Cogitai, a new company aimed at developing and commercializing core artificial intelligence (AI) technologies, today announced a strategic investment from Sony Corporation. Cogitai is focused on addressing one of the biggest problems confronting AI: namely, that no existing AI system has an understanding of the world comparable to a human's. Even small children in the first few years of life develop an understanding of the world far richer and more sophisticated than the most elaborate AI systems on earth. To address this problem, Cogitai is committed to developing systems that learn continually from their experience. "Our continual-learning technology will allow computer systems to build knowledge and skills simply through interacting with the world around them," said Dr. Mark Ring, CEO of Cogitai.

The driving motivations behind the installation of AI in business processes appear to be the greater speed, accuracy and volume capability of computers when compared to their existing human counterparts. Many businesses are already using robotic process automation systems to crunch numbers and sift data on a daily basis. For example, Kensho is an intelligent computer system widely used by stock traders and investors to automatically analyse portfolio performance and predict market changes. The software is described as'the world's first computational knowledge engine for the financial industry'. It claims to address Wall Street's greatest challenge – automating and improving on previously human-intensive knowledge work to keep up with the split-second changeability of stock. Kensho's founder, Daniel Nadler, told the New York Times Magazine: ''People always tell me, 'I used to spend two out of five days a week doing this sort of thing,' or'I used to have a guy whose job it was to do nothing other than this one thing'.''

"The Trick That Makes Google's Self-Driving Cars Work," by Alexis C. Madrigal: Madrigal throws a little cold water on the supposed power of Google's self-driving cars, which can cruise around Mountain View, California, on their own. He shows that the company's vehicles are effectively operating in a meticulously modeled digital double of their environs, one that would take time to reproduce elsewhere.

If you're just talking about the time until we see some driverless vehicles on the road, probably not that long. Anthony Foxx, secretary of the U.S. Department of Transportation, went on the record in 2015 with the claim that "we're going to see [fully autonomous cars] within five years," though he allows that that "just means market availability." A more comprehensive timeline assembled by Recode suggests that by 2030, "Automakers will stop manufacturing cars that don't have at least some highly autonomous features." It goes on to predict that by the middle of the 21st century, we'll witness total fleet turnover, at which point virtually all vehicles on the road will be at least partially autonomous. If that's true, it's possible that driving your own car will rapidly come to be seen as a dangerous affectation like smoking

At first glance, 'intent to leave' seems like it should be pretty good predictor of turnover. If a coworker told me that they were going to quit, I feel like I'd have a pretty good sense of how likely they were to leave. However, many researchers have developed constructs to measure this intention and the results are surprising. For example, there was a meta-analytic study (i.e., study of studies) in 2000 by Rodger Griffeth and Peter Hom on turnover that found the construct'intent to leave' had a shared variance with actually leaving of 12% across all studies (explains roughly 12% of why people leave). That's pretty good for a study on human behavior, but it does leave a reader wondering what is going on.

Risk assessment scoring algorithms are used in courtrooms throughout the United States to determine whether someone is more likely to commit a future crime. Evidence shows they are biased against blacks. "There's software used across the country to predict future criminals. And it's biased against blacks. ON A SPRING AFTERNOON IN 2014, Brisha Borden was running late to pick up her god-sister from school when she spotted an unlocked kid's blue Huffy bicycle and a silver Razor scooter. Borden and a friend grabbed the bike and scooter and tried to ride them down the street in the Fort Lauderdale suburb of Coral Springs.Just as the 18-year-old girls were realizing they were too big for the tiny conveyances -- which belonged to a 6-year-old boy -- a woman came running after them saying, "That's my kid's stuff." Borden and her friend immediately dropped the bike and scooter and walked away. But it was too late -- a neighbor who witnessed the heist had already called the police. Borden and her friend were arrested and charged with burglary and petty theft for the items, which were valued at a total of 80. Compare their crime with a similar one: The previous summer, 41-year-old Vernon Prater was picked up for shoplifting 86.35 worth of tools from a nearby Home Depot store. Prater was the more seasoned criminal. He had already been convicted of armed robbery and attempted armed robbery, for which he served five years in prison, in addition to another armed robbery charge. Borden had a record, too, but it was for misdemeanors committed when she was a juvenile. Yet something odd happened when Borden and Prater were booked into jail: A computer program spat out a score predicting the likelihood of each committing a future crime. Borden -- who is black -- was rated a high risk. Prater -- who is white -- was rated a low risk."

Dyson, the British technology giant primarily known for selling vacuum cleaners, plans to sell its first hair dryer in the United States this September. It's a big moment for Dyson given that it wants to be known as not just…

The future of the way we work will be put under the spotlight by some of the leading minds in technology and computing at the International Festival for Business 2016 (IFB2016). The advancement of Artificial Intelligence and its use in modern life has prompted debate on whether men and women will be needed to work in business in years to come. Scientists have created robots who can do cognitive work and the nightmarish future of androids ruling the planet with brutal oppression has long been a science fiction storyline. A panel which will include a brain specialist, a tech lawyer, a technology expert and a union leader will explore the possibility of humans becoming obsolete in the workplace in reality. The discussion, Man and Woman vs Machine: Is AI Going to Take Your Job?' will take over the Blue Skies Stage in the Liverpool Exhibition Centre on Thursday June 16.

Algorithmic systems that employ machine learning play an increasing role in making substantive decisions in modern society, ranging from online personalization to insurance and credit decisions to predictive policing. But their decision-making processes are often opaque--it is difficult to explain why a certain decision was made. We develop a formal foundation to improve the transparency of such decision-making systems. Specifically, we introduce a family of Quantitative Input Influence (QII) measures that capture the degree of influence of inputs on outputs of systems. These measures provide a foundation for the design of transparency reports that accompany system decisions (e.g., explaining a specific credit decision) and for testing tools useful for internal and external oversight (e.g., to detect algorithmic discrimination). Distinctively, our causal QII measures carefully account for correlated inputs while measuring influence. They support a general class of transparency queries and can, in particular, explain decisions about individuals (e.g., a loan decision) and groups (e.g., disparate impact based on gender). Finally, since single inputs may not always have high influence, the QII measures also quantify the joint influence of a set of inputs (e.g., age and income) on outcomes (e.g.

According to the newspaper, the Toyota Research Institute will use its 1 billion budget to purchase both companies. The Institute was established in November 2015 to develop AI, robotics and autonomous car technologies and opened its first facility in Silicon Valley in January. Earlier this week, Tech Insider reported that the "ink is nearly dry" on the deal, suggesting it won't be long until Alphabet and Toyota formally announce the trade. It added autonomous vehicle specialist Jaybridge Robotics to its team in March, now it's looking to bolster its team ahead of a possible rollout of self-driving cars in 2020. Let's hope Spot, Atlas and AlphaDog make the journey too.