The letter was signed by experts in AI research, policy, and law, including Stanford University's Percy Liang; Pulitzer Prize-winning journalist Julia Angwin; Renée DiResta from the Stanford Internet Observatory; Mozilla fellow Deb Raji, who has pioneered research into auditing AI models; ex-government official Marietje Schaake, a former member of European Parliament; and Brown University professor Suresh Venkatasubramanian, a former adviser to the White House Office of Science and Technology Policy.

This article was syndicated from the Bulletin of the Atomic Scientists, which has covered human-made threats to humanity since 1945. The main artery in Montreal's Little Italy is lined with cafés, wine bars, and pastry shops that spill into tree-lined, residential side streets. Generations of farmers, butchers, bakers, and fishmongers sell farm-to-table goods in the neighborhood's large, open-air market, the Marché Jean-Talon. But the quiet enclave also accommodates a modern, 90,000-square-foot global AI hub known as Mila–Quebec AI Institute. Mila claims to house the largest concentration of deep learning academic researchers in the world, including more than 1,000 researchers and more than 100 professors who work with more than 100 industry partners from around the globe.

Google CEO Sundar Pichai apologized to staffers on Wednesday for the company's handling of AI ethics researcher Dr. Timnit Gebru's departure. The Google CEO also pledged to launch a "review" of Gebru's departure in an attempt to "identify all the points where we can learn." Days prior to Pichai's apology, Gebru - who had been one of the 1.6% of Google's employees who are Black women - claimed she was terminated from the company shortly after sending an email regarding her disappointment in Google's approach to diversity, equity and inclusion. Google AI researcher Nicholas Le Roux, a white man, defended his ex-colleague on Twitter, arguing that the "easiest way to discriminate is to make stringent rules, then to decide when and for whom to enforce them." Other individuals, like former Google public relations manager William Fitzgerald, expressed their disagreement with the company's handling of the situation.

Kemal El Moujahid, director of product management at Google, speaks at the World Artificial Intelligence Conference 2019 in Shanghai on August 30.

The CIFAR deep learning summer school in Toronto has been training the top AI researchers entering or finishing Ph.D. programs since 2005. Over 1,200 students from 60 different countries applied, of which 200 were selected to attend. Attendees represent some of the leading AI labs in the world, Montreal Institute of Learning Algorithms (MILA), University College London, University of Toronto, University of Alberta, Berkeley, NYU, Columbia, CMU, MIT, ETH Zurich, and Stanford. Every year, the school has trained the next generation of top AI researchers which now hold top posts at AI companies like Google, Facebook, Tesla, and Uber. During an intense 10-day period, students learn the tricks of the trade from top AI researchers like deep learning pioneers Yoshua Bengio (MILA), Geoff Hinton (UofT), and reinforcement learning pioneer, Richard Sutton (University of Alberta, Google Deepmind).

Node, an AI-driven search tool designed to surface the information that matters most to you, announced today that it was bringing on a couple of AI research heavy hitters. It also announced $5 million in additional funding. For starters, the company hired Louis Mornier, one of the founders of early internet search engine, Alta Vista, and most recently the Head of the AI Lab at Airbnb. Mornier will join the startup as Chief Scientist. The company also brought on Jeffrey Johnson as Chief Technology Officer in January.

General Electric builds jet engines and wind turbines and medical gear. But the 124-year-old industrial giant is also transforming itself for the digital age. It's fashioning software that pulls data from all this hardware, hoping to gain an insight into industrial operations that was never possible in the past. The problem is that analyzing all this data is difficult, and the talent needed to make it happen is scarce. So GE is going shopping.

General Electric builds jet engines and wind turbines and medical gear. But the 124-year-old industrial giant is also transforming itself for the digital age. It's fashioning software that pulls data from all this hardware, hoping to gain an insight into industrial operations that was never possible in the past. The problem is that analyzing all this data is difficult, and the talent needed to make it happen is scarce. So GE is going shopping.