Robots taking our jobs

The figures below are from the recent paper Robots and Jobs: Evidence from US Labor Markets, by Acemoglu and Restrepo. VoxEU discussion: … Estimates suggest that an extra robot per 1000 workers reduces the employment to population ratio by 0.18-0.34 percentage points and wages by 0.25-0.5%. This effect is distinct from the impacts of imports, …

More

Don’t Touch the Computer

Under what circumstances should humans override algorithms? From what I have read I doubt that a hybrid team of human + AlphGo would perform much better than AlphaGo itself. Perhaps worse, depending on the epistemic sophistication and self-awareness of the human. In hybrid chess it seems that the ELO score of the human partner is …

More

Super-human Relational Reasoning (DeepMind)

These neural nets reached super-human (better than an average human) performance on tasks requiring relational reasoning. See the short video for examples. A simple neural network module for relational reasoning https://arxiv.org/abs/1706.01427 Adam Santoro, David Raposo, David G.T. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, Timothy Lillicrap (Submitted on 5 Jun 2017) Relational reasoning is a …

More

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 …

More

Yann LeCun on Unsupervised Learning

This is a recent Yann LeCun talk at CMU. Toward the end he discusses recent breakthroughs using GANs (Generative Adversarial Networks, see also Ian Goodfellow here and here). LeCun tells an anecdote about the discovery of backpropagation. The first implementation of the algorithm didn’t work, probably because of a bug in the program. But they convinced …

More

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 …

More

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 …

More

Moore’s Law and AI

By now you’ve probably heard that Moore’s Law is really dead. So dead that the semiconductor industry roadmap for keeping it on track has more or less been abandoned: see, e.g., here, here or here. (Reported on this blog 2 years ago!) What I have not yet seen discussed is how a significantly reduced rate …

More

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 …

More

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. …

More

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 …

More

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 …

More

Neural Networks and Deep Learning

One of the SCI FOO sessions I enjoyed the most this year was a discussion of deep learning by AI researcher Juergen Schmidhuber. For an overview of recent progress, see this recent paper. Also of interest: Michael Nielsen’s pedagogical book project. An application which especially caught my attention is described by Schmidhuber here: Many traditional methods …

More

Minds and Machines

HLMI = ‘high–level machine intelligence’ = one that can carry out most human professions at least as well as a typical human. I’m more pessimistic than the average researcher in the poll. My 95 percent confidence interval has earliest HLMI about 50 years from now, putting me at ~ 80-90th percentile in this group as …

More

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.” …

More

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 …

More