Google Brain co-founder raises $175 million fund for AI startups

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Ng announced Tuesday that he raised money from venture capital firms New Enterprise Associates, Sequoia Capital and Greylock Partners as well as SoftBank Group Corp. Under Ng, Baidu released a voice-based operating system that users can talk to - much like Amazon's Alexa voice assistant or Apple's Siri - and also started working on self-driving cars and face recognition technology to open things like transit turnstiles when users approach. I think it's a more systematic, repeatable process than most people think," said Ng, who also taught artificial intelligence courses at Stanford University. The first company to receive money from the fund will be Landing.ai,


Apple's Latest Move Could Help It Compete With Google

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Across Silicon Valley, technology companies are scrambling to make their software smarter with the help of artificial intelligence. Both Apple and Google have made significant improvements to their virtual assistants, Siri and Google Now, that help them better understand what a user might need before he or she asks. Meanwhile, Facebook has unveiled plans to create its own intelligent chat bot that can perform tasks on your behalf. As of this week, Apple has more firepower in the AI department. The Cupertino, Calif.-based company has purchased Emotient, a company that uses artificial intelligence to interpret a person's emotions, The Wall Street Journal first reported Thursday.


Apple's purchase of Emotient fuels artificial intelligence boom in Silicon Valley

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The arms race in Silicon Valley is on for artificial intelligence. Facebook is working on a virtual personal assistant that can read people's faces and decide whether or not to let them in your home. Google is investing in the technology to power self-driving cars, identify people on its photo service and build a better messaging app. Now Apple is adding to its artificial intelligence arsenal. The iPhone maker purchased Emotient, a San Diego maker of facial expression recognition software that can detect emotions to assist advertisers, retailers, doctors and many other professions.


A polynomial-time relaxation of the Gromov-Hausdorff distance

arXiv.org Machine Learning

The Gromov-Hausdorff distance provides a metric on the set of isometry classes of compact metric spaces. Unfortunately, computing this metric directly is believed to be computationally intractable. Motivated by applications in shape matching and point-cloud comparison, we study a semidefinite programming relaxation of the Gromov-Hausdorff metric. This relaxation can be computed in polynomial time, and somewhat surprisingly is itself a pseudometric. We describe the induced topology on the set of compact metric spaces. Finally, we demonstrate the numerical performance of various algorithms for computing the relaxed distance and apply these algorithms to several relevant data sets. In particular we propose a greedy algorithm for finding the best correspondence between finite metric spaces that can handle hundreds of points.


Google Brain Co-Founder Teams With Foxconn to Bring AI to Factories

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Consumers now experience AI mostly through image recognition to help categorize digital photographs and speech recognition that helps power digital voice assistants such as Apple Inc's Siri or Amazon.com But at a press briefing in San Francisco two days before Ng's Landing.ai In many factories, workers look over parts coming off an assembly line for defects. Ng showed a video in which a worker instead put a circuit board beneath a digital camera connected to a computer and the computer identified a defect in the part. Ng said that while typical computer vision systems might require thousands of sample images to become "trained," Landing.ai's