The Highest Performance Next-Gen Porsche 911 Could Be a Hybrid

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The new generation of the Porsche 911 sports car will include a hybrid model — and it could be the highest-performance version of the iconic vehicle.

Emergency Line

The new generation of the Porsche 911 sports car will include a hybrid model, according to Auto Express — and it could be the highest-performance version of the iconic vehicle.

“When I am thinking about a hybrid version of the 911 I do not mean like the Panamera or Cayenne,” said Porsche product line developer August Achleitner told the magazine, comparing the upcoming model to the prototype Porsche 919 Hybrid, which the company has used to dominate in the storied Le Mans circuit race.

All That Power

Hybrid automobiles typically use a gas engine to charge up batteries that power an electric drive system. There are numerous advantages, including that hybrid vehicles can recapture energy used to decelerate.

Analyzing Achleitner’s remarks, Jalopnik pointed out that they could mean that in a few years, the top-performing Porsche 911 could be a hybrid model. If the car is a hit, it could be a watershed moment for high-end hybrid vehicles.

Porsche Unleashed

That’s a big deal, according to Auto Express, because the 911 is such a flagship that any change is subject to enormous internal deliberations.

Gearheads will need to wait a few years to get their hands on the hybrid 911, though. Auto Express reports that even though the car will start rolling out in 2020, the hybrid version isn’t expected until at least 2022.

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A New Amazon Camera Patent Is Straight Out of “1984”

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A new patent application by commerce giant Amazon describes a smart doorbell that monitor neighborhoods and report suspicious activity to the authorities

Neighborhood Watch

A new patent application by commerce giant Amazon describes a smart doorbell that would use a camera to monitor users’ neighborhoods using facial recognition technology and report suspicious activity to the authorities. Needless to say, it immediately made privacy advocates uncomfortable.

“The patent is a roadmap for Amazon’s disturbing vision of surveillance in the future,” American Civil Liberties Union attorney Jacob Snow told CNN Business. “People have the right to go about their daily lives without being watched and tracked. And there’s no assurance the resolution of the doorbell camera is very good.”

Patent Pending

The patent for the doorbell lists as its inventor James Siminoff, the CEO of home security startup Ring, which Amazon acquired in February 2018.

There’s no guarantee that a patent will become an actual product — remember those goofy VR rollerskates Google filed an application for in November? — but CNN speculated that Amazon’s interest in the doorbell is connected to its social network called Neighbors, which is built on Ring technology and is meant to share information about thieves who steal packages.

The implication: that Amazon’s system could become a distributed digital narc that collected information even about neighbors who chose not to use its smart products — like a private-sector version of the ubiquitous cameras in George Orwell’s “1984.”

Good Kid, Smart City

Amazon and Ring’s peers seem circumspect about the patent. Matt Pruit, the chief solutions architect at NEC, which also develops facial recognition tech, told CNN that the impact of the technology depends on how it’s rolled out.

“Smart city or surveillance state are two sides of the same coin,” he told CNN. “Technology in itself is neither good or bad. It’s how it’s used in the end.”

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An Australian Ban Kept Billions of Plastic Bags From Polluting

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When two Australian chains banned plastic bags three months ago, it led to an 80 percent reduction in the country's overall consumption of plastic bags.

Polystyrene Man

There’s mounting pressure on the world to grapple with its plastic addiction. Landfills and oceans alike are choking on waste plastic, which is made from crude oil and can take centuries to decompose.

New evidence, though, suggests that small changes in plastic policy can make large changes in aggregate. When Australia’s two largest supermarket chains banned plastic bags three months ago, the Guardian reports, it led to an 80 percent reduction in the country’s overall consumption of plastic bags.

The Plastics

There was a public outcry in Australia when retailers Coles and Woolworths pledged to ban plastic bags this past summer. Initially, things were tough: Woolworth’s blamed the move for falling sales, and Coles briefly reversed the rule before settling on a small fee for plastic bags.

But just a few months later, according to Australia’s National Retail Association, the bag prohibition has made a significant environmental difference. The group estimates that it’s kept some 1.5 billion bags out of the environment.

Out of the Bag

In October, the European Union voted to completely ban single-use plastics by 2021 — though its member states still need to approve the law. In the meantime, Coles’ and Woolworths’ move shows that small changes by retailers can also help close the plastic gap.

“Everyone delivering things in a package need to take responsibility for what they deliver it in,” National Retail Association spokesperson David Stout told the Guardian. “I think there’s going to be a lot more pressure on all of us to be more aware of what we consume.”

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The Scientist Who Gene-Edited Babies Is Missing

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He Jiankui, the researcher behind the controversial gene-editing of a pair of twin babies in China, is currently nowhere to be found.

Disappearing Act

Just five days ago, it seemed like every pair of eyes in the world was fixed on He Jiankui, the researcher behind the controversial gene-editing of a pair of twin babies in China.

On Wednesday, He took the stage at the Human Genome Editing Summit at the University of Hong Kong to present his research, the broad strokes of which had leaked to the press a few days prior. Significant backlash from the scientific community followed, and the Chinese government itself soon banned He from continuing his research.

Now, no one seems to know where He is.

Tight-Lipped

Over the weekend, rumors circulated that the president of the Southern University of Science and Technology (SUSTC), He’s former employer, forced the scientist to return to Shenzhen, China, where the university was now detaining him.

On Monday, the South China Morning Post (SCMP) published a statement from SUSTC that fell short of wholly refuting the rumor.

“Right now nobody’s information is accurate, only the official channels are,” a spokesperson told SCMP. “We cannot answer any questions regarding the matter right now, but if we have any information, we will update it through our official channels.”

CRISPR Consequences

He will probably turn up eventually, at which point he’ll likely need to submit to an investigation from China’s Ministry of Science and Technology.

The results of that investigation could shape the future of human gene editing — if China punishes He severely for his actions, it could deter other scientists from pursuing the “ask forgiveness, not permission” route with their own research. Leniency could have the opposite effect.

Regardless of how that investigation plays out, though, He has pushed humanity across a line that it can never uncross. We now live in a world in which the first people with CRISPR-modified genes have been born. Will they be the first and last? Or simply the first?

READ MORE: University Denies ‘Chinese Frankenstein’ He Jiankui Detained Over Gene-Edited Babies Claim [SCMP]

More on He Jiankui: Researcher Who Gene-Edited Babies Answers Critics: “I Feel Proud”

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How Google Challenged Coders to Make AI More Culturally Aware

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Ethical AI

By now, it should surprise no one to hear that artificial intelligence has a bias problem. People program their societal prejudices into algorithms all the time, often without meaning to. For instance, most image-recognition algorithms correctly identify women in flowing white dresses as “brides” but fail to do so for Indian women wearing wedding saris.

To solve that problem, Google created an open challenge called the Inclusive Images Competition. The goal of the contest, the MIT Technology Review reports, is to develop data sets and algorithms that result in AI that recognizes more diverse people and customs.

Deep Unlearning

Three months ago, competing teams set out to train image-detection algorithms to be more culturally inclusive, both by using more thoughtful labels on the photos used during training and by improving the algorithms themselves.

These new algorithms were then put through a stress test of photos sent from volunteers around the world. Those that accurately labeled the new photos — for instance, identifying a woman in the process of getting married as a “bride” instead of the vague, less-helpful default label of “person” earned more points according to Google’s metrics.

Necessary Progress

The top five teams on the running leaderboard, led by Samsung AI deep learning engineer Pavel Ostyakov, will each receive a $5,000 prize — admittedly a small reward for helping solve a major problem within AI research.

Over the next few days, the winning teams will present their work at the Thirty-second Conference on Neural Information Processing Systems, a major international AI conference.

None of those five teams built a perfectly-accurate or unbiased algorithm; only one of the top five teams, for instance, built an algorithm that could correctly identify an Indian bride. But the contest marks an important step in the right direction toward building inclusive AI that can serve all types of people.

READ MORE: AI has a culturally biased world view that Google has a plan to change [MIT Technology Review]

More on algorithmic bias: Microsoft Announces Tool To Catch Biased AI Because We Keep Making Biased AI

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This Self-Driving Car Uses a Fold-Out Robot Arm to Deliver Parcels

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A self-driving vehicle named Lotte is taking autonomous delivery to the next level, eliminating the need for a human to immediately retrieve their package.

The Last Mile

This self-driving car can now do more than just transport packages to customers’ homes — it can actually deliver the goods.

On Friday, Cleveron — the tech firm behind Walmart’s online pickup towers — unveiled a self-driving robotic courier named Lotte at an Estonian robotics conference.

Based on a video of Lotte in action, the delivery vehicle can not only drive itself to a secure locker, but even place a package inside with a fold-out robotic arm — eliminating the need for any human intervention.

Testing Grounds

Cleveron plans to begin testing Lotte on Estonian streets in 2020. Once the system is in action, CEO Arno Kutt thinks it’ll prove to be a win-win for both retailers and customers.

“[T]he robot courier will replace human labor, which makes the last mile delivery cheaper,” he told Business Insider. “This in turn helps e-commerce grow even more — it will be less expensive (we eliminate labor costs) and extremely convenient (the parcels are waiting for you safely in your own parcel locker).”

Next-Level Delivery

This is far from the first autonomous delivery vehicle we’ve seen, but it is one of the first to completely remove humans from the process — typically, the customer would need to actually retrieve their order from the vehicle.

Of course, it’ll be a while before every customer of Walmart and the like has access to a secure parcel locker, but this video is an intriguing vision of the future of retail — and one that might have a decent chance of actually coming true.

READ MORE: This Futuristic Car Could Solve a Multibillion-Dollar Problem Facing Amazon, Walmart, and Target [Business Insider]

More on autonomous delivery: Ford and Walmart Want Self-Driving Cars to Deliver Your Groceries

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This AI Avatar Compliments While You Shop So You’ll Buy More Stuff

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Millie, an AI avatar built by Canadian startup TwentyBN, is trained to compliment people trying on new clothes so they're more likely to buy them.

Sale Bot

Millie really wants you to buy that new outfit — Millie thinks it makes you look so good!

Unfortunately, Millie isn’t a new friend or significant other. Instead, it’s an AI avatar built specifically to flatter you and push you to spend more at retail stores when you walk near its kiosks. That’s according to the MIT Technology Review‘s Will Knight, who recently tested out the system.

Attention Shoppers

Millie’s software uses computer vision to tell when a customer approaches, as well as when someone accepts Millie’s encouragement to try on new clothes or pick up a nearby product — all tactics that TwentyBN, the company that created Millie, says are intended to increase sales. When Knight tried a pair of sunglasses, for instance, Millie asked if he was a model.

But Millie’s AI is far behind the abilities of an actual sales associate. Training a digital avatar to detect and respond to people is no small feat, to be sure, but it bears mentioning that we do not yet know how to build artificial intelligence that truly mirrors that of a human.

Prototype

Knight found Millie’s interface to be clunky, which isn’t surprising: contextually understanding and crafting specific compliments based on one’s appearance is too sophisticated for current AI chatbots.

“The experience isn’t quite polished enough yet, and Millie’s communication skills are a bit crude and basic,” Knight wrote.

Still, if your wallet can take the hit, a little flattery never hurt anybody.

READ MORE: I tested an AI sales assistant that’s trained to push you into spending more [MIT Technology Review]

More on retail technology: Amazon is Testing its Cashierless Tech in big box Stores

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This AI Avatar Compliments While You Shop So You’ll Buy More Stuff

Walmart Is About to Deploy Hundreds of Robot Janitors

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By the end of January 2019, Walmart plans to deploy 360

Custodial Agreement

Robot janitors could be coming to a Walmart near you.

On Monday, a robotics company called Brain Corp — seriously — announced it had entered a partnership with the big box chain. By the end of January 2019, the tech company will equip 360 of the retailer’s floor scrubbing machines with a platform called BrainOS. If all goes according to plan, the machines will keep the store’s floors spotless — without the supervision of a human employee.

Helping Hand

Typically, Walmart workers must manually operate the company’s floor scrubbers, guiding them down the various aisles every time a store needs cleaned.

But according to a Brain Corp press release, a Walmart employee will simply need to ride each BrainOS-equipped floor scrubber around the store once to map the building’s layout. After that, the scrubber will be able to navigate the store autonomously, using a system of sensors to keep an eye out for people and obstacles.

The goal, according to Walmart, is to free employees of the tedious task of cleaning floors so they can focus on other parts of their jobs, such as helping customers.

Cleaning House

If that is the case — and these robot janitors don’t actually cost any workers their jobs — they could improve the Walmart experience for both customers and employees.

But there’s also a chance that the collaboration could be a stepping stone along the path to robots that can do all the tasks of a Walmart worker. And given that Walmart employs more Americans than any other company, it’s hard to overstate the impact that could potentially have on the economy.

READ MORE: Robot Janitors Are Coming to Mop Floors at a Walmart Near You [Bloomberg]

More on Walmart: Walmart Wants to Use AI to Track Everything Happening in Its Stores

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Watch the ISS’s New AI Robot Companion Act Like Kind of a Brat

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In a video clip, Cimon, an AI bot designed to test robot-astronaut interactions, refuses to respond to commands and acts defensive — just like a teenager.

Parents Are the Worst

It turns out that spacefaring AIs might be even more temperamental than teens.

On Friday, the European Space Agency released a video of astronaut Alexander Gerst’s first interaction with an AI robot named Cimon, which stands for Crew Interactive Mobile CompanioN, aboard the International Space Station (ISS).

According to the video’s description, the basketball-sized ISS robot is “designed to test human-machine interaction in space.” And if the clip is any indication, that interaction is a lot like a parent trying to connect with their surly teen.

Universal Language

When Gerst asks Cimon to tell him something about space, it rattles off a fact about Mercury with all the enthusiasm of a teen answering the question “What did you learn in school today?” Later, the bot takes its sweet time responding to Gerst’s request for help with one task (completing a 90-degree turn), then questions the astronaut’s decision to wrap up another (a crystallization procedure). Like, okay, dad.

Like countless generations before them, the pair does finally strike up a connection through music — after Gerst asks Cimon to play his favorite song, the bot replies, “Yay, I like your favorite hits, too.” Gerst even busts out a few dance moves, with all the swagger of a dad at the dinner table.

Pout About It

But the Hallmark moment is short-lived — Cimon refuses to leave music mode when Gerst tries to get back to business with another task (recording video via its front camera).

The AI responds by repeatedly sinking toward the floor, and based on its next few utterances — “Be nice, please,” “Don’t you like it here with me?,” “Don’t be so mean, please” — if Cimon had a bedroom door, the ISS robot probably would have slammed it at this point.

And just like a parent dealing with a hormonal teen, all Gerst can do is shrug off the mini meltdown: “He’s a bit sensitive today.”

Let’s hope this is just a phase.

READ MORE: In Video Debut, CIMON the ISS Robot Throws an Unexpected Tantrum [Gizmodo]

More on the ISS: Antibiotic-Resistant Bacteria Found on International Space Station

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Germ Warfare | Dexter’s Laboratory Wiki | FANDOM powered …

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Germ Warfare is the third part of episode 10 of season 2. In this episode, Dexter's family comes down with the flu, and the boy genius tries his best to avoid becoming ill. However, this becomes a problem when Dee Dee enters his laboratory looking for a tissue.

Dexter has just put the finishing touches on his "greatest creation", which is a sphere that he claims will give him the power to rule the universe. Then, his Mom calls him down for breakfast. However, Mom is revealed to have the flu and sneezes all over his food. After Dexter runs out of the kichen in disgust, he runs into his Dad who is also sick with the flu. When Dexter has ran up the stairs to avoid getting sneezed on by Dad, he runs into Dee Dee, who has the worst case of the flu. Dexter rushes to his lab for refuge from his sick family. Suddenly, Dee Dee comes into his laboratory looking for her "hanky", which is actually a tissue that she accidentally left in the lab, which leads Dexter to put himself in a bubble to avoid catching the flu. However, his plan soon goes awry when Dee Dee sneezes onto Dexter's latest invention seen at the beginning of the episode, which causes Dexter's bubble to explode. The episode ends with Dee Dee finding her tissue, but Dexter, on the other hand, catches the flu that he was trying to avoid. A sick Dexter gives the viewer a sad look of defeat and the episode ends.

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U.S. Germ Warfare Research Pushes Treaty Limits – The New …

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Two other projects completed during the Clinton administration focused on the mechanics of making germ weapons.

In a program code-named Clear Vision, the Central Intelligence Agency built and tested a model of a Soviet-designed germ bomb that agency officials feared was being sold on the international market. The C.I.A. device lacked a fuse and other parts that would make it a working bomb, intelligence officials said.

At about the same time, Pentagon experts assembled a germ factory in the Nevada desert from commercially available materials. Pentagon officials said the project demonstrated the ease with which a terrorist or rogue nation could build a plant that could produce pounds of the deadly germs.

Both the mock bomb and the factory were tested with simulants -- benign substances with characteristics similar to the germs used in weapons, officials said.

A senior Bush administration official said all the projects were ''fully consistent'' with the treaty banning biological weapons and were needed to protect Americans against a growing danger. ''This administration will pursue defenses against the full spectrum of biological threats,'' the official said.

The treaty, another administration official said, allows the United States to conduct research on both microbes and germ munitions for ''protective or defensive purposes.''

Some Clinton administration officials worried, however, that the project violated the pact. And others expressed concern that the experiments, if disclosed, might be misunderstood as a clandestine effort to resume work on a class of weapons that President Nixon had relinquished in 1969.

Simultaneous experiments involving a model of a germ bomb, a factory to make biological agents and the developoment of more potent anthrax, these officials said, would draw vociferous protests from Washington if conducted by a country the United States viewed as suspect.

Administration officials said the need to keep such projects secret was a significant reason behind President Bush's recent rejection of a draft agreement to strengthen the germ-weapons treaty, which has been signed by 143 nations.

The draft would require those countries to disclose where they are conducting defensive research involving gene-splicing or germs likely to be used in weapons. The sites would then be subject to international inspections.

Many national security officials in both the Clinton and Bush administrations opposed the draft, arguing that it would give potential adversaries a road map to what the United States considers its most serious vulnerabilities.

Among the facilities likely to be open to inspection under the draft agreement would be the West Jefferson, Ohio, laboratory of the Battelle Memorial Institute, a military contractor that has been selected to create the genetically altered anthrax.

Several officials who served in senior posts in the Clinton administration acknowledged that the secretive efforts were so poorly coordinated that even the White House was unaware of their full scope.

The Pentagon's project to build a germ factory was not reported to the White House, they said. President Clinton, who developed an intense interest in germ weapons, was never briefed on the programs under way or contemplated, the officials said.

A former senior official in the Clinton White House conceded that in retrospect, someone should have been responsible for reviewing the projects to ensure that they were not only effective in defending the United States, but consistent with the nation's arms-control pledges.

The C.I.A.'s tests on the bomb model touched off a dispute among government experts after the tests were concluded in 2000, with some officials arguing that they violated the germ treaty's prohibition against developing weapons.

Intelligence officials said lawyers at the agency and the White House concluded that the work was defensive, and therefore allowed. But even officials who supported the effort acknowledged that it brought the United States closer to what was forbidden.

''It was pressing how far you go before you do something illegal or immoral,'' recalled one senior official who was briefed on the program.

Public disclosure of the research is likely to complicate the position of the United States, which has long been in the forefront of efforts to enforce the ban on germ weapons.

The Bush administration's willingness to abandon the 1972 Antiballistic Missile treaty has already drawn criticism around the world. And the administration's stance on the draft agreement for the germ treaty has put Washington at odds with many of its allies, including Japan and Britain.

The Original Treaty

During the cold war, both the United States and the Soviet Union produced vast quantities of germ weapons, enough to kill everyone on earth.

Eager to halt the spread of what many called the poor man's atom bomb, the United States unilaterally gave up germ arms and helped lead the global campaign to abolish them. By 1975, most of the world's nations had signed the convention.

In doing so, they agreed not to develop, produce, acquire or stockpile quantities or types of germs that had no ''prophylactic, protective or other peaceful purposes.'' They also pledged not to develop or obtain weapons or other equipment ''designed to use such agents or toxins for hostile purposes or in armed conflict.''

There were at least two significant loopholes: The pact did not define ''defensive'' research or say what studies might be prohibited, if any. And it provided no means of catching cheaters.

In the following decades, several countries did cheat, some on a huge scale. The Soviet Union built entire cities devoted to developing germ weapons, employing tens of thousands of people and turning anthrax, smallpox and bubonic plague into weapons of war. In the late 1980's, Iraq began a crash program to produce its own germ arsenal.

Both countries insisted that their programs were for defensive purposes.

American intelligence officials had suspected that Baghdad and Moscow were clandestinely producing germ weapons. But the full picture of their efforts did not become clear until the 1990's, after several Iraqi and Soviet officials defected.

Fears about the spread of biological weapons were deepened by the rise of terrorism against Americans, the great strides in genetic engineering and the collapse of the Soviet Union, which left thousands of scientists skilled in biological warfare unemployed, penniless and vulnerable to recruitment.

The threat disclosed a quandary: While the United States spent billions of dollars a year to assess enemy military forces and to defend against bullets, tanks, bombs and jet fighters, it knew relatively little about the working of exotic arms it had relinquished long ago.

Designing a Delivery System

In the mid-1990's, the C.I.A. and other intelligence agencies stepped up their search for information about other nations' biological research programs, focusing on the former Soviet Union, Iran, Iraq and Libya, among others. Much of the initial emphasis was on the germs that enemies might use in an attack, officials said.

But in 1997, the agency embarked on Clear Vision, which focused on weapons systems that would deliver the germs.

Intelligence officials said the project was led by Gene Johnson, a senior C.I.A. scientist who had long worked with some of the world's deadliest viruses. Dr. Johnson was eager to understand the damage that Soviet miniature bombs -- bomblets, in military parlance -- might inflict.

The agency asked its spies to find or buy a Soviet bomblet, which releases germs in a fine mist. That search proved unsuccessful, and the agency approved a proposal to build a replica and study how well it could disperse its lethal cargo.

The agency's lawyers concluded that such a project was permitted by the treaty because the intent was defensive. Intelligence officials said the C.I.A. had reports that at least one nation was trying to buy the Soviet-made bomblets.

A model was constructed and the agency conducted two sets of tests at Battelle, the military contractor. The experiments measured dissemination characteristics and how the model performed under different atmospheric conditions, intelligence officials said. They emphasized that the device was a ''portion'' of a bomb that could not have been used as a weapon.

The experiments caused concern at the White House, which learned about the project after it was under way. Some aides to President Clinton worried that the benefits did not justify the risks. But a White House lawyer led a joint assessment by several departments that concluded that the program did not violate the treaty, and it went ahead.

The questions were debated anew after the project was completed, this time without consensus. A State Department official argued for a strict reading of the treaty: the ban on acquiring or developing ''weapons'' barred states from building even a partial model of a germ bomb, no matter what the rationale.

''A bomb is a bomb is a bomb,'' another official said at the time.

The C.I.A. continued to insist that it had the legal authority to conduct such tests and, intelligence officials said, the agency was prepared to reopen the fight over how to interpret the treaty. But even so, the agency ended the Clear Vision project in the last year of the Clinton administration, intelligence officials said.

Bill Harlow, the C.I.A. spokesman, acknowledged that the agency had conducted ''laboratory or experimental'' work to assess the intelligence it had gathered about biological warfare.

''Everything we have done in this respect was entirely appropriate, necessary, consistent with U.S. treaty obligations and was briefed to the National Security Council staff and appropriate Congressional oversight committees,'' Mr. Harlow said.

Breeding More Potent Anthrax

In the 1990's, government officials also grew increasingly worried about the possibility that scientists could use the widely available techniques of gene-splicing to create even more deadly weapons.

Those concerns deepened in 1995, when Russian scientists disclosed at a scientific conference in Britain that they had implanted genes from Bacillus cereus, an organism that causes food poisoning, into the anthrax microbe.

The scientists said later that the experiments were peaceful; the two microbes can be found side-by-side in nature and, the Russians said, they wanted to see what happened if they cross-bred.

A published account of the experiment, which appeared in a scientific journal in late 1997, alarmed the Pentagon, which had just decided to require that American soldiers be vaccinated against anthrax. According to the article, the new strain was resistant to Russia's anthrax vaccine, at least in hamsters.

American officials tried to obtain a sample from Russia through a scientific exchange program to see whether the Russians had really created such a hybrid. The Americans also wanted to test whether the microbe could defeat the American vaccine, which is different from that used by Russia.

Despite repeated promises, the bacteria were never provided.

Eventually the C.I.A. drew up plans to replicate the strain, but intelligence officials said the agency hesitated because there was no specific report that an adversary was attempting to turn the superbug into a weapon.

This year, officials said, the project was taken over by the Pentagon's intelligence arm, the Defense Intelligence Agency. Pentagon lawyers reviewed the proposal and said it complied with the treaty. Officials said the research would be part of Project Jefferson, yet another government effort to track the dangers posed by germ weapons.

A spokesman for Defense Intelligence, Lt. Cmdr. James Brooks, declined comment. Asked about the precautions at Battelle, which is to create the enhanced anthrax, Commander Brooks said security was ''entirely suitable for all work already conducted and planned for Project Jefferson.''

The Question of Secrecy

While several officials in both the Clinton and Bush administrations called this and other research long overdue, they expressed concern about the lack of a central system for vetting such proposals.

And a former American diplomat questioned the wisdom of keeping them secret.

James F. Leonard, head of the delegation that negotiated the germ treaty, said research on microbes or munitions could be justified, depending on the specifics.

But he said such experiments should be done openly, exposed to the scrutiny of scientists and the public. Public disclosure, he said, is important evidence that the United States is proceeding with a ''clean heart.''

''It's very important to be open,'' he said. ''If we're not open, who's going to be open?''

Mr. Leonard said the fine distinctions drawn by government lawyers were frequently ignored when a secret program was exposed. Then, he said, others offer the harshest possible interpretations -- a ''vulgarization of what has been done.''

But he concluded that the secret germ research, as described to him, was ''foolish, but not illegal.''

The authors have reported on biological weapons for The New York Times and based this article on material gathered for their book, ''Germs: Biological Weapons and America's Secret War,'' which is being published this month by Simon & Schuster Inc.

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NATO hunts Russian submarines in the Arctic – CNN

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"They're letting us know that they're out there," Adm. James G. Foggo III, commander of US Naval Forces in Europe, said of Russia's increased submarine presence in the North Atlantic and Arctic oceans.

"They're operating in much greater numbers and in places they have not operated before."

It will be NATO's largest exercise in decades, involving 50,000 troops, 10,000 vehicles, 250 aircraft and 65 vessels, including a US aircraft carrier operating north of the Arctic Circle for the first time in almost 30 years.

Tensions between Russia and the West are at highs not seen since the Cold War, amid the poisoning of former Russian intelligence agent Sergei Skripal in England, allegations of Russian interference in the 2016 US election and Western sanctions on Moscow following its annexation of Crimea.

But Foggo, who is overseeing Trident Juncture, said the exercise isn't a threat to Russia, noting that NATO and Russian troops will be more than 700 kilometers (435 miles) apart during the maneuvers. NATO, he added, had invited Russian and Belarusian observers to monitor the exercise.

"I want them to be there because that conveys the strength of the alliance," Foggo said.

As the exercise plays out, it will involve air, ground and maritime operations, including anti-submarine warfare.

Russia not yet NATO's equal

Foggo said he believes Russia has over 40 combat submarines, more than 20 concentrated in its Northern Fleet, capable of operating in the North Atlantic and the Arctic.

To keep track of the Russian subs, NATO planes are making a flight about every other day out of a revived US base at Keflavik International Airport.

Iceland's foreign minister, Thr Thrdarson, said in a speech in Stockholm in January that alliance aircraft are operating out of the country with increased frequency, taking off from Keflavik for a total of 153 days in 2017, a steady year-on-year increase from just 21 days in 2014.

Established in 1951, the US Naval Air Station in Iceland was deactivated in 2006, as NATO shifted its focus in Europe south to the Mediterranean. However, the threat posed by a resurgent Russia and its submarine fleet has worried US military commanders and brought the Americans back to this island nation, which sits between Greenland and the United Kingdom.

To get from bases in the Russian Arctic to the open Atlantic, Moscow's submarines need to pass Iceland.

Foggo says those subs are a big headache for NATO's leaders.

"The Russians have continued to invest in research and development and production of very capable submarines. They have been our most capable adversary," said the US admiral, who spoke with CNN in an exclusive interview.

Russia says its sub fleet is defensive and necessary to safeguard the country's security.

At this year's "Submariner Day" in March, Vice Adm. Oleg Burtsev, the former head of Russian naval forces, talked about the importance of beefing up the country's fleet of subs.

"This is because the plans of the leadership of our country and our army are to ensure that we are capable of worthily countering any probable enemy from all directions," Burtsev said, according to Russia's Tass news agency.

And another former top naval commander said Russia has some work to do to match the submarine fleet the NATO allies can muster.

"I believe that the qualitative level of our fleet is quite high now, but its quantity is not yet enough," Adm. Vladimir Komoyedov, the former head of Russia's Black Sea Fleet, told Tass.

Much of NATO's trouble with the Russian sub fleet is of its own making, said Carl Schuster, a former US Navy captain and current Hawaii Pacific University professor.

"Much of (the Russian sub fleet's) current threat is based on the expansion of its operations and operating areas at a time when NATO countries have reduced their fleets and fleet operations," Schuster said, calling it "a serious threat only because NATO ignored it until recently to focus on other security concerns."

A new generation of threat

Foggo says Russia's new generation of submarines is highly capable and dangerous. Among the newest is the Borei class: virtually silent, nuclear-powered vessels capable of launching ballistic missiles. The Borei class is a main pillar of Russia's underwater nuclear deterrent force, similar to the US Ohio class ballistic missile submarines.

"This is beyond any doubt the future of our group of naval strategic nuclear forces," the head of Russia's naval forces, Adm. Vladimir Korolev, said recently at the christening of another new Borei class submarine.

But Russia is also in the process of modernizing many of its older submarines, like the diesel-electric Kilo class boats. These can now stay under water longer and are capable of carrying four cruise missiles, which they successfully fired at ISIS targets in Syria, the Russian military says.

"They carry the Kalibr cruise missile, a very capable weapon system. And from any of the places the Russians operate from, they can target any capital in Europe," Foggo said.

"Would they do it? I don't think so, but nevertheless, we need to be cognizant of where they are at all times," he said.

Schuster said that worry gives Russia an advantage.

"Moscow 's aggressive actions and intent will determine the time and place of a crisis while Western nations must be present and ready to respond at all times," he said.

And that's why NATO is methodically ramping up operations in Iceland.

Chess in the ocean

The US is spending $34 million to upgrade facilities at Keflavik, which will enable the Navy to deploy its P-8 Poseidon surveillance and anti-submarine aircraft more frequently.

But even with the twin-engine jets running regular surveillance in the North Atlantic, finding Russian submarines is not an easy task.

"The ocean is big .... It's a chess match between the sub commander and all the assets that are trying to find him," Lt. Cmdr. Rick Dorsey, the tactical coordinator for one of the US P-8 units operating out of Iceland, told CNN. "It's a combination of a lot of work, from a lot of different units."

"We work with ships, we work with other aircraft, we work with other nations to help get the picture," Dorsey said.

It's the sort of team work among allies that Adm. Foggo wants to encourage, applauding the UK and Norway for acquiring their own P-8 aircraft and calling on NATO members to invest in research and development to keep a competitive edge over Russia. "We must continue challenging them wherever they are and knowing where they are," he said.

"We can no longer take for granted that we can sail with impunity in all of the oceans."

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NATO hunts Russian submarines in the Arctic - CNN

Caribbean Hotels – Hotel Database of the Caribbean Islands

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Caribbean Hotels - Hotel Database of the Caribbean IslandsAnguilla (45) updatedAnguilla hotels and resorts.Antigua and Barbuda (55) updatedHotels and resorts in Antigua and Barbuda.Aruba (52) updatedHigh Rise, Low Rise and beachfront hotels on the Dutch island of Aruba.Bahamas (153) new updatedThe Bahamas is home to 700 islands all with a different charm. Accommodations range from Luxury hotels and casinos in New Providence and Grand Bahama to quaint seaside resorts in the Out Islands of Abaco, Bimini, Exuma, Eleuthera and Harbour Island.Barbados (108) updatedExquisite Barbados hotels.Belize (306) updatedBelize Hotels & ResortsBermuda (28) updatedLuxury resorts and cottage communities in Bermuda.Bonaire (41) updatedHotels and guest houses in Bonaire.British Virgin Islands (79) updatedVilla rentals in Tortola, Virgin Gorda, Anegada in the British Virgin Islands.Cayman Islands (69) updatedA selection of hotels and guest houses on Grand Cayman, Cayman Brac and Little Cayman.Cuba (16) updatedCuba Hotels & ResortsCuracao (49) updatedHotels and resorts on the Dutch island of Curacao.Dominica (41) updatedDominica Hotels & ResortsDominican Republic (100) updatedHotels, resorts, all inclusive properties in the Dominican Republic.Grenada (41) updatedHotels and guest cottages in Grenada.Guadeloupe (61) updatedGuadeloupe Hotels & ResortsGuyana (8) updatedGuyana Hotels & ResortsHaiti (17) updatedHaiti Hotels & ResortsJamaica (206) updatedLuxury villas and vacation homes in popular Jamaican resort areas of Montego Bay, Ocho Rios, Negril.Martinique (26) updatedHotels and inns in Martinique.Mexico (116) updatedHotels and resorts in Mexico.Montserrat (6) updatedMontserrat Hotels & ResortsPuerto Rico (91) updatedHotels, resorts and casinos in Puerto Rico.Saba (9) updatedSaba Hotels & ResortsSt Barts (22) updatedLuxury hotels on the French Caribbean island of St. Barths.St Eustatius (2)Hotels in St EustatiusSt Kitts and Nevis (22) updatedSmall hotels and inns in St Kitts & Nevis.St Lucia (84) updatedVillas and vacation homes in St. Lucia.St Maarten (26) updatedHotels, resorts and casinos on the Dutch island of St Maarten.St Martin (24) updatedHotels and guest houses in St Martin, French West Indies.St Vincent and The Grenadines (31) updatedSt Vincent & The Grenadines hotelsSuriname (13) updatedSuriname hotelsTrinidad and Tobago (73) updatedTrinidad and Tobago hotels & ResortsTurks and Caicos (45) updatedAccommodations in the Turks and Caicos islands including Parrot Cay.US Virgin Islands (73) updatedVillas and vacation homes in St. Thomas, St. John, St. Croix in the US Virgin Islands.There are 2138 hotels for you to choose from! Check back often as we are constantly updating our site with new hotels.

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Caribbean Hotels - Hotel Database of the Caribbean Islands

What is Litecoin? | A Beginner’s Guide

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What is Litecoin?

Litecoin (LTC) is a decentralized peer-to-peer cryptocurrency that was released on October 7th, 2011 and went live on October 13th, 2011.

The silver to Bitcoins gold.

Bitcoins little brother that doesnt get out much.

These are just a few of the things you might hear being tossed around when talking about Litecoin. At first glance, Litecoin doesnt garner much respect as a top 10 market cap cryptocurrency.

However, once you get into the weeds, Litecoin presents an extremely useful and interesting application of the original Bitcoin blockchain.

For all the flak Litecoin gets, its easy to overlook what it actually is, and what functions it serves.

Litecoin was founded by former Google employee Charlie Lee. It was one of the first forks of the Bitcoin core client. It was proposed as a solution to some of the bottlenecks and scalability issues with Bitcoin, most notably the number of transactions that could be processed within a given time.

https://files.coinmarketcap.com/static/widget/currency.js

The edge Litecoin has over Bitcoin is that the payment transaction costs are extremely low, and it is capable of facilitating payments around 4x as fast.

Litecoin originally started gathering attention during its explosive growth in November 2013, where it saw a near 15x spike in price. This jump in price, however, was short-lived and Litecoin hovered around the $4 per LTC range for about two years. It wasnt until May 2017 that it started to pick up steam again during a time where generally all cryptocurrencies experienced massive growth.

Litecoin has also been relatively innovative, adopting new technologies such as Segregated Witness and carrying out the first Lightning Network transaction that sent 0.00000001 LTC from Zurich, Switzerland to San Francisco, USA in under a single second.

Theres a reason Litecoin receives a lot of comparisons to Bitcoin. Except for a handful of minor distinctions, Litecoin serves the exact same purpose as Bitcoin. After all, it was one of the first Bitcoin forks.

Comparing Litecoin to Bitcoin not only makes sense from a convenience point of view, but it also lets us zone in what makes it different at a technological level. Litecoin is meant to be used as peer-to-peer cryptocurrency and is actually able to accomplish the same job Bitcoin does at a faster and cheaper rate.

Transaction confirmation speed plays a huge role in how quickly a currency gets adopted. Bitcoin confirmations usually take around ten minutes and have been steadily increasing with periods hitting as high as 2,548 minutes. Litecoins network is able to confirm transactions at a much quicker rate.

Litecoins verification period lasts a fixed 2.5 minutes. For every individual Bitcoin block that gets confirmed, four Litecoin blocks of equal size get confirmed.

The cost of sending any denomination of Litecoin costs around $0.09, whereas Bitcoin currently hovers around $5.00. This is an immediate advantage Litecoin has over Bitcoin for small transactions, since splitting a $10 Uber with a friend doesnt make sense for most people if you have to pay $5.00 on top of that. Litecoin offers the option to pay for everyday goods without high fees that will start adding up very quickly.

One of Litecoins goals is to distribute hash power more evenly than Bitcoins network. The problem that Litecoins founder Charlie Lee wanted to address was how Bitcoins hash power was largely distributed among mining pools, groups of miners, and generally a much smaller (and less decentralized) subset of miners. Litecoin aims to keep the hashing power decentralized.

Litecoins mining also keeps transaction fees relatively low due to the inherently higher total supply. There can only be 21 million Bitcoins existence, whereas there can be up to 84 million Litecoins. This matters because it makes mining less competitive, and the more competitive mining gets, the higher the transaction fees.

Whereas Bitcoin is near hitting some pretty serious scalability issues due to its high transaction fees, Litecoin is able to churn out block after block and retain its lower transaction costs. Granted, not as many people are using Litecoin as they are Bitcoin and Litecoin could theoretically end up dealing with the same scalability issues if it were to experience proportionate growth and usage, but that simply just isnt the case today.

Litecoin also uses the Scrypt hashing algorithm that utilizes much less processing power than the Bitcoin SHA256 hashing algorithm. Placing a higher emphasis on utilizing high-speed RAM, Litecoin makes it much less possible for a single player (or small collective group of big players) to dominate the mining world.

Fundamental Non-Technical Differences

Its important to also look at the differences in how both Bitcoin and Litecoin came about.

Bitcoins founders origins are relatively shrouded in mystery. Satoshi Nakamoto, the pseudonym of Bitcoins founder, is essentially relegated to legend and myth.

Litecoins founder, on the other hand, has been publicly available and active in the community. You can find Charlie Lee on Linkedin or on Twitter, as @SatoshiLite. After working at Google and founding Litecoin, he also worked on the engineering side at Coinbase, one of the largest cryptocurrency exchanges in the world.

Personally, I much rather prefer Lees accessible and open nature to the mysterious secretive Satoshi, and the fact that Lee is capable of making light (Lite) of the situation is very humanizing.

Additionally, youd be hard pressed to find any serious claims or illusions of grandeur within the Litecoin camp. Its meant to make cryptocurrency accessible and usable for everyone and is perfectly fine with taking a back-seat role to Bitcoin.

Well, the fact that Litecoin can hold its own weight when it comes to having a legitimate use case says a lot, especially in a cryptocurrency world with over 700+ alt-coins with dubious purposes.

It does, after all, hold a market cap of upwards of $3 billion. That doesnt just happen by dumb luck.

When compared to Bitcoin, which has a market cap about 33x bigger, Litecoin does pose several advantages. As listed above, its capable of offering users lower transaction fees, faster transaction processing times, a more decentralized mining network, and its founder even throws out the occasional zinger on Twitter. These advantages technically make Litecoin a better coin for the vast majority of small transactions.

However, to be fair, Litecoin hasnt been pushed to its limits because there simply arent that many people using it. For the time being, Litecoin does exactly what it was created to do: offer low-cost, speedy transactions in a way that Bitcoin couldnt.

As is, Litecoin is simply another cryptocurrency that just so happened to prove its use case as a low-cost decentralized peer-to-peer payment method.

Litecoin was never made to go head to head with Bitcoin, but its technological advantages do pose somewhat of a threat. While it might be theoretically better than Bitcoin, Bitcoin has already run off with the network effect of rapidly onboarding a much larger and active user base.

Bitcoin also has the benefit of being a near household name by now, whereas Litecoin is much more obscure (especially with hot new tokens on the block like Ethereum). The vast majority of people who jump into the cryptocurrency world will buy Bitcoin first, and if their hunger isnt satiated, maybe some Litecoin and Ethereum.

While Litecoin seems to function very well for what its meant for, its interesting to postulate ideas about situations where it could experience massive user adoption and growth. There isnt much meat on the bones of whatever Litecoin loyalists are chewing on, but its worth noting that it could only be a matter of time before more people start to add Litecoin into their portfolios.

If, and this is a big IF, Bitcoin isnt able to address its scalability issues, Litecoin will be there to at least offer the same utility without having to pay high (and if Bitcoin reaches the climax of its scalability problems extremely high) fees.

Until then, Litecoin will likely hang around the top 10 market-cap cryptocurrencies, doing the same thing it always has.

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What is Litecoin? | A Beginner's Guide

Litecoin Mining Pool (LTC) | Coinfoundry

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Stratum Configuration

All of our stratum servers utilize GeoIP routing which automatically selects the server with the closest geographical proximity to your mining operation, resulting in optimal latency.

Login using your wallet address as username. An optional workername can be appended to your address separated by a dot character. Leave the password blank.

Static difficulty: To mine with a static (fixed) difficulty simply use d=xxx as password in your miner configuration where xxx denotes your preferred difficulty.

Before you can start to mine you need to create a wallet. Although Litecoin is an entirely digital asset, you still need a place to store them. This is done in a digital wallet. There are multiple methods to obtain a wallet which vary by ease of use and the security they provide.

Official first-party Wallets for all major platforms are available from the Litecoin Website. These wallets are released and maintained by the Litecoin Team.

Another possibility is to create a wallet at LiteVault. Please make sure to immediately backup your wallet keys after creating a wallet. We recommend using a password store such as KeePass or 1Password for that.

For long-term storage of Litecoin you can create a paper wallet. A paper wallet is extremely secure if you guard your private key by storing it in a password vault such as KeePass or LastPass or printing it out and depositing the sheet in a real bank vault.

A hardware wallet is a special type of wallet which stores the user's private keys in a secure hardware device. Hardware wallets offer robust safety features for storing cryptographic assets and securing digital payments. Popular hardware wallets are the Ledger Nano S and the Trezor.

There are multiple digital currency exchanges you can register with. Registering with an exchange allows you to create a wallet on the exchange for every currency the exchange supports.

Popular exchanges are: Binance, Bittrex, Poloniex, Kraken, Bitfinex and HitBTC.

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Litecoin Mining Pool (LTC) | Coinfoundry

4th Amendment Supreme Court Cases – Know My Rights

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Stop and FriskTerry v. Ohio [392 U.S. 1, 88 S.Ct. 1968, 20 L.Ed.2d 889 (1968)]

A police officer witnessed three men pacing in front of a jewelry store and suspected that a robbery was being planned. He approached the men and identified himself, then performed frisks of defendants Chilton and Terry and discovered illegal concealed weapons. Defendants were convicted and appealed, claiming that the frisk violated their Fourth Amendment right against unlawful searches and seizures.

The Supreme Court upheld the conviction, finding that when a law enforcement officer has "reasonable grounds" for suspecting that a criminal suspect may be armed, he may pat down the outer layer of the suspect's clothing for weapons. The ruling held that the Fourth Amendment protection against unreasonable searches and seizures is not violated when a pat down is performed based on reasonable suspicion for the purpose of ensuring officer safety.

The Court's ruling in Terry v. Ohio has been understood to validate the practice of frisking (or patting down) suspects for weapons under diverse circumstances. Generally, law enforcement officers will perform frisks at their discretion, regardless of the "reasonable suspicion" standard established by the ruling in Terry. Thus, it is not uncommon for frisks to be conducted for investigatory purposes where no actual evidence of a threat to officer safety exists.

Due to the prevalence of police frisks, it is important for citizens to understand the rationale behind police authority to pat down suspects and the limitations the Court has placed on that authority:

For more on this, check out our podcast on police pat downs and the 'plain feel' doctrine.

Defendant Bostick boarded a bus from Miami to Atlanta. At a stopover in Ft. Lauderdale, the bus was boarded by two uniformed narcotics officers who were performing a routine inspection of the bus. Without reasonable suspicion, the officers approached Bostick in his seat and requested to see his ticket and identification. Finding nothing out of the ordinary, the officers proceeded to request consent to search his luggage. Bostick reportedly consented, at which point the officers performed a search and discovered cocaine. Bostick was subsequently convicted, and appealed claiming that due to his apparent inability to leave the bus, the encounter constituted an unlawful seizure, the evidence obtained must be suppressed. The Supreme Court upheld Bostick's conviction, finding that the practice of contacting citizens on buses in this fashion did not constitute an unlawful seizure under the Fourth Amendment. The Court's ruling rejected Bostick's claim that because the officers were armed and positioned such that he could not leave his seat or the bus, the encounter was a seizure. Since it was never directly communicated to the defendant that he was not free to leave, the Court concluded that the police officers' actions did not violate the Fourth Amendment. So long as nature of the officers' contact with the defendant is held constitutionally valid, his consent to be searched and the evidence that resulted are held valid as well.

Florida v. Bostick is a clear example of law enforcement officers' systematic reliance on the tendency of citizens to overestimate police authority. Moreover, the Supreme Court's ruling in this case indicates a willingness to accommodate manipulative law enforcement practices in order to prevent the Constitution's provisions from interfering with the arrest of drug suspects. So long as the police and the courts cooperate in using the ignorance of suspects as a tool through which to obtain convictions, it is extremely important for all citizens to know their rights.

In the context of investigatory stops and detentions, here are a few important principles that should be remembered:

For more on this, check out our podcast on the 3 levels of police-citizen encounters.

An investigatory stop is a particularly difficult encounter for the citizen because police officers are experienced at controlling the situation. It is important to note, however, that it is actually the citizen who controls all police encounters unless and until there exists such evidence to justify police intrusion into the citizen's privacy or freedom of movement.

Remember that your refusal to be searched cannot be legally interpreted as evidence that you may be involved in a crime. Police cannot detain you merely because you refused consent to a search.

Officer James Rand stopped a car with six occupants and received consent from the driver to search the vehicle. It was determined that the officer did not pressure the driver into consenting. In the back seat he found three checks which had been stolen from a car wash. Defendant Robert Bustamonte challenged his arrest, arguing that while he had consented voluntarily, he had not been informed of his right not to consent to the search.

In Schneckloth v. Bustamonte, the Supreme Court ruled that consent is valid as long as it is voluntarily given. The ruling held that police may not use threats or coercion to obtain consent, but that they need not inform suspects of their right not to consent to a search. In reaching this decision, the Court overturned the more strict "waiver test", which required that suspects be fully informed of their Fourth Amendment right against unreasonable searches and seizures before they can give valid consent.

As demonstrated by the Court in the Schneckloth ruling, the police are under no obligation to inform citizens of their Fourth Amendment rights when requesting to perform a search. This means that it is up to the individual to understand and exercise their right not to be searched. Some states require that police obtain the citizen's signature on a waiver form before conducting the search, however, in most places, police merely need to obtain the citizen's permission verbally. This can be a tricky situation because police will sometimes interpret a broad range of statements or actions as implied consent. Here's what you should remember about police search requests:

Cooperating with someone who is trying to arrest you just might get you arrested!

Police officers forcibly entered Mapp's home in search of a bombing suspect. In the course of the search, officers failed to produce a valid search warrant and denied Mapp contact with her attorney, who was present at the scene. While the suspect was not found, officers did discover illegal pornography in Mapp's home, for which she was charged and convicted. Mapp appealed her conviction claiming that the evidence against her should not be admissible in court because it was illegally obtained.

In Mapp v. Ohio, the Supreme Court ruled that illegally obtained evidence is not admissible in State courts. The Court found that the Fourteenth Amendment right to due process of law and the Fourth Amendment right against unreasonable searches and seizures could not be properly enforced as long as illegally obtained evidence continued to be presented in court. The ruling argued that there was no other effective means of deterring widespread Fourth Amendment violations by police. The ruling acknowledged that sometimes a criminal could go free due to improper police conduct, but argued that the interest in promoting professionalism among police outweighed this concern.

The policy established in Mapp v. Ohio is known as the "exclusionary rule". This rule holds that if police violate your constitutional rights in order to obtain evidence, they cannot use that evidence against you. If you have been charged with a crime and you feel that the evidence was illegally obtained, your lawyer can make a "motion to suppress" that evidence. The judge will then consider the manner in which the evidence was obtained and make a decision as to whether or not it can be presented during the trial. In many instances, the evidence is central to the prosecution's case, and if the judge grants a motion to suppress, it is not uncommon for all charges to be dropped.

The exclusionary rule is a critical remedy against improper searches, and can be used as an effective protection by citizens who know their rights. The reality is that police officers on the street consider it their primary duty to identify and arrest criminals, and often consider the procedural guidelines which restrict their authority as a secondary concern or even a hindrance. In this context, it is understandable that police sometimes perform searches when they shouldn't. Here's what you should know about illegally seized evidence:

The U.S. Supreme Court's opinion in Herring v. United States further weakened the exclusionary rule by expanding the so-called "good faith" exception. Listen to our podcast on this, "Herring v. U.S. (and why it sucks!)".

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4th Amendment Supreme Court Cases - Know My Rights

Twenty-fourth Amendment | United States Constitution …

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Twenty-fourth Amendment, amendment (1964) to the Constitution of the United States that prohibited the federal and state governments from imposing poll taxes before a citizen can participate in a federal election. It was proposed by the U.S. Congress on August 27, 1962, and was ratified by the states on January 23, 1964.

In 1870, following the American Civil War, the Fifteenth Amendment, guaranteeing the right to vote to former slaves, was adopted. The Twenty-fourth Amendment was adopted as a response to policies adopted in various Southern states after the ending of post-Civil War Reconstruction (186577) to limit the political participation of African Americans. Such policies were bolstered by the 1937 U.S. Supreme Court decision in Breedlove v. Suttles, which upheld a Georgia poll tax. The Supreme Court reasoned that voting rights are conferred by the states and that the states may determine voter eligibility as they see fit, save for conflicts with the Fifteenth Amendment (respecting race) and the Nineteenth Amendment (respecting sex). It further ruled that a tax on voting did not amount to a violation of privileges or immunities protected by the Fourteenth Amendment. In short, because the tax applied to all votersrather than just certain classes of votersit did not violate the Fourteenth or Fifteenth Amendment.

During the civil rights era of the 1950s, particularly following the Brown v. Board of Education decision in 1954, such policies increasingly were seen as barriers to voting rights, particularly for African Americans and the poor. Thus, the Twenty-fourth Amendment was proposed (by Sen. Spessard Lindsey Holland of Florida) and ratified to eliminate an economic instrument that was used to limit voter participation. Two years after its ratification in 1964, the U.S. Supreme Court, invoking the Fourteenth Amendments equal protection clause, in Harper v. Virginia Board of Electors, extended the prohibition of poll taxes to state elections.

The full text of the amendment is:

Section 1The right of citizens of the United States to vote in any primary or other election for President or Vice President, for electors for President or Vice President, or for Senator or Representative in Congress, shall not be denied or abridged by the United States or any State by reason of failure to pay any poll tax or other tax.

Section 2The Congress shall have power to enforce this article by appropriate legislation.

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Twenty-fourth Amendment | United States Constitution ...

19 Artificial Intelligence Technologies That Will Dominate In …

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In 2017, we published a popular post on artificial intelligence (AI) technologies that would dominate that year, based on Forresters TechRadar report.

Heres the updated version, which includes 9 more technologies to watch out for this year.

We hope they inspire you to join the 62% of companies boosting their enterprises in 2018.

Natural language generation is an AI sub-discipline that converts data into text, enabling computers to communicate ideas with perfect accuracy.

It is used in customer service to generate reports and market summaries and is offered by companies like Attivio, Automated Insights, Cambridge Semantics, Digital Reasoning, Lucidworks, Narrative Science, SAS, and Yseop.

Siri is just one of the systems that can understand you.

Every day, more and more systems are created that can transcribe human language, reaching hundreds of thousands through voice-response interactive systems and mobile apps.

Companies offering speech recognition services include NICE, Nuance Communications, OpenText and Verint Systems.

A virtual agent is nothing more than a computer agent or program capable of interacting with humans.

The most common example of this kind of technology are chatbots.

Virtual agents are currently being used for customer service and support and as smart home managers.

Some of the companies that provide virtual agents include Amazon, Apple, Artificial Solutions, Assist AI, Creative Virtual, Google, IBM, IPsoft, Microsoft and Satisfi.

These days, computers can also easily learn, and they can be incredibly intelligent!

Machine learning (ML) is a subdiscipline of computer science and a branch of AI. Its goal is to develop techniques that allow computers to learn.

By providing algorithms, APIs (application programming interface), development and training tools, big data, applications and other machines, ML platforms are gaining more and more traction every day.

They are currently mainly being used for prediction and classification.

Some of the companies selling ML platforms include Amazon, Fractal Analytics, Google, H2O.ai, Microsoft, SAS, Skytree and Adext.

This last one is particularly interesting for one simple reason: Adext AI is the first and only audience management tool in the world that applies real AI and machine learning to digital advertising to find the most profitable audience or demographic group for any ad. You can learn more about it here.

AI technology makes hardware much friendlier.

How?

Through new graphic and central processing units and processing devices specifically designed and structured to execute AI-oriented tasks.

And if you havent seen them already, expect the imminent appearance and wide acceptance of AI-optimized silicon chips that can be inserted right into your portable devices and elsewhere.

You can get access to this technology through Alluviate, Cray, Google, IBM, Intel, and Nvidia.

Intelligent machines are capable of introducing rules and logic to AI systems so you can use them for initial setup/training, ongoing maintenance, and tuning.

Decision management has already been incorporated into a variety of corporate applications to assist and execute automated decision, making your business as profitable as possible.

Check out Advanced Systems Concepts, Informatica, Maana, Pegasystems, and UiPath for additional options.

Deep learning platforms use a unique form of ML that involves artificial neural circuits with various abstraction layers that can mimic the human brain, processing data and creating patterns for decision making.

It is currently mainly being used to recognize patterns and classify applications that are only compatible with large-scale data sets.

Deep Instinct, Ersatz Labs, Fluid AI, MathWorks, Peltarion, Saffron Technology and Sentient Technologies all have deep learning options worthy of exploring.

This technology can identify, measure and analyze human behavior and physical aspects of the bodys structure and form.

It allows for more natural interactions between humans and machines, including interactions related to touch, image, speech and body language recognition, and is big within the market research field.

3VR, Affectiva, Agnitio, FaceFirst, Sensory, Synqera and Tahzoo are all biometrics companies working hard to develop this area.

Robotic processes automation uses scripts and methods that mimic and automate human tasks to support corporate processes.

It is particularly useful for situations when hiring humans for a specific job or task is too expensive or inefficient.

The good example is Adext AI, a platform that automates digital advertising processes using AI, saving businesses from devoting hours to mechanical and repetitive tasks.

Its a solution that lets you make the most of your human talent and move employees into more strategic and creative positions, so their actions can really make an impact on the company's growth.

Advanced Systems Concepts, Automation Anywhere, Blue Prism, UiPath, and WorkFusion are other examples of robotic processes automation companies.

This technology uses text analytics to understand the structure of sentences, as well as their meaning and intention, through statistical methods and ML.

Text analytics and NLP are currently being used for security systems and fraud detection.

They are also being used by a vast array of automated assistants and apps to extract unstructured data.

Some of the service providers and suppliers of these technologies include Basis Technology, Coveo, Expert System, Indico, Knime, Lexalytics, Linguamatics, Mindbreeze, Sinequa, Stratifyd, and Synapsify.

A digital twin is a software construct that bridges the gap between physical systems and the digital world.

General Electric (GE), for example, is building an AI workforce to monitor its aircraft engines, locomotives and gas turbines and predict failures with cloud-hosted software models of GEs machines. Their digital twins are mainly lines of software code, but the most elaborate versions look like 3-D computer-aided design drawings full of interactive charts, diagrams, and data points.

Companies using digital twin and AI modeling technologies include VEERUM, in the capital project delivery space; Akselos, which is using it to protect critical infrastructure, and Supply Dynamics, which has developed a SaaS solution to manage raw material sourcing in complex, highly distributed manufacturing environments.

Cyber defense is a computer network defense mechanism that focuses on preventing, detecting and providing timely responses to attacks or threats to infrastructure and information.

AI and ML are now being used to move cyberdefense into a new evolutionary phase in response to an increasingly hostile environment: Breach Level Index detected a total of over 2 billion breached records during 2017. Seventy-six percent of the records in the survey were lost accidentally, and 69% were an identity theft type of breach.

Recurrent neural networks, which are capable of processing sequences of inputs, can be used in combination with ML techniques to create supervised learning technologies, which uncover suspicious user activity and detect up to 85% of all cyber attacks.

Startups such as Darktrace, which pairs behavioral analytics with advanced mathematics to automatically detect abnormal behavior within organizations and Cylance, which applies AI algorithms to stop malware and mitigate damage from zero-day attacks, are both working in the area of AI-powered cyber defense.

DeepInstinct, another cyber defense company, is a deep learning project named Most Disruptive Startup by Nvidias Silicon Valley ceremony, protects enterprises' endpoints, servers, and mobile devices.

Compliance is the certification or confirmation that a person or organization meets the requirements of accepted practices, legislation, rules and regulations, standards or the terms of a contract, and there is a significant industry that upholds it.

We are now seeing the first wave of regulatory compliance solutions that use AI to deliver efficiency through automation and comprehensive risk coverage.

Some examples of AIs use in compliance are showing up across the world. For example, NLP (Natural Language Processing) solutions can scan regulatory text and match its patterns with a cluster of keywords to identify the changes that are relevant to an organization.

Capital stress testing solutions with predictive analytics and scenario builders can help organizations stay compliant with regulatory capital requirements. And the volume of transaction activities flagged as potential examples of money laundering can be reduced as deep learning is used to apply increasingly sophisticated business rules to each one.

Companies working in this area include Compliance.ai, a Retch company that matches regulatory documents to a corresponding business function; Merlon Intelligence, a global compliance technology company that supports the financial services industry to combat financial crimes, and Socure, whose patented predictive analytics platform boosts customer acceptance rates while reducing fraud and manual reviews.

While some are rightfully concerned about AI replacing people in the workplace, lets not forget that AI technology also has the potential to vastly help employees in their work, especially those in knowledge work.

In fact, the automation of knowledge work has been listed as the #2 most disruptive emerging tech trend.

The medical and legal professions, which are heavily reliant on knowledge workers, is where workers will increasingly use AI as a diagnostic tool.

There is an increasing number of companies working on technologies in this area. Kim Technologies, whose aim is to empower knowledge workers who have little to no IT programming experience with the tools to create new workflow and document processes with the help of AI, is one of them. Kyndi is another, whose platform is designed to help knowledge workers process vast amounts of information.

Content creation now includes any material people contribute to the online world, such as videos, ads, blog posts, white papers, infographics and other visual or written assets.

Brands like USA Today, Hearst and CBS, are already using AI to generate their content.

Wibbitz, a SaaS tool that helps publishers create videos from written content in minutes with AI video production technology, is a great example of a solution from this field. Wordsmith is another tool, created by Automated Insights, that applies NLP (Natural Language Processing) to generate news stories based on earnings data.

Peer-to-peer networks, in their purest form, are created when two or more PCs connect and share resources without the data going through a server computer.

But peer-to-peer networks are also used by cryptocurrencies, and have the potential to even solve some of the worlds most challenging problems, by collecting and analyzing large amounts of data, says Ben Hartman, CEO of Bet Capital LLC, to Entrepreneur.

Nano Vision, a startup that rewards users with cryptocurrency for their molecular data, aims to change the way we approach threats to human health, such as superbugs, infectious diseases, and cancer, among others.

Another player utilizing peer-to-peer networks and AI is Presearch, a decentralized search engine thats powered by the community and rewards members with tokens for a more transparent search system.

This technology allows software to read the emotions on a human face using advanced image processing or audio data processing. We are now at the point where we can capture micro-expressions, or subtle body language cues, and vocal intonation that betrays a persons feelings.

Law enforcers can use this technology to try to detect more information about someone during interrogation. But it also has a wide range of applications for marketers.

There are increasing numbers of startups working in this area. Beyond Verbal analyzes audio inputs to describe a persons character traits, including how positive, how excited, angry or moody they are. nViso uses emotion video analytics to inspire new product ideas, identify upgrades and enhance the consumer experience. And Affectivas Emotion AI is used in the gaming, automotive, robotics, education, healthcare industries, and other fields, to apply facial coding and emotion analytics from face and voice data.

Image recognition is the process of identifying and detecting an object or feature in a digital image or video, and AI is increasingly being stacked on top of this technology to great effect.

AI can search social media platforms for photos and compare them to a wide range of data sets to decide which ones are most relevant during image searches.

Image recognition technology can also be used to detect license plates, diagnose disease, analyze clients and their opinions and verify users based on their face.

Clarifai provides image recognition systems for customers to detect near-duplicates and find similar uncategorized images.

SenseTime is one of the leaders in this industry and develops face recognition technology that can be applied to payment and picture analysis for bank card verification and other applications. And GumGums mission is to unlock the value of images and videos produced across the web using AI technology.

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19 Artificial Intelligence Technologies That Will Dominate In ...

4 Artificial Intelligence Trends to Watch for in 2019

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Siri and Alexa are going to become a lot more useful to you in the near future.

November27, 20185 min read

Opinions expressed by Entrepreneur contributors are their own.

Consumers have been skittish about the notion of artificial intelligence (AI) invading their homes:What if robots take over the world?Whos spying on me? Who'slistening to my conversations? But now those same consumers are starting to embracethe new technology in their personal lives and businesses.

Related:10 Artificial Intelligence Trends to Watch in 2018

This in turn has raised the confidence of companies interested in the technology -- so much so that companies have tripled their AI investment since 2013, according to a survey by McKinsey & Company.

AI, in fact, has the potential to completely change the way companies do business; and because of technological developments, more companies, in 2019, will be able to access and implement this life-changing technology. Already, companies like Amazon, Microsoft and Google are leading the way.

So, given those expected future advances for the technology, check out four AI trends to watch for in 2019.

Consumers have been benefiting from having AI assistants in their homes for some time now with the introduction of Apples Siri, Amazons Alexa and other devices. You can ask AI assistants to play you a song, tell you the weather, search out information online, turn off your house lights and much more.

Consumers have been embracing this new AI-powered technology. In fact, in a study from Adobe Analytics, 71 percent of smart-speaker owners reported using them at least daily, while 44 percent said they used them multiple times a day. So, in 2019, expect to see even more advanced AI assistants in your home, at work and in other areas of your life.

As of now, what consumers ask AI assistants to do is pretty basic, like searching for and playing a particular song. But expect to see big changes in the tasks AI assistants canperform in the near future. AI assistants will soon be able to provide even more individualized experiences as they get better at recognizing different users' voices.

Instead of just speaking to your AI home device or your mobile phone, I predict youll soon be able to speak to your car, TV, refrigerator -- even your lamps.

Related:The Impact of Artificial Intelligence on 2018's Top HR Trends

According to a survey from Indeed, 42 percent of employers polled were worried that they wouldn't be able to find the talent they needed. For many businesses, the recruiting process is one of their most time-consuming and stressful tasks, but with advancements in artificial intelligence, AI-powered recruiting tools will be a recruitment trend to watch for in 2019.

For example, Mya, which stands for My Recruiting Assistant,is a chatbot recruiting assistant. It can communicate with candidates via Skype, emailor text. It can pre-qualify candidates for you and even reject a candidate if you decide to pass on his or her application.

Image credit: Hiremya.com

Along with AI-powered screening and candidate-communication tools, a number of emerging artificial intelligence toolsare emerging that will help employers save even more time and find the candidates they need next year.

Because users will soon start using AI-powered assistants in new ways and more often, advanced conversational AI-powered search will be a huge trend. With the introduction of voice search, the way in which consumers search online has changed. Instead of typing in a search query like condos for sale Dallas,consumers will be able to speak their search queries using a more conversational phrase, like, What condos are for sale in Dallas for under $150,000?

In other words, the way users are provided answers to their queries will become more advanced as well.

Continuing with the condo example, AI-powered search engines will do more than just providing users with a number of listings; they'll also receive more conversational answers. Search engines could follow up with questions to provide more detailed solutions by asking, say:

How many bedrooms do you want?

What neighborhood would you prefer to live in?

Would you prefer a gym and pool on the premises?

Users will then be able to narrow down the solutions and get exactly the search results theyre looking for. Since consumers are changing the way they search, the quality of the results they expect to get is changing, as well, pushing AI to keep up with those expectations next year.

Chatbots have been improving customer service for businesses of all types in recent years; you can even order a pizza through a Facebook chatbot now. In 2019, expect chatbots to become even more advanced and human than before. With natural language programming, you no longer have to have a robotic conversation: Consumers can speak to chatbots just as they would a live chat agent. Beyond simple chatbots, more companies will also be implementing life-like animated virtual agents, too.

Autodesk recently unveiled its virtual agent,Ava. Ava is a digital human who can answer customers' questions, direct them to content and help them check out, as well as respond interactively to emotional signals from those users.

Image credit: Ava digital human image on YouTube

More and more retailers and businesses will be using conversational chatbots and virtual agents to solve customer service issues without having to pass users off to a real-life staffer.

Related:5 Tech Trends Content Creators Need to Pay Attention To

So, now you have four useful and exciting AI trends to look forward to in the new year. As AI advances, your businesswill be able to take advantage of this technology to not only give you more convenience in your personal life, but help you run a more efficient and profitable business.

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4 Artificial Intelligence Trends to Watch for in 2019

The Rise of the Artificially Intelligent Hedge Fund | WIRED

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Last week, Ben Goertzel and his company, Aidyia, turned on a hedge fund that makes all stock trades using artificial intelligenceno human intervention required. "If we all die," says Goertzel, a longtime AI guru and the company's chief scientist, "it would keep trading."

He means this literally. Goertzel and other humans built the system, of course, and they'll continue to modify it as needed. But their creation identifies and executes trades entirely on its own, drawing on multiple forms of AI, including one inspired by genetic evolution and another based on probabilistic logic. Each day, after analyzing everything from market prices and volumes to macroeconomic data and corporate accounting documents, these AI engines make their own market predictions and then "vote" on the best course of action.

If we all die, it would keep trading.

Ben Goertzel, Aidyia

Though Aidyia is based in Hong Kong, this automated system trades in US equities, and on its first day, according to Goertzel, it generated a 2 percent return on an undisclosed pool of money. That's not exactly impressive, or statistically relevant. But it represents a notable shift in the world of finance. Backed by $143 million in funding, San Francisco startup Sentient Technologies has been quietly trading with a similar system since last year. Data-centric hedge funds like Two Sigma and Renaissance Technologies have said they rely on AI. And according to reports, two othersBridgewater Associates and Point72 Asset Management, run by big Wall Street names Ray Dalio and Steven A. Cohenare moving in the same direction.

Hedge funds have long relied on computers to help make trades. According to market research firm Preqin, some 1,360 hedge funds make a majority of their trades with help from computer modelsroughly 9 percent of all fundsand they manage about $197 billion in total. But this typically involves data scientistsor "quants," in Wall Street lingousing machines to build large statistical models. These models are complex, but they're also somewhat static. As the market changes, they may not work as well as they worked in the past. And according to Preqin's research, the typical systematic fund doesn't always perform as well as funds operated by human managers (see chart below)

Preqin/WIRED

In recent years, however, funds have moved toward true machine learning, where artificially intelligent systems can analyze large amounts of data at speed and improve themselves through such analysis. The New York company Rebellion Research, founded by the grandson of baseball Hall of Famer Hank Greenberg, among others, relies upon a form of machine learning called Bayesian networks, using a handful of machines to predict market trends and pinpoint particular trades. Meanwhile, outfits such as Aidyia and Sentient are leaning on AI that runs across hundreds or even thousands of machines. This includes techniques such as evolutionary computation, which is inspired by genetics, and deep learning, a technology now used to recognize images, identify spoken words, and perform other tasks inside Internet companies like Google and Microsoft.

The hope is that such systems can automatically recognize changes in the market and adapt in ways that quant models can't. "They're trying to see things before they develop," says Ben Carlson, the author of A Wealth of Common Sense: Why Simplicity Trumps Complexity in Any Investment Plan, who spent a decade with an endowment fund that invested in a wide range of money managers.

This kind of AI-driven fund management shouldn't be confused with high-frequency trading. It isn't looking to front-run trades or otherwise make money from speed of action. It's looking for the best trades in the longer termhours, days, weeks, even months into the future. And more to the point, machinesnot humansare choosing the strategy.

Though the company has not openly marketed its fund, Sentient CEO Antoine Blondeau says it has been making official trades since last year using money from private investors (after a longer period of test trades). According to a report from Bloomberg, the company has worked with the hedge fund business inside JP Morgan Chase in developing AI trading technology, but Blondeau declines to discuss its partnerships. He does say, however, that its fund operates entirely through artificial intelligence.

The whole idea is to do something no other humanand no other machineis doing.

The system allows the company to adjust certain risk settings, says chief science officer Babak Hodjat, who was part of the team that built Siri before the digital assistant was acquired by Apple. But otherwise, it operates without human help. "It automatically authors a strategy, and it gives us commands," Hodjat says. "It says: 'Buy this much now, with this instrument, using this particular order type.' It also tells us when to exit, reduce exposure, and that kind of stuff."

According to Hodjat, the system grabs unused computer power from "millions" of computer processors inside data centers, Internet cafes, and computer gaming centers operated by various companies in Asia and elsewhere. Its software engine, meanwhile, is based on evolutionary computationthe same genetics-inspired technique that plays into Aidyia's system.

In the simplest terms, this means it creates a large and random collection of digital stock traders and tests their performance on historical stock data. After picking the best performers, it then uses their "genes" to create a new set of superior traders. And the process repeats. Eventually, the system homes in on a digital trader that can successfully operate on its own. "Over thousands of generations, trillions and trillions of 'beings' compete and thrive or die," Blondeau says, "and eventually, you get a population of smart traders you can actually deploy."

Though evolutionary computation drives the system today, Hodjat also sees promise in deep learning algorithmsalgorithms that have already proven enormously adept at identify images, recognizing spoken words, and even understanding the natural way we humans speak. Just as deep learning can pinpoint particular features that show up in a photo of a cat, he explains, it could identify particular features of a stock that can make you some money.

Goertzelwho also oversees the OpenCog Foundation, an effort to build an open source framework for general artificial intelligencedisagrees. This is partly because deep learning algorithms have become a commodity. "If everyone is using something, it's predictions will be priced into the market," he says. "You have to be doing something weird." He also points out that, although deep learning is suited to analyzing data defined by a very particular set of patterns, such as photos and words, these kinds of patterns don't necessarily show up in the financial markets. And if they do, they aren't that usefulagain, because anyone can find them.

For Hodjat, however, the task is to improve on today's deep learning. And this may involve combining the technology with evolutionary computation. As he explains it, you could use evolutionary computation to build better deep learning algorithms. This is called neuroevolution. "You can evolve the weights that operate on the deep learner," Hodjat says. "But you can also evolve the architecture of the deep learner itself." Microsoft and other outfits are already building deep learning systems through a kind of natural selection, though they may not be using evolutionary computation per se.

Whatever methods are used, some question whether AI can really succeed on Wall Street. Even if one fund achieves success with AI, the risk is that others will duplicate the system and thus undermine its success. If a large portion of the market behaves in the same way, it changes the market. "I'm a bit skeptical that AI can truly figure this out," Carlson says. "If someone finds a trick that works, not only will other funds latch on to it but other investors will pour money into. It's really hard to envision a situation where it doesn't just get arbitraged away."

Goertzel sees this risk. That's why Aidyia is using not just evolutionary computation but a wide range of technologies. And if others imitate the company's methods, it will embrace other types of machine learning. The whole idea is to do something no other humanand no other machineis doing. "Finance is a domain where you benefit not just from being smart," Goertzel says, "but from being smart in a different way from others."

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The Rise of the Artificially Intelligent Hedge Fund | WIRED