In this April 30, 2015, file photo, Tesla Motors CEO Elon Musk unveils the company's newest products, in Hawthorne, Calif. Ringo H.W. Chiu/AP hide caption

In this April 30, 2015, file photo, Tesla Motors CEO Elon Musk unveils the company's newest products, in Hawthorne, Calif.

One of Tesla CEO Elon Musk's companies, the nonprofit start-up OpenAI, manufactures a device that last week was victorious in defeating some of the world's top gamers in an international video game (e-sport) tournament with a multi-million-dollar pot of prize money.

We're getting very good, it seems, at making machines that can outplay us at our favorite pastimes. Machines dominate Go, Jeopardy, Chess and as of now at least some video games.

Instead of crowing over the win, though, Musk is sounding the alarm. Artificial Intelligence, or AI, he argued last week, poses a far greater risk to us now than even North Korean warheads.

No doubt Musk's latest pronouncements make for good advertising copy. What better way to drum up interest in a product than to announce that, well, it has the power to destroy the world.

But is it true? Is AI a greater threat to mankind than the threat posed to us today by an openly hostile, well-armed and manifestly unstable enemy?

AI means, at least, three things.

First, it means machines that are faster, stronger and smarter than us, machines that may one day soon, HAL-like, come to make their own decisions and make up their own values and, so, even to rule over us, just as we rule over the cows. This is a very scary thought, not the least when you consider how we have ruled over the cows.

Second, AI means really good machines for doing stuff. I used to have a coffee machine that I'd set with a timer before going to bed; in the morning I'd wake up to the smell of fresh coffee. My coffee maker was a smart, or at least smart-ish, device. Most of the smart technologies, the AIs, in our phones, and airplanes, and cars, and software programs including the ones winning tournaments are pretty much like this. Only more so. They are vastly more complicated and reliable but they are, finally, only smart-ish. The fact that some of these new systems "learn," and that they come to be able to do things that their makers cannot do like win at Go or Dota is really beside the point. A steam hammer can do what John Henry can't but, in the end, the steam hammer doesn't really do anything.

Third, AI is a research program. I don't mean a program in high-tech engineering. I mean, rather, a program investigating the nature of the mind itself. In 1950, the great mathematician Alan Turing published a paper in a philosophy journal in which he argued that by the year 2000 we would find it entirely natural to speak of machines as intelligent. But more significantly, working as a mathematician, he had devised a formal system for investigating the nature of computation that showed, as philosopher Daniel Dennett puts it in his recent book, that you can get competence (the ability to solve problems) without comprehension (by merely following blind rules mechanically). It was not long before philosopher Hilary Putnam would hypothesize the mind is a Turing Machine (and a Turing Machine just is, for all intents and purposes, what we call a computer today). And, thus, the circle closes. To study computational minds is to study our minds, and to build an AI is, finally, to try to reverse engineer ourselves.

Now, Type 3 AI, this research program, is alive and well and a continuing chapter in our intellectual history that is of genuine excitement and importance. This, even though the original hypothesis of Putnam is wildly implausible (and was given up by Putnam decades ago). To give just one example: the problem of the inputs and the outputs. A Turing Machine works by performing operations on inputs. For example, it might erase a 1 on a cell of its tape and replace it with a 0. The whole method depends on being able to give a formal specification of a finite number of inputs and outputs. We can see how that goes for 1s and 0s. But what are the inputs, and what are the outputs, for a living animal, let alone a human being? Can we give a finite list, and specify its items in formal terms, of everything we can perceive, let alone, do?

And there are other problems, too. To mention only one: We don't understand how the brain works. And this means that we don't know that the brain functions, in any sense other than metaphorical, like a computer.

Type 1 AI, the nightmare of machine dominance, is just that, a nightmare, or maybe (for the capitalists making the gizmos) a fantasy. Depending on what we learn pursuing the philosophy of AI, and as luminaries like John Searle and the late Hubert Dreyfus have long argued, it may be an impossible fiction.

Whatever our view on this, there can be no doubt that the advent of smart, rather than smart-ish, machines, the sort of machines that might actually do something intelligent on their own initiative, is a long way off. Centuries off. The threat of nuclear war with North Korea is both more likely and more immediate than this.

Which does not mean, though, that there is not in fact real cause for alarm posed by AI. But if so, we need to turn our attention to Type 2 AI: the smart-ish technologies that are everywhere in our world today. The danger here is not posed by the technologies themselves. They aren't out to get us. They are not going to be out to get us any time soon. The danger, rather, is our increasing dependence on them. We have created a technosphere in which we are beholden to technologies and processes that we do not understand. I don't mean you and me, that we don't understand: No one person can understand. It's all gotten too complicated. It takes a whole team or maybe a university to understand adequately all the mechanisms, for example, that enable air traffic control, or drug manufacture, or the successful production and maintenance of satellites, or the electricity grid, not to mention your car.

Now this is not a bad thing in itself. We are not isolated individuals all alone and we never have been. We are a social animal and it is fine and good that we should depend on each other and on our collective.

But are we rising to the occasion? Are we tending our collective? Are we educating our children and organizing our means of production to keep ourselves safe and self-reliant and moving forward? Are we taking on the challenges that, to some degree, are of our own making? How to feed 7 billion people in a rapidly warming world?

Or have we settled? Too many of us, I fear, have taken up a "user" attitude to the gear of our world. We are passive consumers. Like the child who thinks chickens come from supermarkets, we are hopelessly alienated from how things work.

And if we are, then what are we going to do if some clever young person some where maybe a young lady in North Korea writes a program to turn things off? This is a serious and immediate pressing danger.

Alva No is a philosopher at the University of California, Berkeley, where he writes and teaches about perception, consciousness and art. He is the author of several books, including his latest, Strange Tools: Art and Human Nature (Farrar, Straus and Giroux, 2015). You can keep up with more of what Alva is thinking on Facebook and on Twitter: @alvanoe

See the article here:

Is AI More Threatening Than North Korean Missiles? - NPR

By Peter Holley The Washington Post

For decades, the world's smartest game-playing humans have been racking up losses to increasingly sophisticated forms of artificial intelligence.

The defeats began in the 1990s when Deep Blue conquered chess master Garry Kasparov. In May, Ke Jie - until then the world's best player of the ancient Chinese board game "Go" - was defeated by a Google computer program.

Now the AI supergamers have moved into the world of e-sports. Last week, an artificial intelligence bot created by the Elon Musk-backed start-up OpenAI defeated some of the world's most talented players of Dota 2, a fast-paced, highly complex, multiplayer online video game that draws fierce competition from all over the globe.

OpenAI unveiled its bot at an annual Dota 2 tournament where players walk away with millions in prize money. It was a pivotal moment in gaming and in AI research largely because of how the bot developed its skills and how long it took to refine them enough to defeat the world's most talented pros, according to Greg Brockman, co-founder and chief technology officer of OpenAI.

The somewhat frightening reality: It only took the bot two weeks to go from laughable novice to world-class competitor, a period in which Brockman said the bot gathered "lifetimes" of experience by playing itself.

During that period, players said, the bot went from behaving like a bot to behaving in a way that felt more alive.

Danylo "Dendi" Ishutin, one of the game's top players, was defeated twice by his AI competition, which felt "a little like human, but a little like something else," he said, according to the Verge.

Brockman agreed with that perspective: "You kind of see that this thing is super fast and no human can execute its moves as well, but it was also strategic, and it kind of knows what you're going to do," he said. "When you go off screen, for example, it would predict what you were going to do next. That's not something we expected."

Brockman said games are a great testing ground for AI because they offer a defined set of rules with "baked-in complexity" that allow developers to measure a bot's changing skill level. He said one of the major revelations of the Dota 2 bot's success was that it was achieved via "self-play" - a form of training in which the bot would continuously play against a copy of itself until it amassed more and more knowledge while improving incrementally.

For a game as complicated as Dota 2 - which incorporates more than 100 playable roles and thousands of moves - self-play proved more organic and comprehensive than having a human preprogram the bot's behavior.

"If you're a novice playing against someone who is awesome - playing tennis against Serena Williams, for example - you're going to be crushed, and you won't realize there are slightly better techniques or ways of doing something," Brockman said. "The magic happens when your opponent is exactly balanced with you so that if you . . . explore and find a slightly better strategy it is then reflected in your performance in the game."

Tesla chief executive Elon Musk hailed the bot's achievement in historic fashion on Twitter before going on to once again highlight the risk posed by AI, which he said poses "vastly more risk than North Korea."

Musk unleashed a debate about the danger of AI last month when he tweeted that Facebook chief executive Mark Zuckerberg's understanding of the threat posed by AI "is limited."

Read this article:

'It knew what you were going to do next': AI learns from pro gamers - then crushes them - News Chief

Credit: Silver Logic Labs

Silver Logic Labs (SLL) is in the people business. Technically, its an AI startup, but what it really does is figure out what people want. At first glance theyve simply found a better way to do focus-groups, but after talking to CEO Jerimiah Hamon weve learned theres nothing simple about the work hes doing.

The majority of AI in the world is being taught to do boring stuff. The machines are learning to analyze data, and scrape websites. Theyre being forced to to sew shirts and watch us sleep. Hamon and his team created an algorithm that analyzes the tiniest of human movements, using a camera, and determines what that person is feeling.

Credit: Silver Logic Labs

Dont worry if your mind isnt blown right now it takes a little explanation to sink in. Imagine youre trying to determine whether a TV show will be popular with an audience and youve gathered a group of test-viewers whove just seen your show. How do you know if theyre responding honestly, or simply trying to respond in the way they think they should. Hamon told us:

You have these situations where youre trying to determine how people feel about something that could possibly be considered controversial, or that people might not want to be honest about. You might have a scene with two men kissing each other, or two women. You might have a scene where a dog gets hit by a car in such a way that its supposed to be funny.

Well find, sometimes, people will respond that they didnt like those things, but then when we analyze what they were doing while they were watching it, and we pick up these details and we see theyre expressing joy, or arousal, quite often.

And were better at predicting whether that show is going to do well based on our insight, than if you just go by how people respond to the list of questions.

SLL is trying to solve one of the oldest problems in the world: people lie. In fact, according to the fictional Dr. House, M.D. Everybody lies. More importantly though, Hamon who is not-at-all fictional told us:

With our system we find that we get a lot more data. We can use it to watch every second and compare every second to every other second in a way a person watching cant. So when asked Can you predict a Nielsen rating? the answer is yes, the lowest accuracy rating weve got is about 89% thats the lowest.

Being able to determine the viability of a TV show, or how people feel about a specific scene in a movie is a pretty neat trick. The fact that theyve adapted the technology to work with almost any laptop camera for survey purposes such as observing someone watching a video clip at home is astounding.

Hamon told us that the algorithms work so well his team almost always ends up flunking certain respondents for being under the influence of a substance. A drug detecting robot that can be employed through any connected camera? Thats a little spooky.

SLL does more than provide analytics for TV shows and movies, in fact its ambitions might be some of the highest weve ever seen for an AI company. We asked Hamon how this technology was supposed to be used outside of simply detecting if someone liked something or not:

Im very passionate about health care. With this we can identify neural-deficits very quickly. We did a lot of research and it turns out its proven that if youre going to have a stroke, you will have a series of micro-strokes first. These are undetectable most of the time, sometimes even to the people having them if you live at a nursing home for instance, we could have cameras set up, we could detect those.

These people might have a one percent change in gait, we could see that for example, our system might be able to detect the first of the micro-strokes and signal for help.

The company also wants to change the way law enforcement works. Hamon believes that dash-cams and body-cams that utilize this technology will save lives. He proposed a what-if scenario:

Say youve got someone running up to a building and theres someone on guard, they might see this person running who, incidentally, has just lost their baby and needs help as a threat, maybe due to a lack of training or because theyre scared.

The other side is maybe you see someone running and think they need your help when in reality they have a pound of explosives in their backpack. We know that how a person moves is different based on how they feel. People make these decisions under extreme pressure and theyre not always right.

There are even more uses for educational applications. The potential to determine exactly how students respond to a teacher, or to tailor a specific lesson to an individual could help a lot of people, especially those who arent benefiting from traditional methods.

Its about time someone created an AI that helps us better understand each other in a practical sense that might actually save lives.

Read next: Your social media use is helping scientists monitor the worlds ecosystems

Read the original post:

AI can determine our motivations using a simple camera - TNW

The heart of Home is Essential's operating system, Ambient OS. Rubin didn't share much about the new software, but he did share his thoughts about how AI will become the next big operating system.

"I think it's AI. It's a slightly different AI than we see today. Today we see pattern matching and vision tricks and automation for self-driving cars and assistants like Siri or Google Assistant, but I think there's a thing after that that will coalesce into something that's more of an operating platform."

Rubin knows his own hardware company can't create the master AI platform alone, which is why his incubator Playground is so important.

"We're investing in hardware companies because we think they're essential in training AI," Rubin said. "One of our invested companies is called Light House. They make a camera for your home like a Dropcam except it uses AI to analyze everything that's happening in your house. You can ask if the kids went to school on time and it can answer."

Essential Home will allow you to play music through popular services, check the weather and more, all through a circular touchscreen.

But unlike other systems, like the Amazon Echo or Google Home, his plan is to create an OS that works with everything else. It's an ambitious goal with serious technical challenges, but Rubin knows enough about operating systems that he shouldn't be ignored.

See the rest here:

The man behind Android says AI is the next major operating system - CNBC

We are only human, and our recollections are imperfect. So when we try to create an account of our past, can we trust ourselves? That's the question at the heart of the new film Marjorie Prime, which opens today in 15 cities (with a national rollout to eventually follow). It is a quiet, contemplative drama that studies our fear of technology and mortality by juxtaposing people with computerized versions of themselves. Thanks to convincing performances by Jon Hamm (Walter Prime), Lois Smith (Marjorie/Marjorie Prime) and Geena Davis (Tess/Tess Prime), the movie forces us to consider if we're to blame for all the times AI goes awry. It also questions whether we're entrusting technology with too much responsibility.

In Marjorie Prime, the holograms (usually of the deceased) are meant to provide comfort, although they sometimes act as caretakers. For example, Walter Prime obligingly tells Marjorie stories of how he wooed her and when he proposed, based on the tales she had told him in the past. It's an unconventional form of therapy, but the act of talking to a loved one without fear of judgment can be just as cathartic as traditional counseling. Walter Prime also reminds Marjorie to eat, calmly questioning the excuses she comes up with to avoid doing so. By contrast, Marjorie's human caretaker, Julie, sneaks the ailing woman cigarettes when Tess and Jon aren't around.

Compared with AI, people's imperfections stand out. These imperfections are passed on to the Primes. The stories that Marjorie shares with Walter Prime (that he later tells back to her) are the versions she wants to remember. For a variety of reasons, she casually changes details like the movie she was watching with her late husband when he proposed, and even the people involved in certain events. The Primes are also designed to mimic verbal signs of hesitation like stuttering or pausing to appear more realistic, and thus more flawed.

The film challenges our mistrust of AI and technology, showing that if anything is untrustworthy, it's our own memories. We are the ones who contaminate software with our own biases. We don't need Marjorie Prime to show us that -- our own world today is full of examples: Microsoft's AI chatbot Tay, who was turned racist by Twitter users, and the company's subsequent bot Zo, who met the same fate. Some believe that in the US justice system, the use of algorithms that predict a person's potential for recidivism as a way to determine punishment is inherently biased. AI is a man-made product, and its flaws are created by us. It is also our fault when we entrust the technology with responsibilities, like making them our therapists, as the characters in Marjorie Prime have done, however unwittingly.

The film eventually takes its central idea to the logical conclusion, where we find out whether AI can even fool themselves into thinking they're human.

The questions of trusting AI and contrasting humans with machines have already been heavily explored (think: Her or the episode "Be Right Back" in Black Mirror), but Marjorie Prime delves deeper into how human nature is to blame. Yet it withholds judgement and shows how we can't help our failings, especially as we age. The beauty of humanity often lies in its flaws, and it's something AI can imitate but not fully replicate.

See more here:

'Marjorie Prime' explores the limits of AI built from memories - Engadget

AI is now able to synthesize new sounds from old ones, and even compose original music

"Can machines be creative?" This question is the target of a recent Google undertaking, dubbed Project Magenta,focused on bringing artificial intelligence into the art world.

Magenta and other creative AI endeavors draw on the power of deep neural networks, systems that allow computers to sort through large amounts of data, recognizing patterns, and eventually generating their own pictures, music and more. These networks had previously been put to artistic use by Google for its "DeepDream" project, which was designed to visualize how neural networks think. Researchers could feed the tool images, which it thenreinterpretedinto often abstract, and oftentrippy, works.

Last year, Google started Project Magenta to apply what it learned from these AI-created masterpieces to further push the limits of computer creativity in art, music, videos and more. Now,TheNew York Times'Cade Metz tuned into the software giant's recent projects to see (and hear) what's come of the endeavor.

Along with the announcement of Project Magenta last summer, Google released the neural network's first song. The Google team gave its algorithm four notes (C, C, G, G) to work with, and then let the machine compose a roughly 90-second song with a piano sound.The littleditty is upbeat, starting slow but picking up with a drum beat added behind it as it explores patterns using those four notes.

But now, Google programmers are using those networks to not only create new pieces of music, but new instruments. For example, a tool calledNSynth, has analyzed hundreds of notes played by a variety of modern instruments, mapping out the features that makea guitar sound like a guitar, or a trumpet sound like a trumpet. Using these maps, users can then combine instrument characteristics to create brandnew sound makers.

A more recent project from Google trained an algorithm with examples of classical piano music to create a tool that can compose its own music within the framework of classical piano techniques, reports MatthewHutsonforScience. While you won't findPerformanceRNN, as the algorithm is called, composing a symphony any time soon, it can create short original music phrasings that are "quite expressive," as programmersIan Simon andSageevOorewrote last month on the Project Magenta blog. And another algorithm has been trained from Magenta's code to be able to respond to notes that people play with its own original snippets of music, in effect creating a "duet" with an AI.

Other Google algorithms have worked on edging more into the visual art world, reportsHutson. For example, the algorithmSketchRNNhas analyzed thousands of examples of human drawings to teach a computer to create basic sketches of common shapes, such aschairs, cats and trucks.

Once these models have been "trained," writes Google researcher David Ha, the computercan analyze and recreate previously submitted drawings in original ways. It can even correctmistakes researchers added in to make the images appear more accurate, such as drawing a pig with four legs instead of five.Similar to the blended instruments ofNSynth, artists can game these models by doing things like submitting drawings of chairs to a program that draws cats, creating blended sketches that lie somewhere between the shapes.

Some other projects haven't worked out just yet,Hutsonreports, such as a tool to create new jokes. (They just weren't funny.)

Google aren't the only ones interested in artsy AI. As Metz notes, last year, researchers at Sony trained an neural network tocompose new songs in the styles of existing artistseven creatinganpop songthat resemblesa composition from the Beatles. Another neural networkcomposed its ownChristmas songwhen shown a picture of a Christmas tree.

Though some people are concerned that AI could replace us all, developers don't see these tools as ever supplanting human creativity,Hutsonreports. But rather, these algorithms are tools that can helpinspire and channel imagination into new creations.

Maybe one day, your muse could be a computer.

Like this article? SIGN UP for our newsletter

Read more:

AI Is Edging Into the Art World in Psychedelic Ways - Smithsonian

August 19, 2017 by Liz Thomas Predictions for an AI-dominated future are increasingly common, but Antoine Blondeau has experience in reading, and arguably manipulating, the runeshe helped develop technology that evolved into predictive texting and Apple's Siri

It's 2050 and the world revolves around you. From the contents of your fridge to room temperaturedigital assistants ensure your home runs smoothly. Your screens know your taste and show channels you want to see as you enter the room. Your car is driverless and your favourite barman may just be an android.

Predictions for an AI-dominated future are increasingly common, but Antoine Blondeau has experience in reading, and arguably manipulating, the runeshe helped develop technology that evolved into predictive texting and Apple's Siri.

"In 30 years the world will be very different," he says, adding: "Things will be designed to meet your individual needs."

Work, as we know it, will be redundant, he saysvisual and sensory advances in robotics will see smart factories make real time decisions requiring only human oversight rather than workers, while professions such as law, journalism, accounting and retail will be streamlined with AI doing the grunt work.

Healthcare is set for a revolution, with individuals holding all the data about their general health and AI able to diagnose ailments, he explains.

Blondeau says: "If you have a doctor's appointment, it will be perhaps for the comfort of talking things through with a human, or perhaps because regulation will dictate a human needs to dispense medicine. But you won't necessarily need the doctor to tell you what is wrong."

The groundwork has been done: Amazon's Alexa and Google Home are essentially digital butlers that can respond to commands as varied as ordering pizza to managing appliances, while Samsung is working on a range of 'smart' fridges, capable of giving daily news briefings, ordering groceries, or messaging your family at your request.

Leading media companies are already using 'AI journalists' to produce simple economics and sports stories from data and templates created by their human counterparts.

Blondeau's firm Sentient Technologies has already successfully used AI traders in the financial markets.

In partnership with US retailer , it created an interactive 'smart shopper', which uses an algorithm that picks up information from gauging not just what you like, but what you don't, offering suggestions in the way a real retail assistant would.

In healthcare, the firm worked with America's MIT to invent an AI nurse able to assess patterns in blood pressure data from thousands of patients to correctly identify those developing sepsisa catastrophic immune reaction30 minutes before the outward onset of the condition more than 90 percent of the time in trials.

"It's a critical window that doctors say gives them the extra time to save lives," Blondeau says, but concedes that bringing such concepts to the masses is difficult.

"The challenge is to pass to market because of regulations but also because people have an intrinsic belief you can trust a doctor, but will they trust a machine?" he adds.

Law, he says, is the next industry ripe for change. In June, he became chairman of Hong Kong's Dragon Law. The dynamic start-up is credited with helping overhaul the legal industry by making it more accessible and affordable.

For many the idea of mass AI-caused redundancy is terrifying, but Blondeau is pragmatic: humans simply need to rethink careers and education.

"The era where you exit the education system at 16, 21, or 24 and that is it, is broadly gone," he explains.

"People will have to retrain and change skillsets as the technology evolves."

Blondeau disagrees that having a world so catered to your whims and wants might lead to a myopic life, a magnified version of the current social media echo chamber, arguing that it is possible to inject 'serendipity' into the technology, to throw up surprises.

While computers have surpassed humans at specific tasks and games such as chess or Go, predictions of a time when they develop artificial general intelligence (AGI) enabling them to perform any intellectual task an adult can range from as early as 2030 to the end of the century.

Blondeau, who was chief executive at tech firm Dejima when it worked on CALOone of the biggest AI projects in US historyand developed a precursor to Siri, is more circumspect.

"We will get to some kind of AGI, but its not a given that we will create something that could match our intuition," muses Blondeau, who was also a chief operating officer at Zi Corporation, a leader in predictive text.

"AI might make a better trader, maybe a better customer operative, but will it make a better husband? That machine will need to look at a lot of cases to develop its own intuition. That will take a long time," he says.

The prospect of AI surpassing human capabilities has divided leaders in science and technology.

Microsoft's Bill Gates, British physicist Stephen Hawking and maverick entrepreneur Elon Musk have all sounded the alarm warning unchecked AI could lead to the destruction of mankind.

Yet Blondeau seems unflinchingly positive, pointing out nuclear technology too could have spelled armageddon.

He explains: "Like any invention it can be used for good and bad. So we have to safeguard in each industry. There will be checks along the way, we are not going to wake up one day and suddenly realise the machines are aware."

Explore further: Apple readying Siri-powered home assistant: report

2017 AFP

Apple is preparing to launch a connected speaker to serve as a smart home assistant in a challenge to Amazon Echo and Google Home, a news report said Thursday.

Intelligent machines of the future will help restore memory, mind your children, fetch your coffee and even care for aging parents.

Robots have been taking our jobs since the 1960s. So why are politicians and business leaders only now becoming so worried about robots causing mass unemployment?

Major technology firms are racing to infuse smartphones and other internet-linked devices with software smarts that help them think like people.

That's the name of Samsung's virtual assistant, a key feature of the new Galaxy S8 phone. The Korean company has big plans for the voice-based technology, seeing it as a fundamental way its customers will interact with a ...

Google CEO Sundar Pichai believes that we are moving to an "AI-first" world. In this world, we will be interacting with personal digital assistants on a range of platforms, including through Google's new intelligent speaker ...

If disaster ever struck, Joe Fleischmann could keep the lights, refrigerator and big-screen TV running in his Orange County home, even if the power company went dark.

Standing in a warehouse in a Moscow suburb, Dmitry Marinichev tries to speak over the deafening hum of hundreds of computers stacked on shelves hard at work mining for crypto money.

Buildings could soon be able to convert the sun's energy into electricity without the need for solar panels, thanks to innovative new technology.

Battery researchers agree that one of the most promising possibilities for future battery technology is the lithium-air (or lithium-oxygen) battery, which could provide three times as much power for a given weight as today's ...

Distracted drivingtexting or absent-mindednessclaims thousands of lives a year. Researchers from the University of Houston and the Texas A&M Transportation Institute have produced an extensive dataset examining how ...

Facebook's interest in China has led it to discreetly create a photo-sharing application released there without the social network's brand being attached.

Adjust slider to filter visible comments by rank

Display comments: newest first

It will "all be about" milking humans. To transfer money from the humans bank accounts to the owner of the AI. (or at least those humans who still have jobs)

Nice prophecy. But i doubt it'll happen THAT quickly.

By then these will all be smart, all talking to each other. Economies of scale will make them as ubiquitous as they are now. Nothing manufactured will NOT be smart.

And people will be able to buy them because the economies of scale requires it. How they earn the money to do so is not readily apparent.

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Read more from the original source:

AI revolution will be all about humans, says Siri trailblazer - Phys.Org