Richard Feynman: Can Machines Think?

What Hacker News said

Recommends EGreg · 2024-10 · 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). [this video]

Cites qiskit · 2022-03 · on “What’s a fire and why does it burn? (2016)”

Here is feynman on AI: [this video] Feynman turned his focus to computing ( AI, heuristics, quantum computing ) later on his life.

Cites mutant_glofish · 2023-07 · on “Do LLMs Reason?”

Do submarines swim? [1] Do cars run, like a cheetah does? [2] [1]: [LINK] [2]: [this video] (Richard Feynman: Can Machines Think?)

Cites SilverSlash · 2024-04 · 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. [this video]

Cites saithound · 2024-10 · 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] [this video]

Cites sobellian · 2025-03 · on “Gödel's theorem debunks the most important AI myth – Roger Penrose [video]”

> It's very difficult to find some way of defining rather precisely something we can do that we can say a computer will never be able to do. There are some things that people make up that say that, "While it's doing it, will it feel good?" or, "While it's doing it, will it understand what it's doing?" or some other abstraction. I rather feel that these are things like, "While it's doing it, will it be able to scratch the lice out of it's hair?" No, it hasn't got any hair nor lice to scratch from it, okay? > You've got to be careful when you say what the human does, if you add to the actual result of his effort some other things that you like, the appreciation of the aesthetic... then it gets

Cites perching_aix · 2025-05 · 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

Cites EGreg · 2025-07 · 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