Face Recognition applied at scale in China

The Chinese government is not the only entity that has access to millions of faces + identifying information. So do Google, Facebook, Instagram, and anyone who has scraped information from similar social networks (e.g., US security services, hackers, etc.). In light of such ML capabilities it seems clear that anti-ship ballistic missiles can easily target …

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Rise of the Machines: Survey of AI Researchers

These predictions are from a recent survey of AI/ML researchers. See SSC and also here for more discussion of the results. When Will AI Exceed Human Performance? Evidence from AI Experts Katja Grace, John Salvatier, Allan Dafoe, Baobao Zhang, Owain Evans Advances in artificial intelligence (AI) will transform modern life by reshaping transportation, health, science, …

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Walter Pitts and Neural Nets

Pitts is one of the least studied geniuses of the early information age. See also Wikipedia, Nautil.us. Cabinet Magazine: There are no biographies of Walter Pitts, and any honest discussion of him resists conventional biography. Pitts was among the original participants in the mid-century cybernetics conferences, though he began his association with that group of …

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AlphaGo (BetaGo?) Returns

Rumors over the summer suggested that AlphaGo had some serious problems that needed to be fixed — i.e., whole lines of play that it pursued poorly, despite its thrashing of one of the world’s top players in a highly publicized match. But tuning a neural net is trickier than tuning, for example, an expert system …

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Toward A Geometry of Thought

Apologies for the blogging hiatus — I’m in California now for the holidays :-) In case you are looking for something interesting to read, I can share what I have been thinking about lately. In Thought vectors and the dimensionality of the space of concepts (a post from last week) I discussed the dimensionality of the space of …

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AI, Westworld, and Electric Sheep

AI, Westworld, and Electric Sheep I’m holding off on this in favor of a big binge watch. Certain AI-related themes have been treated again and again in movies ranging from Blade Runner to the recent Ex Machina (see also this episode of Black Mirror, with Jon Hamm). These artistic explorations help ordinary people think through …

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Theory, Money, and Learning

After 25+ years in theoretical physics research, the pattern has become familiar to me. Talented postdoc has difficulty finding a permanent position (professorship), and ends up leaving the field for finance or Silicon Valley. The final phase of the physics career entails study of entirely new subjects, such as finance theory or machine learning, and developing …

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Geoff Hinton on Deep Learning

This is a recent, and fairly non-technical, introduction to Deep Learning by Geoff Hinton. In the most interesting part of the talk (@25 min; see arxiv:1409.3215 and arxiv:1506.00019) he describes extracting “thought vectors” or semantic meaning relationships from plain text. This involves a deep net, human text, and resulting vectors of weights. The slide below summarizes some …

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DeepMind and Demis Hassabis

Recent profile in the Guardian; 15 facts about Hassabis. The mastery of Atari games through reinforcement learning deep neural nets is described here (Nature). See also Deep Neural Nets and Go: AlphaGo beats European champion. Guardian: … “We’re really lucky,” says Hassabis, who compares his company to the Apollo programme and Manhattan Project for both …

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Who owns the future?

NewStatesman: Who owns the future? How the prophets of Silicon Valley took control In an era when politics is bereft of grand visions, bioengineers and Silicon Valley tech geeks are claiming the mantle of leadership and prophecy. But what do they want and where are they leading us? … The 20th century was shaped by …

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Contemplating the Future

A great profile of Nick Bostrom in the New Yorker. I often run into Nick at SciFoo and other similar meetings. When Nick is around I know there’s a much better chance the discussion will stay on a highbrow, constructive track. It’s surprising how often, even at these heavily screened elitist meetings, precious time gets …

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Deep Learning in Nature

When I travel I often carry a stack of issues of Nature and Science to read (and then discard) on the plane.The article below is a nice review of the current state of the art in deep neural networks. See earlier posts Neural Networks and Deep Learning 1 and 2, and Back to the Deep. …

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Back to the deep

The Chronicle has a nice profile of Geoffrey Hinton, which details some of the history behind neural nets and deep learning. See also Neural networks and deep learning and its sequel. The recent flourishing of deep neural nets is not primarily due to theoretical advances, but rather the appearance of GPUs and large training data …

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Neural Networks and Deep Learning 2

Inspired by the topics discussed in this earlier post, I’ve been reading Michael Nielsen’s online book on neural nets and deep learning. I particularly liked the subsection quoted below. For people who think deep learning is anything close to a solved problem, or anticipate a near term, quick take-off to the Singularity, I suggest they …

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The Mystery of Go

Nice article on the progress of computer Go. See also The Laskers and the Go master: “While the baroque rules of Chess could only have been created by humans, the rules of Go are so elegant, organic, and rigorously logical that if intelligent life forms exist elsewhere in the universe, they almost certainly play Go.” …

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Another species, an evolution beyond man

  Readers might be interested in this interview I did, which is on the MIRI (Machine Intelligence Research Institute, in Berkeley) website. Some excerpts below. … I think there is good evidence that existing genetic variants in the human population (i.e., alleles affecting intelligence that are found today in the collective world population, but not …

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