The promise of artificial intelligence could be lost to humanity because people fear Terminator-style robots and other doomsday scenarios, an expert has warned. Hyperbole about the risks of artificial intelligence threaten to scupper developments that could assist humanity, from driverless cars that could cut down road accidents to medical systems that could revolutionise healthcare, said Chris Bishop, director of Microsoft Research in Cambridge. "The danger I see is if we spend too much of our attention focusing on Terminators and Skynet and the end of humanity – or generally just painting a too negative, emotive and one-sided view of artificial intelligence – we may end up throwing the baby out with the bathwater," Bishop told the Guardian ahead of a discussion about machine learning at the Royal Society on Tuesday. He said he "completely disagreed" with the views of high-profile naysayers such as Elon Musk and Stephen Hawking. The latter has previously warned that the "development of full artificial intelligence could spell the end of the human race".

Economists have largely preferred to act within their own field and interpretations. However, the rise of big data challenges, data analytics, and machine learning is beginning to change all that. In the summer of 2015, Susan Athey, a Professor of Economics of Technology at Stanford attracted a crowd of over 250 economists for a one-day instructive session on machine learning. Historically, the discipline of economics has always been categorized among the social sciences, which means the word'science' should be understood as somewhat loosely applied. Unlike the natural sciences, which are prescribed as strictly positivist and bound by the ideals of empirical truth to only build theories around quantitative data that can be measured and duplicated, social sciences are often influenced by observations that are open to interpretation.

The artificial intelligence craze continues to spread in the enterprise market. Last week saw Nvidia Inc. add its name to the long list of vendors trying to monetize the trend by introducing a new graphical processing unit specifically designed to run deep learning algorithms. The Tesla P100, as the chip is called, is the biggest of its kind by far thanks to a 15-billion transistor count that took the company's engineers some two years to achieve. Nvidia says that the GPU also includes faster memory than its previous-generation cards and a new interconnect technology called NVLink designed to increase processing speed even further. Its impressive feature set has already attracted orders from Hewlett-Packard Enterprise, IBM Corp. and several other top data center equipment makers that presumably plan on incorporating Tesla P100s into their high-performance computing systems.

Computers have long been good at carrying out assigned tasks but terrible at learning things on their own. Thus all the excitement around "neural networks," a breakthrough artificial intelligence technique that mimics the structure of the human brain and allows machines to learn things independently. Tech giants are using neural networks to do some pretty impressive things. Microsoft is using them to make instant translation real for Skype. Google's artificial intelligence learned Atari video games and then mastered the ancient game of Go, with its AlphaGo program beating the human champion Lee Sedol 4 to 1.

At a time when the banking industry needs to become increasingly focused on creating better customer experiences, the importance of distributing personalized communications that provide real value has never been greater. Artificial intelligence (AI) can help make this possible -- both automatically and at scale. The banking industry is undergoing a major transformation. Evolving regulatory requirements, more demanding customers, and greater competition from new, non-traditional players are among the catalysts driving change. Collectively, these and other factors are forcing banks and credit unions to rethink their business and how they engage with consumers.

It's been a busy month in the field of artificial intelligence (AI). In a face-off of man versus machine, the world champion of the Go board game lost to Google's AI program. And just last week, Microsoft unveiled a program designed to Tweet like a teenage girl -- only to have it devolve into praising Hitler and lambasting feminists. You've probably seen one of the many commercials featuring the IBM supercomputer Watson, which made waves a few years ago when it easily defeated two "Jeopardy!" Watson even analyzes trends in music now, as seen in a recent advertising spot featuring Bob Dylan.

With oil and gas prices hovering at decade lows, companies are turning to artificial intelligence to cut costs and boost productivity. The technology, which gives companies the ability to predict future problems, is estimated to save the industry trillions of dollars and lead to a new wave of highly sophisticated jobs. GE Oil and Gas is at the forefront of the shift, using artificial intelligence software to help producers become more efficient. The company's regional director, Mary Hackett, said the recent downturn in prices was driving interest in the technology. "We now need to rather than add to production, we need to make production more efficient and it's that, that will change this industry," she said.

Ever since I learned about neural networks playing Atari games I wanted to reimplemnted it and learn how it works. Below you can see an AI playing Space Invaders. I trained it during my batch at Recurse Center on little over 50M frames. It is more awesome if you realize that the AI was trained in a similar way a human would learn: the only inputs are screen and number of gained (or lost) points after each action taken by the AI. DQN does much better then a best-action strategy (do nothing but shoot) and random strategy.

As a former research scientist at Google, Ian Goodfellow has had a direct hand in some of the more complex, promising frameworks set to power the future of deep learning in coming years. He spent his first years at the search giant chipping away at TensorFlow, creating new capabilities, including the creation of a new element to the deep learning stack, called generative adversarial networks. And as part of the Google Brain team, he furthered this work and continued to optimize machine learning algorithms used by Google and now, the wider world. Goodfellow has since moved on to the non-profit OpenAI company, where he is further refining what might be possible with generative adversarial networks. The mission of OpenAI is to develop open source tools to further many of the application areas that were showcased this week at the the GPU Technology Conference this week in San Jose, where the emphasis was placed squarely on the future of deep learning, and of course, the role that Nvidia's accelerators will play in the training and execution of neural networks and other machine learning. There has been a fair bit about VR and gaming, of course, but for a company that is placing its best on where the big money for its graphics chips will be in the next decade, the focus is likely not misplaced.

Australia has warned the world that artificially intelligent killer robots "may be closer than many of us had imagined" and nations need to work harder to tackle the future threat they may pose. Is the Australian Defence Force the next big customer for unmanned aerial vehicles? At a United Nations meeting on "lethal autonomous weapons systems" in Geneva, Switzerland, the Australian delegation on Monday night called on the world to come up with agreed rules about how to handle the rapid pace in technology in military artificial intelligence. "The development of fully autonomous systems able to conduct military targeting operations which kill and injure combatants or civilians may be closer than many of us had imagined," the delegation's statement said. "It is an appropriate time to consider the risks of such weapons systems and to make sure we understand fully what might constitute misuse as well as legitimate use of emerging technologies."