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OpenAI teaches a robotic hand to solve a Rubik's cube

#artificialintelligence

Robots with truly humanlike dexterity are far from becoming reality, but progress accelerated by AI has brought us closer to achieving this vision than ever before. In a research paper published in September, a team of scientists at Google detailed their tests with a robotic hand that enabled it to rotate Baoding balls with minimal training data. And at a computer vision conference in June, MIT researchers presented their work on an AI model capable of predicting the tactility of physical things from snippets of visual data alone. Now, OpenAI -- the San Francisco-based AI research firm cofounded by Elon Musk and others, with backing from luminaries like LinkedIn cofounder Reid Hoffman and former Y Combinator president Sam Altman -- says it's on the cusp of solving something of a grand challenge in robotics and AI systems: solving a Rubik's cube. Unlike breakthroughs achieved by teams at the University of California, Irvine and elsewhere, which leveraged machines tailor-built to manipulate Rubik's cubes with speed, the approach devised by OpenAI researchers uses a five-fingered humanoid hand guided by an AI model with 13,000 years of cumulative experience -- on the same order of magnitude as the 40,000 years used by OpenAI's Dota-playing bot.


Upfront Ventures, L.A. County's biggest venture capital firm, just got bigger

Los Angeles Times

Los Angeles County's most prominent start-up investor just got bigger. Upfront Ventures closed June with the announcement of a $400-million investment fund that it plans to spend on dozens of start-ups in the next couple of years. It's believed to be Los Angeles County's largest-ever venture capital fund by raw number, though Upfront Ventures' $390-million investment fund in 2000 comes out far on top when adjusted for inflation. Still, it beats the $280 million that Upfront Ventures picked up at the end of 2014. Mark Suster, managing partner at the firm, declined to provide specifics about the returns that prior funds have generated.


L.A. County to require licenses for immigration consultants

Los Angeles Times

Moving to crack down on scam artists, Los Angeles County supervisors voted Tuesday to require immigration consultants working in unincorporated areas of the county to be licensed. The consultants, sometimes referred to as "notarios," are not attorneys. But some offer legal services and charge high rates. Because notary publics in Latin America are roughly equivalent to lawyers, immigrants often do not realize that in the United States they are only authorized to witness signatures and authenticate documents, said Supervisor Hilda Solis, who proposed the enforcement program along with Supervisor Sheila Kuehl. "I've spoken with numerous families who have been for years paying dollar after dollar without making any progress on their immigration matters," Solis said.


Machine-Learning Maestro Michael Jordan on the Delusions of Big Data and Other Huge Engineering Efforts

@machinelearnbot

The overeager adoption of big data is likely to result in catastrophes of analysis comparable to a national epidemic of collapsing bridges. Hardware designers creating chips based on the human brain are engaged in a faith-based undertaking likely to prove a fool's errand. Despite recent claims to the contrary, we are no further along with computer vision than we were with physics when Isaac Newton sat under his apple tree. Those may sound like the Luddite ravings of a crackpot who breached security at an IEEE conference. In fact, the opinions belong to IEEE Fellow Michael I. Jordan, Pehong Chen Distinguished Professor at the University of California, Berkeley. Jordan is one of the world's most respected authorities on machine learning and an astute observer of the field. His CV would require its own massive database, and his standing in the field is such that he was chosen to write the introduction to the 2013 National Research Council report "Frontiers in Massive Data Analysis." San Francisco writer Lee Gomes interviewed him for IEEE Spectrum on 3 October 2014. IEEE Spectrum: I infer from your writing that you believe there's a lot of misinformation out there about deep learning, big data, computer vision, and the like. Michael Jordan: Well, on all academic topics there is a lot of misinformation. The media is trying to do its best to find topics that people are going to read about. Sometimes those go beyond where the achievements actually are.


Machine-Learning Maestro Michael Jordan on the Delusions of Big Data and Other Huge Engineering Efforts

#artificialintelligence

The overeager adoption of big data is likely to result in catastrophes of analysis comparable to a national epidemic of collapsing bridges. Hardware designers creating chips based on the human brain are engaged in a faith-based undertaking likely to prove a fool's errand. Despite recent claims to the contrary, we are no further along with computer vision than we were with physics when Isaac Newton sat under his apple tree. Those may sound like the Luddite ravings of a crackpot who breached security at an IEEE conference. In fact, the opinions belong to IEEE Fellow Michael I. Jordan, Pehong Chen Distinguished Professor at the University of California, Berkeley. Jordan is one of the world's most respected authorities on machine learning and an astute observer of the field. His CV would require its own massive database, and his standing in the field is such that he was chosen to write the introduction to the 2013 National Research Council report "Frontiers in Massive Data Analysis." San Francisco writer Lee Gomes interviewed him for IEEE Spectrum on 3 October 2014. IEEE Spectrum: I infer from your writing that you believe there's a lot of misinformation out there about deep learning, big data, computer vision, and the like. Michael Jordan: Well, on all academic topics there is a lot of misinformation. The media is trying to do its best to find topics that people are going to read about. Sometimes those go beyond where the achievements actually are.