paulsutteron Hacker News • Recommends
On “Ask HN: What are some examples of beautiful software?”
The Deepmind Atari Player is only 22KB of source code: link If you haven't seen the video it's remarkable: link to this video
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Deepmind artificial intelligence @ FDOT14
Elizr
105 subscribers • 1 video on Hallway
- Recommended by 2 people: 2 on Hacker News.
- Presented by Demis Hassabis, co-founder of DeepMind
- May be out of date. Uploaded 12 years ago, in an area where tools change fast.
Beginner. No background in the topic needed.
288K views12 years ago2 recommendations
AI and machine learningGame developmentReinforcement learningNeural networks and deep learningRetro games and consoles
Demis Hassabis demonstrates a DeepMind reinforcement learning system learning to play Atari games using only raw pixels and score as inputs.
/!\ Smartphone bad audio quality Deepmind technology wrecking old Atari games, presented by neuroscientist and game developper Demis Hassabis, Deepmind CEO. (More information on this article : cs.toronto.edu/~vmnih/docs/dqn.pdf) Event held @ First Day of Tomorrow #1, april 2014, ParisWhy it's here
2 people recommend thisWhat people say. Recommended as a landmark demonstration of deep reinforcement learning achieving human-level play on Atari games.
mturmonon Hacker News • Recommends
On “Google's Intelligence Designer”
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.: link to 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.)
paulsutteron Hacker News • Recommends
On “A General Feedback Theory of Human Behavior (1960)”
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 year4 1 link 2 link 3 link 4 link to this video (this is awesome)
u/organic-neural-netin r/compsci • Mentions
On “How a computer learns to play super mario using neural networks”
yes. here's a cool demo using video games. you just have note that there are chess AIs that can beat the average player (or a first-person shooer AI, fighting game, etc) to see that machines can be trained to perform pretty well at some complex tasks and (importantly) generalize what its learned to new situations (e.g. chess AIs don't/cannot store all possible chess games, they de facto have to make decisions in novel contexts)
generally, i think a lot of this stuff falls under the field of reinforcement learning but i'm no expert so take that with caution
MacsHeadroomon Hacker News • Mentions
On “‘Soft’ Artificial Intelligence Is Suddenly Everywhere”
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? link to this video
paulsutteron Hacker News • Mentions
On “Deep Learning – Review by LeCun, Bengio, and Hinton”
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 Berkeley2 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 link to this video 2 link
paulsutteron Hacker News • Mentions
On “Why 2015 Was a Breakthrough Year in Artificial Intelligence”
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: link to 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