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The meeting of the minds that launched AI

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Re: The meeting of the minds that launched AI

#11
post #7
post #4

Other than Minsky, I don’t think others (who are nevertheless scientists in their respective fields) are considered to have made significant contributions to modern machine learning or AI. McCarthy’s work around this topic culminated in LISP, leading to Emacs, a text editor! From that period, Rosenblatt’s work was instrumental to modern AI.

Claiming that the creator of LISP did not have a significant impact on AI is not a defensible position.

The story goes as, John McCarthy was applying for an assistant professorship position at MIT. MIT told him, but we have here Norbert Wiener who was a renowned mathematician at the time and had published cybernetics some time ago, in which he talks about agents interacting with the environment and feedback control, sort of modern computation-based AI. McCarthy changed the name from cybernetics to AI, and focused on symbolic systems and logic. The approach was generally not successful.

Some people consider that the logic-based approach to AI pioneered in this conference contributed to an (what we now call) AI winter. People like John Pierce of Bell Labs, a very influential figure in government, defunded research in computation-based AI such as for speech recognition (he wrote articles, saying, basically, researchers pursuing these techniques are charlatans).

There is no major algorithm or idea in undergrad machine learning textbooks named after these people. There are other people from that era.

Re: The meeting of the minds that launched AI

#12
post #2

My father and his friends were academic computer scientists working on AI back in the 60s. I don't know that there's a straightforward path between what they were doing and the popular LLMs today, but I do applaud more stories on what old school comp sci researchers were up to.

There's some value in putting a flag in the ground. Even if most of those people there were in the symbolic camp, a lot of their critiques of neural networks as they existed were well-founded and were really only proved obviously _wrong_ after many many rounds of moore's law.

The criticism from the beginning was of a fundamental theoretical nature, and died at the 90's when people proved and demonstrated that neural networks were powerful enough to run any kind of computation.

In fact, I don't recall people criticizing neural networks from being too small to be useful. Ever. There was a lot of disagreement between wide and deep network proponents, that deep won by demonstration, but "how large a network we need to handle X" was always more of a question than a "see, we'll never get there". (Even more because the "we will never get there" is obviously false, since the thing practically no limit on scaling.)

Re: The meeting of the minds that launched AI

#13
My favourite detail about that 1956 meeting is this extract from the conference proposal:

> An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.

I think this may be one of the most over-ambitious software estimates of all time.

The whole proposal is on https://en.wikipedia.org/wiki/Dartmouth_workshop

Re: The meeting of the minds that launched AI

#14
post #8
post #7

Earlier quoted context omitted.

Claiming that the creator of LISP did not have a significant impact on AI is not a defensible position.

People forget for how long Lisp had an impact on AI, even outside GOFAI techniques; LeCun's early neural networks were written in Lisp: https://leon.bottou.org/publications/pdf/sn-1988.pdf

I don’t know - there’s real impact and then there’s inconsequential path dependency. This feels like the latter. The networks turned out to be valuable but LISP did not.

Re: The meeting of the minds that launched AI

#16
post #2

My father and his friends were academic computer scientists working on AI back in the 60s. I don't know that there's a straightforward path between what they were doing and the popular LLMs today, but I do applaud more stories on what old school comp sci researchers were up to.

LLMs of today display amazing abductive abilities but are limited in inductive and deductive abilities, as well as other optimization techniques of classical AI and algorithms. These abductive abilities are unique and exciting because we’ve typically done really poorly with ambiguous and complex semantic spaces like this. However I think the excitement has obscured the fact it’s just a piece of a larger machine. Why do we care that LLMs are mediocre chess players when we have machine models using more traditional techniques that are the best chess players on earth? Why do we care they fail at deductive reasoning tests? At mathematical calculations? Those are really well understood areas of computing. Somehow people have fixated on the things we’ve already done that this new technique fails at, but ignore the abilities LLMs and other generative models demonstrate we’ve never achieved before. At the same time the other camp only sees generative AI as the silver bullet tool to end all other tools. Neither is correct.

Re: The meeting of the minds that launched AI

#18

Earlier quoted context omitted.

There's some value in putting a flag in the ground. Even if most of those people there were in the symbolic camp, a lot of their critiques of neural networks as they existed were well-founded and were really only proved obviously _wrong_ after many many rounds of moore's law.

The criticism from the beginning was of a fundamental theoretical nature, and died at the 90's when people proved and demonstrated that neural networks were powerful enough to run any kind of computation. In fact, I don't recall people criticizing neural networks from being too small to be useful. Ever. There was a lot of disagreement between wide and deep network proponents, that deep won by demonstration, but "how…

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Re: The meeting of the minds that launched AI

#19

Earlier quoted context omitted.

Solomonoff's https://en.wikipedia.org/wiki/Solomonoff%27s_theory_of_induc... is about as basic to the theory of intelligent agents as anything gets. (He's in the pic and I'd guess this article was by a relative.)

If I was an intelligent agent, I would prefer to be based on a theory that was computable without time travel, which this one isn't.

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Re: The meeting of the minds that launched AI

#20
post #11
post #7

Earlier quoted context omitted.

Claiming that the creator of LISP did not have a significant impact on AI is not a defensible position.

The story goes as, John McCarthy was applying for an assistant professorship position at MIT. MIT told him, but we have here Norbert Wiener who was a renowned mathematician at the time and had published cybernetics some time ago, in which he talks about agents interacting with the environment and feedback control, sort of modern computation-based AI. McCarthy changed the name from cybernetics to AI, and focused on sy…

Makes sense. I heard that some of Wiener’s anti-war sentiment (specifically anti-military-work-during-peacetime) may have contributed… cybernetics really collapsed hard as a discipline, even though I find it very helpful from a systems design perspective. AI has always bothered me as a term because, from a design perspective, the goal should be creating intelligent systems—not necessarily entirely artificial ones.

>There is no major algorithm or idea in undergrad machine learning textbooks named after these people.

Maybe the pandemonium idea from Selfridge?

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