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Richard Feynman: Can Machines Think?

Lex Clips

1.6M subscribers • 3 videos on Hallway

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  • Recommended by 1 person: 1 on Hacker News.
  • Presented by Richard Feynman, physicist
  • May be out of date. Uploaded 6 years ago, in an area where tools change fast.
  • An opinion. It argues one side of a question engineers disagree on.

Beginner. No background in the topic needed.

2.5M views6 years ago1 recommendation

AI and machine learningComputer scienceComputation and complexityHistory of computingPeople who shaped computing

Richard Feynman discusses the definition of machine intelligence and the limits of what computers can do in this 1985 Q&A.

This is a Q&A excerpt on the topic of AI from a lecture by Richard Feynman from September 26th, 1985. This is a clip on the Lex Clips channel that I mostly use to post video clips from the Artificial Intelligence podcast, but occasionally I post favorite clips from lectures given by others. Hope you find these interesting, thought-provoking, and inspiring. If you do, please subscribe, click bell icon, and share! Full lecture: youtube.com/watch?v=EKWGGDXe5MA Lex Clips channel: youtube.com/lexclips Lex Fridman channel: youtube.com/lexfridman Artificial Intelligence podcast website: lexfridman.com/ai Apple Podcasts: apple.co/2lwqZIr Spotify: open.spotify.com/show/2MAi0BvDc6GTFvKFPXnkCL RSS: lexfridman.com/category/ai/feed/ Connect with on social media: - Twitter: twitter.com/lexfridman - LinkedIn: linkedin.com/in/lexfridman - Facebook: facebook.com/lexfridman - Instagram: instagram.com/lexfridman - Medium: medium.com/@lexfridman - Support on Patreon: patreon.com/lexfridman

Why it's here

1 person recommends this

What people say. Engineers share this clip for Feynman's timeless, philosophical perspective on artificial intelligence.

EGregon Hacker News • Recommends

On “When machines could see you”

Relevant — decades earlier, Righard Feynman discussing AI like a boss. He discusses exactly the problems being solved in the article with the Haar approach, but from his time. He mentioned Lenat, who was the OG and who the “LeNet” by Yann LeCun was named after probably (it is mentioned in the article). link to this video
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qiskiton Hacker News • Mentions

On “What’s a fire and why does it burn? (2016)”

Here is feynman on AI: link to this video Feynman turned his focus to computing ( AI, heuristics, quantum computing ) later on his life.
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mutant_glofishon Hacker News • Mentions

On “Do LLMs Reason?”

Do submarines swim? 1 Do cars run, like a cheetah does? 2 1: link 2: link to this video (Richard Feynman: Can Machines Think?)
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SilverSlashon Hacker News • Mentions

On “Cyc: History's Forgotten AI Project”

I first heard about Cyc's creator Douglas Lenat a few months back when I watched an old talk by Richard Feynman. link to this video
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saithoundon Hacker News • Mentions

On “Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]”

Feynman was a well-known proponent of AI and neural networks 1. He even gave popular lectures on the subject 2. He also claimed that replicating animal-like visual recognition abilities in machines would be Nobel-worthy; deep learning was certainoy a breakthrough in that. 1 link 2 link to this video
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sobellianon Hacker News • Mentions

On “Gödel's theorem debunks the most important AI myth – Roger Penrose [video]”

…preciation of the aesthetic... then it gets harder and harder for the computer to do it because the human beings have a tendency to try to make sure that they can do something that no machine can do. Somehow it doesn't bother them anymore, it must have bothered them in earlier times, that machines are stronger physically than they are... - Feynman link to this video…
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perching_aixon Hacker News • Mentions

On “AniSora: Open-source anime video generation model”

Sure, but intent is a very fickle thing. Consider zero and single click deployments in IT operations. With single click deployments, you need to have everything automated, but the go sign is still given by a human. With zero click, you'll have a deployment policy instead - the human decision is now out of the critical path completely, and only plays part during the authoring and later editing of said policy. And you can also then generate those policies, and so on. Same can be applied to AI. You can have canned prompts that you keep refining to encode your intent and preferences, then you just use them with a single click. But you can also build a harness that generates prompts and continuou…
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EGregon Hacker News • Mentions

On “I don't think AGI is right around the corner”

Well, you have to define what you mean by "intelligence". I think it's just not been enough time, we can take the current LLM technology and just put it in a pipeline that includes 24/7 checking work and building up knowledge bases. A lot of the stuff that you think is "new and original ideas" are just like prompting an LLM to "come up with 20 original variations" or "20 original ways to combine" some building blocks it already has been trained on or have been added into its context. If you do this frequently enough, and make sure to run acceptance tests (e.g. unit testing or whatever is in your domain) then you can really get quite far. In fact, you can generate the tests themselves as well…
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lostmsuon Hacker News • Mentions

On “"ChatGPT said this" Is Lazy”

It hinges assuming that ChatGPT does not thinking, which is clearly false. Hell, Feynman said as much in 1985. link to this video
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EGregon Hacker News • Mentions

On “Blowing ChatGPT's mind. Is this just sycophancy? Or a realistic assessment?”

Nah. I don’t “feel the AGI”. I think the AGI is a silly quest, just like having a plane flap its wings. Feynman had it right in the 80s: link to this video I think the future is lots of incremental improvements that get replicated everywhere and humans outclassed in nearly every field, where they stop relying on each other. As far as LLMs yes I think they are the best placed to know if some code or invention is novel, because of their vast training. Can be far better than a patent examiner, if trained on prior art, for instance. What you’re not used to is an LLM being fed stuff that you statistically / heuristically would expect to be average but is in fact the polished result of years of work. The LLM…
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