming was delayed until August.[23] Aside from a couple of weeks shooting on location in Oxbow Regional Park in Oregon, A.I. was shot entirely using sound stages at Warner Bros. Studios and the Spruce Goose Dome in Long Beach, California.[24]The Swinton house was constructed on Stage 16, while Stage 20 was used for Rouge City and other sets.[25][26] Spielberg copied Kubrick’s obsessively secretive approach to filmmaking by refusing to give the complete script to cast and crew, banning press from the set, and making actors sign confidentiality agreements. Social robotics expert Cynthia Breazeal served as technical consultant during production.[15][27] Haley Joel Osment and Jude Law applied prosthetic makeup daily in an attempt to look shinier and robotic.[4] Costume designer Bob Ringwood (Batman, Troy) studied pedestrians on the Las Vegas Strip for his influence on the Rouge City extras.[28] Spielberg found post-production on A.I. difficult because he was simultaneously preparing to shoot Minority Report.[29]

The film’s soundtrack was released by Warner Sunset Records in 2001. The original score was composed and conducted by John Williams and featured singers Lara Fabian on two songs and Josh Groban on one. The film’s score also had a limited release as an official “For your consideration Academy Promo”, as well as a complete score issue by La-La Land Records in 2015.[30] The band Ministry appears in the film playing the song “What About Us?” (but the song does not appear on the official soundtrack album).

Warner Bros. used an alternate reality game titled The Beast to promote the film. Over forty websites were created by Atomic Pictures in New York City (kept online at Cloudmakers.org) including the website for Cybertronics Corp. There were to be a series of video games for the Xbox video game console that followed the storyline of The Beast, but they went undeveloped. To avoid audiences mistaking A.I. for a family film, no action figures were created, although Hasbro released a talking Teddy following the film’s release in June 2001.[15]

A.I. had its premiere at the Venice Film Festival in 2001.[31]

A.I. Artificial Intelligence was released on VHS and DVD by Warner Home Video on March 5, 2002 in both a standard full-screen release with no bonus features, and as a 2-Disc Special Edition featuring the film in its original 1.85:1 anamorphic widescreen format as well as an eight-part documentary detailing the film’s development, production, music and visual effects. The bonus features also included interviews with Haley Joel Osment, Jude Law, Frances O’Connor, Steven Spielberg and John Williams, two teaser trailers for the film’s original theatrical release and an extensive photo gallery featuring production sills and Stanley Kubrick’s original storyboards.[32]

The film was released on Blu-ray Disc on April 5, 2011 by Paramount Home Media Distribution for the U.S. and by Warner Home Video for international markets. This release featured the film a newly restored high-definition print and incorporated all the bonus features previously included on the 2-Disc Special Edition DVD.[33]

The film opened in 3,242 theaters in the United States on June 29, 2001, earning $29,352,630 during its opening weekend. A.I went on to gross $78.62 million in US totals as well as $157.31 million in foreign countries, coming to a worldwide total of $235.93 million.[34]

Based on 192 reviews collected by Rotten Tomatoes, 73% of critics gave the film positive notices with a score of 6.6/10. The website’s critical consensus reads, “A curious, not always seamless, amalgamation of Kubrick’s chilly bleakness and Spielberg’s warm-hearted optimism. A.I. is, in a word, fascinating.”[35] By comparison, Metacritic collected an average score of 65, based on 32 reviews, which is considered favorable.[36]

Producer Jan Harlan stated that Kubrick “would have applauded” the final film, while Kubrick’s widow Christiane also enjoyed A.I.[37] Brian Aldiss admired the film as well: “I thought what an inventive, intriguing, ingenious, involving film this was. There are flaws in it and I suppose I might have a personal quibble but it’s so long since I wrote it.” Of the film’s ending, he wondered how it might have been had Kubrick directed the film: “That is one of the ‘ifs’ of film historyat least the ending indicates Spielberg adding some sugar to Kubrick’s wine. The actual ending is overly sympathetic and moreover rather overtly engineered by a plot device that does not really bear credence. But it’s a brilliant piece of film and of course it’s a phenomenon because it contains the energies and talents of two brilliant filmmakers.”[38] Richard Corliss heavily praised Spielberg’s direction, as well as the cast and visual effects.[39] Roger Ebert gave the film three stars, saying that it was “wonderful and maddening.”[40] Leonard Maltin, on the other hand, gives the film two stars out of four in his Movie Guide, writing: “[The] intriguing story draws us in, thanks in part to Osment’s exceptional performance, but takes several wrong turns; ultimately, it just doesn’t work. Spielberg rewrote the adaptation Stanley Kubrick commissioned of the Brian Aldiss short story ‘Super Toys Last All Summer Long’; [the] result is a curious and uncomfortable hybrid of Kubrick and Spielberg sensibilities.” However, he calls John Williams’ music score “striking”. Jonathan Rosenbaum compared A.I. to Solaris (1972), and praised both “Kubrick for proposing that Spielberg direct the project and Spielberg for doing his utmost to respect Kubrick’s intentions while making it a profoundly personal work.”[41] Film critic Armond White, of the New York Press, praised the film noting that “each part of David’s journey through carnal and sexual universes into the final eschatological devastation becomes as profoundly philosophical and contemplative as anything by cinema’s most thoughtful, speculative artists Borzage, Ozu, Demy, Tarkovsky.”[42] Filmmaker Billy Wilder hailed A.I. as “the most underrated film of the past few years.”[43] When British filmmaker Ken Russell saw the film, he wept during the ending.[44]

Mick LaSalle gave a largely negative review. “A.I. exhibits all its creators’ bad traits and none of the good. So we end up with the structureless, meandering, slow-motion endlessness of Kubrick combined with the fuzzy, cuddly mindlessness of Spielberg.” Dubbing it Spielberg’s “first boring movie”, LaSalle also believed the robots at the end of the film were aliens, and compared Gigolo Joe to the “useless” Jar Jar Binks, yet praised Robin Williams for his portrayal of a futuristic Albert Einstein.[45][not in citation given] Peter Travers gave a mixed review, concluding “Spielberg cannot live up to Kubrick’s darker side of the future.” But he still put the film on his top ten list that year for best movies.[46] David Denby in The New Yorker criticized A.I. for not adhering closely to his concept of the Pinocchio character. Spielberg responded to some of the criticisms of the film, stating that many of the “so called sentimental” elements of A.I., including the ending, were in fact Kubrick’s and the darker elements were his own.[47] However, Sara Maitland, who worked on the project with Kubrick in the 1990s, claimed that one of the reasons Kubrick never started production on A.I. was because he had a hard time making the ending work.[48] James Berardinelli found the film “consistently involving, with moments of near-brilliance, but far from a masterpiece. In fact, as the long-awaited ‘collaboration’ of Kubrick and Spielberg, it ranks as something of a disappointment.” Of the film’s highly debated finale, he claimed, “There is no doubt that the concluding 30 minutes are all Spielberg; the outstanding question is where Kubrick’s vision left off and Spielberg’s began.”[49]

Screenwriter Ian Watson has speculated, “Worldwide, A.I. was very successful (and the 4th highest earner of the year) but it didn’t do quite so well in America, because the film, so I’m told, was too poetical and intellectual in general for American tastes. Plus, quite a few critics in America misunderstood the film, thinking for instance that the Giacometti-style beings in the final 20 minutes were aliens (whereas they were robots of the future who had evolved themselves from the robots in the earlier part of the film) and also thinking that the final 20 minutes were a sentimental addition by Spielberg, whereas those scenes were exactly what I wrote for Stanley and exactly what he wanted, filmed faithfully by Spielberg.”[50]

In 2002, Spielberg told film critic Joe Leydon that “People pretend to think they know Stanley Kubrick, and think they know me, when most of them don’t know either of us”. “And what’s really funny about that is, all the parts of A.I. that people assume were Stanley’s were mine. And all the parts of A.I. that people accuse me of sweetening and softening and sentimentalizing were all Stanley’s. The teddy bear was Stanley’s. The whole last 20 minutes of the movie was completely Stanley’s. The whole first 35, 40 minutes of the film all the stuff in the house was word for word, from Stanley’s screenplay. This was Stanley’s vision.” “Eighty percent of the critics got it all mixed up. But I could see why. Because, obviously, I’ve done a lot of movies where people have cried and have been sentimental. And I’ve been accused of sentimentalizing hard-core material. But in fact it was Stanley who did the sweetest parts of A.I., not me. I’m the guy who did the dark center of the movie, with the Flesh Fair and everything else. That’s why he wanted me to make the movie in the first place. He said, ‘This is much closer to your sensibilities than my own.'”[51]

Upon rewatching the film many years after its release, BBC film critic Mark Kermode apologized to Spielberg in an interview in January 2013 for “getting it wrong” on the film when he first viewed it in 2001. He now believes the film to be Spielberg’s “enduring masterpiece”.[52]

Visual effects supervisors Dennis Muren, Stan Winston, Michael Lantieri and Scott Farrar were nominated for the Academy Award for Best Visual Effects, while John Williams was nominated for Best Original Music Score.[53] Steven Spielberg, Jude Law and Williams received nominations at the 59th Golden Globe Awards.[54] A.I. was successful at the Saturn Awards, winning five awards, including Best Science Fiction Film along with Best Writing for Spielberg and Best Performance by a Younger Actor for Osment.[55]

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A.I. Artificial Intelligence – Wikipedia

Artificial Intelligence: The Pros, Cons, and What to Really Fear

For the last several years, Russia has been steadily improving its ground combat robots. Just last year,Kalashnikov, the maker of the famous AK-47 rifle,announced it would builda range of products based on neural networks, including a fully automated combat module that promises to identify and shoot at targets.

According to Bendett,Russia delivered a white paperto the UN saying that from Moscow’s perspective,it would be inadmissible to leave UASwithout anyhuman oversight. In other words, Russia always wants a human in the loop and to be the one to push the final button to fire that weapon.

Worth noting: “A lot of these are still kind of far-out applications,” Bendett said.

The same can be said for China’s more military-focused applications of AI, largely in surveillance and UAV operations for the PLA,said Elsa Kania, Technology Fellow at the Center for a New American Security. Speaking beside Bendett at the Genius Machines event in March, Kania said China’s military applications appear to beat a a fairly nascent stage in its development.

That is to say: There’snothing to fear about lethal AI applications yet unless you’re an alleged terrorist in the Middle East. For the rest of us, we have our Siris, Alexas, Cortanas and more, helping us shop, search, listen to music,and tag friends in images on social media.

Until the robot uprising comes, let us hope there will always be clips ofthe swearing Atlas Robot from Boston Dynamics available online whenever we need a laugh. It may be better to laugh before these robots start helping each other through doorwaysentirely independent of humans. (Too late.)

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Artificial Intelligence: The Pros, Cons, and What to Really Fear

A.I. Artificial Intelligence (2001) – IMDb

Nominated for 2 Oscars. Another 17 wins & 68 nominations. See more awards Learn more More Like This

Comedy | Drama | Sci-Fi

An android endeavors to become human as he gradually acquires emotions.

Director:Chris Columbus

Stars:Robin Williams,Embeth Davidtz,Sam Neill

Adventure | Sci-Fi | Thriller

As Earth is invaded by alien tripod fighting machines, one family fights for survival.

Director:Steven Spielberg

Stars:Tom Cruise,Dakota Fanning,Tim Robbins

Action | Crime | Mystery

In a future where a special police unit is able to arrest murderers before they commit their crimes, an officer from that unit is himself accused of a future murder.

Director:Steven Spielberg

Stars:Tom Cruise,Colin Farrell,Samantha Morton

Drama | History

In 1839, the revolt of Mende captives aboard a Spanish owned ship causes a major controversy in the United States when the ship is captured off the coast of Long Island. The courts must decide whether the Mende are slaves or legally free.

Director:Steven Spielberg

Stars:Djimon Hounsou,Matthew McConaughey,Anthony Hopkins

Drama | History | War

Young Albert enlists to serve in World War I after his beloved horse is sold to the cavalry. Albert’s hopeful journey takes him out of England and to the front lines as the war rages on.

Director:Steven Spielberg

Stars:Jeremy Irvine,Emily Watson,David Thewlis

Drama | Sci-Fi

Roy Neary, an electric lineman, watches how his quiet and ordinary daily life turns upside down after a close encounter with a UFO.

Director:Steven Spielberg

Stars:Richard Dreyfuss,Franois Truffaut,Teri Garr

Drama | History | War

A young English boy struggles to survive under Japanese occupation during World War II.

Director:Steven Spielberg

Stars:Christian Bale,John Malkovich,Miranda Richardson

Drama | History | Thriller

Based on the true story of the Black September aftermath, about the five men chosen to eliminate the ones responsible for that fateful day.

Director:Steven Spielberg

Stars:Eric Bana,Daniel Craig,Marie-Jose Croze

In the not-so-far future the polar ice caps have melted and the resulting rise of the ocean waters has drowned all the coastal cities of the world. Withdrawn to the interior of the continents, the human race keeps advancing, reaching the point of creating realistic robots (called mechas) to serve them. One of the mecha-producing companies builds David, an artificial kid which is the first to have real feelings, especially a never-ending love for his “mother”, Monica. Monica is the woman who adopted him as a substitute for her real son, who remains in cryo-stasis, stricken by an incurable disease. David is living happily with Monica and her husband, but when their real son returns home after a cure is discovered, his life changes dramatically. Written byChris Makrozahopoulos

Budget:$100,000,000 (estimated)

Opening Weekend USA: $29,352,630,1 July 2001, Wide Release

Gross USA: $78,616,689, 23 September 2001

Cumulative Worldwide Gross: $235,927,000

Runtime: 146 min

Aspect Ratio: 1.85 : 1

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A.I. Artificial Intelligence (2001) – IMDb

Online Artificial Intelligence Courses | Microsoft …

The Microsoft Professional Program (MPP) is a collection of courses that teach skills in several core technology tracks that help you excel in the industry’s newest job roles.

These courses are created and taught by experts and feature quizzes, hands-on labs, and engaging communities. For each track you complete, you earn a certificate of completion from Microsoft proving that you mastered those skills.

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Online Artificial Intelligence Courses | Microsoft …

What is Artificial Intelligence (AI)? – Definition from …

Artificial intelligence is a branch of computer science that aims to create intelligent machines. It has become an essential part of the technology industry.

Research associated with artificial intelligence is highly technical and specialized. The core problems of artificial intelligence include programming computers for certain traits such as:

Knowledge engineering is a core part of AI research. Machines can often act and react like humans only if they have abundant information relating to the world. Artificial intelligence must have access to objects, categories, properties and relations between all of them to implement knowledge engineering. Initiating common sense, reasoning and problem-solving power in machines is a difficult and tedious task.

Machine learning is also a core part of AI. Learning without any kind of supervision requires an ability to identify patterns in streams of inputs, whereas learning with adequate supervision involves classification and numerical regressions. Classification determines the category an object belongs to and regression deals with obtaining a set of numerical input or output examples, thereby discovering functions enabling the generation of suitable outputs from respective inputs. Mathematical analysis of machine learning algorithms and their performance is a well-defined branch of theoretical computer science often referred to as computational learning theory.

Machine perception deals with the capability to use sensory inputs to deduce the different aspects of the world, while computer vision is the power to analyze visual inputs with a few sub-problems such as facial, object and gesture recognition.

Robotics is also a major field related to AI. Robots require intelligence to handle tasks such as object manipulation and navigation, along with sub-problems of localization, motion planning and mapping.

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What is Artificial Intelligence (AI)? – Definition from …

Artificial Intelligence: The Robots Are Now Hiring – WSJ

Sept. 20, 2018 5:30 a.m. ET

Some Fortune 500 companies are using tools that deploy artificial intelligence to weed out job applicants. But is this practice fair? In this episode of Moving Upstream, WSJ’s Jason Bellini investigates.

Some Fortune 500 companies are using tools that deploy artificial intelligence to weed out job applicants. But is this practice fair? In this episode of Moving Upstream, WSJ’s Jason Bellini investigates.

Hiring is undergoing a profound revolution.

Nearly all Fortune 500 companies now use some form of automation — from robot avatars interviewing job candidates to computers weeding out potential employees by scanning keywords in resumes. And more and more companies are using artificial intelligence and machine learning tools to assess possible employees.

DeepSense, based in San Francisco and India, helps hiring managers scan peoples social media accounts to surface underlying personality traits. The company says it uses a scientifically based personality test, and it can be done with or without a potential candidates knowledge.

The practice is part of a general trend of some hiring companies to move away from assessing candidates based on their resumes and skills, towards making hiring decisions based on peoples personalities.

The Robot Revolution: An inside look at how humanoid robots are evolving.

WSJS Jason Bellini explores breakthrough technologies that are reshaping our world and beginning to impact human happiness, health and productivity. Catch the latest episode by signing up here.

Cornell sociology and law professor Ifeoma Ajunwa said shes concerned about these tools potential for bias. Given the large scale of these automatic assessments, she believes potentially faulty algorithms could do more damage than one biased human manager. And she wants scientists to test if the algorithms are fair, transparent and accurate.

In the episode of Moving Upstream above, correspondent Jason Bellini visits South Jordan, Utah-based HireVue, which is delivering AI-based assessments of digital interviews to over 50 companies. HireVue says its algorithm compares candidates tone of voice, word clusters and micro facial expressionsCC with people who have previously been identified as high performers on the job.

Write to Jason Bellini at jason.bellini@wsj.com and Hilke Schellmann at hilke.schellmann@wsj.com

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Artificial Intelligence: The Robots Are Now Hiring – WSJ

Scientists to Test New Cancer Treatment on Human Patients in 2019

A new cancer treatment that uses the body's own immune system to fight cancer is scheduled to start human trials in 2019.

Cancer Treatment

A new cancer treatment that uses the body’s own immune system to fight cancer is scheduled to start human trials in 2019.

The U.K.’s Telegraph reports that the new treatment, devised by researchers at the Francis Crick Institute in London, uses implanted immune system cells from strangers to fight tumors, instead of old-school cancer treatments like chemotherapy — a new tack in oncology that the researchers say could boost cancer ten-year cancer survival rates from 50 percent to 75 percent.

Immune System

The scientists behind the project explained it as a “do-it-yourself” approach to cancer treatment in interviews with the Telegraph. Instead of relying on chemicals or radiation outside the body to fight tumors, the transplants aim to help the bodies of cancer patients fight the tumors on their own.

“It’s a very exciting time,” said Charlie Swanton, one of the Francis Crick researchers involved in the work, in an interview with the paper. “Using the body’s own immune cells to target the tumor is elegant because tumours evolve so quickly there is no way a pharmaceutical company can keep up with it, but the immune system has been evolving for over four billion years to do just that.”

“Rapidly Treated Diseases”

Swanton told the Telegraph that he believes the trials could lead to a whole new tool set that doctors will be able to use to fight cancer.

“I would go so far as to say that we might reach a point, maybe 20 years from now, where the vast majorities of cancers are rapidly treated diseases or long-term chronic issues that you can manage,” he said. “And I think the immune system will be essential in doing that.”

READ MORE: Cancer breakthrough: Scientists say immune system transplants mean ‘future is incredibly bright’ [The Telegraph]

More on cancer research: Researchers May Have Discovered a New Way to Kill off Cancer Cells

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Scientists to Test New Cancer Treatment on Human Patients in 2019

Holograms Are Resurrecting Dead Musicians, Raising Legal Questions

Dead Musicians

Michael Jackson. Amy Winehouse. Tupac. Roy Orbison.

Those are just a few of the dead musicians who have been resurrected on stage in recent years as holograms — and a new feature by the Australian Broadcasting Corporation explores not just the critical reception and technological frontiers of the new industry, but the legal minefield it raises to dust off the visage of a famous person and bring them out on the road.

Back to Life

According to University of Sydney digital human researcher Mike Seymour, today’s musical holograms have only started to tap the medium’s potential. In the future, he predicted to the ABC, machine learning will let these long-dead holograms interact with the crowd and improvise.

Additionally, according to the report, the law is still grappling with how to handle life-after-death performances. In the U.S., a legal concept called a “right to publicity” gives a person, or their estate, the right to profit from their likeness. But whether right to publicity applies after death, and for how long, differs between states.

Atrocity

Of course, no legal or technical measures will win over fans of an act who find it disrespectful to raise a performer from death and trot them out on tour.

“If you are appalled by [the idea], because you think it’s an atrocity to the original act, you are going to hate it,” Seymour told the broadcaster. “And if you are a fan that just loves seeing that song being performed again, you are going to think it’s the best thing ever.”

READ MORE: Dead musicians are touring again, as holograms. It’s tricky — technologically and legally [Australian Broadcasting Corporation]

More on hologram performances: Wildly Famous Japanese Pop Star Sells Thousands of Tickets in NYC. Also, She’s A Hologram

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Holograms Are Resurrecting Dead Musicians, Raising Legal Questions

New Theory: The Universe is a Bubble, Inflated by Dark Energy

A mind-bending new theory claims to make sense not just of the expanding universe and extra dimensions, but string theory and dark energy as well.

Dark Energy

A mind-bending new theory claims to make sense not just of the expanding universe and extra dimensions, but string theory and dark energy as well.

According to the new model, proposed in the journal Physical Review Letters by researchers from Uppsala University, the entire universe is riding on an expanding bubble in an “additional dimension” — which is being inflated by dark energy and which is home to strings that extend outwards from it and correspond to all the matter that it contains.

Breaking It Down

The paper is extraordinarily dense and theoretical. But the surprising new theory it lays out, its authors say, could provide new insights about the creation and ultimate destiny of the cosmos.

In the long view, though, physicists have suggested many outrageous models for the universe over the years — many of which we’ve covered here at Futurism. The reality: until a theory not only conforms to existing evidence but helps explain new findings, the road to a consensus will be long.

READ MORE: Our universe: An expanding bubble in an extra dimension [Uppsala University]

More on dark energy: An Oxford Scientist May Have Solved the Mystery of Dark Matter

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New Theory: The Universe is a Bubble, Inflated by Dark Energy

Poll: Two Thirds of Americans Support Human Gene Editing to Cure Disease

The majority of U.S. adults would support gene editing embryos to protect babies against disease, according to a new poll.

Human Gene Editing

The majority of U.S. adults support human gene editing to protect babies against disease, according to a new poll.

But they wouldn’t support gene edits that make babies smarter or taller, according to the new research by the Associated Press-NORC Center for Public Affairs Research, which polled about a thousand U.S. adults this month to learn about public attitudes toward genetic engineering.

Deep Divides

The AP research found that 71 percent of respondents support gene editing to protect a baby from an inherited condition, and 67 percent support reducing the risk of diseases like cancer.

But just 12 percent would be okay with tampering with intelligence or athletic ability, and only 10 percent would consider altering physical characteristics like eye color or height.

CRISPR Drawer

Questions about using technologies like CRISPR to gene edit human embryos gained immediacy last month, when Chinese scientists claimed to have edited the genes of two babies in order to protect them against HIV — a move that prompted an international outcry, but also questions about when the technology will be ready for human testing.

“People appear to realize there’s a major question of how we should oversee and monitor use of this technology if and when it becomes available,” Columbia University bioethicist Robert Klitzman told the AP of the new research. “What is safe enough? And who will determine that? The government? Or clinicians who say, ‘Look, we did it in Country X a few times and it seems to be effective.

READ MORE: Poll: Edit baby genes for health, not smarts [Associated Press]

More on human gene editing: Chinese Scientists Claim to Have Gene-Edited Human Babies For the First Time

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Poll: Two Thirds of Americans Support Human Gene Editing to Cure Disease