“If you haven't seen the video it's remarkable”
DeepMind Atari player demo, with tiny source code
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The Deepmind Atari Player is only 22KB of source code: link If you haven't seen the video it's remarkable: this video
Deepmind artificial intelligence @ FDOT14
288K views · Apr 19, 2014 · 4:41 · 2 HN recommenders · 6 mentions · discussed 2014–2016
A short smartphone-recorded clip from a 2014 event in Paris where DeepMind CEO Demis Hassabis presents an AI learning to play old Atari games. The system learns from only the video signal and the score. Audio quality is poor.
Why Hacker News points people here: HN commenters use it as the canonical demo of deep reinforcement learning, noting that watching it teaches more than an article does.
“you learn more about the tech from a youtube video than from an article”HN comment, 2014
What Hacker News said 6
“you learn more about the tech from a youtube video than from an article”
DeepMind demo learning games from only the video signal
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Thanks for the correction. The "arbitrary" qualifier is not in TFA, but (as, indeed, you said) that's the point of the demo, e.g.: this video Note that they're using just the video signal from the game as input. It's really a sad comment on the state of reporting at MIT Tech Review that you learn more about the tech from a youtube video than from an article. (My complaint is not with the DeepMind people, it's with the article, which should put the work in context.)
“A cool reinforcement learning demo is the DeepMind Atari video from last year[4]”
DeepMind Atari reinforcement learning demo
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In psychology, this is called "Reinforcement"[1] and that goes back to Skinner (1938) and Thorndike (1911). In AI research its called "Reinforcement learning"[2]. One of the earliest papers relating reinforcement learning to AI was “Theory of Neural-Analog Reinforcement Systems”[3] by Minsky, 1954 A cool reinforcement learning demo is the DeepMind Atari video from last year[4] [1] link [2] link [3] link [4] this video (this is awesome)
DeepMind demo as serious AI research example
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Creating a GAI which can learn how to act human, on its own, in virtual worlds and in robots with realistic bodies isn't serious research? this video
“The Deepmind demo [1] and the recent robotics work at Berkeley[2] are good examples.”
Example of impressive deep reinforcement learning progress
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I was also under the misapprehension that deep learning is just about classification, but that isn't true. Yes, reinforcement learning is the path to general intelligence, and the deep learning community is showing impressive progress on that front as well. The Deepmind demo [1] and the recent robotics work at Berkeley[2] are good examples. Thanks for the link to Stan Franklin's work. I'm glad to hear there is work to integrate the two approaches. [1] this video [2] link
“Deepmind's Atari player is based on deep reinforcement learning, where increasing the score represents a reward”
DeepMind Atari player uses score as reward
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AGI is the idea of creating general intelligence. Which almost certainly requires some reinforcement learning (the ways dogs and humans learn, by having a goal and an internal reward system). Deepmind's Atari player is based on deep reinforcement learning, where increasing the score represents a reward: this video I used to believe the moving goalpost idea, that AI is anything that isn't yet possible. I now disagree. I saved myself a lot of energy by avoiding entirely the question "what counts as AI?" by switching to the question, "what counts as AGI?" which is a term with a clearer threshold: link