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Gary Marcus

Published podcast speaker

Claims
39
Episodes
1
Shows
1
Named items
2

Books, apps, and tools

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book / built

The Algebraic Mind

“I see a set of problems that a cognitive creature must solve, many of which I wrote in my 2,001 book, The Algebraic Mind.”

Machine Learning Street Talk · 24 Jun 2025

Evidence receipt · Source ↗

book / built

The Future of the Brain

“And it was in a book that I wrote called The Future of the Brain, which I guess we wrote in 02/2015.”

Machine Learning Street Talk · 24 Jun 2025

Evidence receipt · Source ↗

Claim ledger

What Gary said.

39 transcript-backed records

03 / belief

Think that's exactly what people like Sam and Dario are now hinting that they're gonna be able to do soon. I'm not really buying those claims, but I think that's what they wanna do now.

“Think that's exactly what people like Sam and Dario are now hinting that they're gonna be able to do soon. I'm not really buying those claims, but I think that's what they wanna do now.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

04 / belief

I hadn't played this variation either before, but it was obvious what to do. So it failed to identify what 3 in a row was, which I would say goes to a conceptual weakness like you should have had enough data to understand what 3 in a row was.

“I hadn't played this variation either before, but it was obvious what to do. So it failed to identify what 3 in a row was, which I would say goes to a conceptual weakness like you should have had enough data to understand what 3 in a row was.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

05 / commitment

You suggested 1 red line, there are others. So we could decide as a society there are certain red lines, maybe recursive self improvement might be a reasonable 1 to consider, that we could say we won't cross any of the red lines.

“You suggested 1 red line, there are others. So we could decide as a society there are certain red lines, maybe recursive self improvement might be a reasonable 1 to consider, that we could say we won't cross any of the red lines.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

10 / belief

I mean, here's way to put it, is the AGI that I think we're afraid might be unconstrained or whatever, there really shouldn't be a lot of edge cases like that.

“I mean, here's way to put it, is the AGI that I think we're afraid might be unconstrained or whatever, there really shouldn't be a lot of edge cases like that.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

11 / belief

I think we are completely agreed that we're not doing a great job on the alignment problem and that we need to do much better and that there's a temporal dimension to that as you were just saying, which is like, you know, it's not great for humanity if we solve that problem in 200 years and we we have AGI or ASI, you know, in the next decade or 2.

“I think we are completely agreed that we're not doing a great job on the alignment problem and that we need to do much better and that there's a temporal dimension to that as you were just saying, which is like, you know, it's not great for humanity if we solve that problem in 200 years and we we have AGI or ASI, you know, in the next decade or 2.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

13 / belief

There's some differentiation in how people do their RL and what their data sets are, but I think there's not so much value in transparency until somebody has something that really is unique that they think other people aren't going to just reconstruct very rapidly.

“There's some differentiation in how people do their RL and what their data sets are, but I think there's not so much value in transparency until somebody has something that really is unique that they think other people aren't going to just reconstruct very rapidly.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

17 / uncertainty

I was told, I don't know if it's true, that that people in OpenAI actually look on social media for example, including mine, and, you know, people patch them up.

“I was told, I don't know if it's true, that that people in OpenAI actually look on social media for example, including mine, and, you know, people patch them up.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

21 / belief

If you can have the neural networks reliably call the tools that they want or that they should be calling relative to the problem, I should say, then you're golden. I think empirically it is a bit hard to get the tools to work reliably.

“If you can have the neural networks reliably call the tools that they want or that they should be calling relative to the problem, I should say, then you're golden. I think empirically it is a bit hard to get the tools to work reliably.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

23 / belief

I think the 3 of us are maybe not known for agreeing on everything, but we actually have a lot of shared values around that, and I'm looking forward to the conversation.

“I think the 3 of us are maybe not known for agreeing on everything, but we actually have a lot of shared values around that, and I'm looking forward to the conversation.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

24 / belief

I think that the level of intelligence that you attribute to the machines towards the end of the essay I remember some of that actually happens after the year 2027.

“I think that the level of intelligence that you attribute to the machines towards the end of the essay I remember some of that actually happens after the year 2027.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

27 / belief

You can argue about that and and, you know, I I would say that like the weakest AGI would be it's as good as Joe Sixpack who's really not very good at reasoning, has is full of confirmation bias, has not gone to graduate school, doesn't have, you know, critical reasoning.

“You can argue about that and and, you know, I I would say that like the weakest AGI would be it's as good as Joe Sixpack who's really not very good at reasoning, has is full of confirmation bias, has not gone to graduate school, doesn't have, you know, critical reasoning.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

28 / belief

Like I believe in my political party and so when my political party does dumb thing then I go and try to, you know, come up with a rationale for it.

“Like I believe in my political party and so when my political party does dumb thing then I go and try to, you know, come up with a rationale for it.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

30 / commitment

I am sure that I will be able to come up with variations on chess, that are not orthodox variations, but maybe there's some already known.

“I am sure that I will be able to come up with variations on chess, that are not orthodox variations, but maybe there's some already known.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

33 / prediction

I mean, like, if you're worried about superintelligence, then you might think if we move even towards AGI, which presumably is closer in time, that that's a bad idea because we won't be able to stop the superintelligence.

“I mean, like, if you're worried about superintelligence, then you might think if we move even towards AGI, which presumably is closer in time, that that's a bad idea because we won't be able to stop the superintelligence.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

34 / evaluation

We have slightly different ideas about world models. But he would say, I don't think we're close because we don't really have world models and neither of us I think are satisfied with the current thing that some people call reasoning but neither of us think is robust enough.

“We have slightly different ideas about world models. But he would say, I don't think we're close because we don't really have world models and neither of us I think are satisfied with the current thing that some people call reasoning but neither of us think is robust enough.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

35 / prediction

I think we're making some bad assumptions, but it's hard to predict when people will move past an EDA fix, which is where I think we are now.

“I think we're making some bad assumptions, but it's hard to predict when people will move past an EDA fix, which is where I think we are now.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

36 / evaluation

On Tower of Hanoi, Herb Simon solved it in 1957 with a classical technique that generalizes to arbitrary length whereas the LLMs do not generalize to arbitrary length and face problems. And so I could go through more but the gist of it is I don't see the qualitative problems that I think need to be solved.

“On Tower of Hanoi, Herb Simon solved it in 1957 with a classical technique that generalizes to arbitrary length whereas the LLMs do not generalize to arbitrary length and face problems. And so I could go through more but the gist of it is I don't see the qualitative problems that I think need to be solved.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

37 / prediction

Then we have the whole I don't know if we have time to go into it, but maybe we will, maybe won't the mechanisms of open sourcing or at least open weight models, which means that essentially anybody can get in this game to some degree.

“Then we have the whole I don't know if we have time to go into it, but maybe we will, maybe won't the mechanisms of open sourcing or at least open weight models, which means that essentially anybody can get in this game to some degree.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

38 / evaluation

It works better for things like math where you can verify that the the augmented data are better. And so I think we're already running against that, kind of like bottleneck on 1 of the, let's say, raw resources that go in at least into the current approaches.

“It works better for things like math where you can verify that the the augmented data are better. And so I think we're already running against that, kind of like bottleneck on 1 of the, let's say, raw resources that go in at least into the current approaches.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk

39 / evaluation

I take I take even, like, don't make illegal moves in chess to be a form of the alignment problem, like a very simple microcosm of the alignment problem, and they're still struggling with that.

“I take I take even, like, don't make illegal moves in chess to be a form of the alignment problem, like a very simple microcosm of the alignment problem, and they're still struggling with that.”
Speaker
Gary Marcus
Publisher
Machine Learning Street Talk
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