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Tim Scarfe

Host · Machine Learning Street Talk

Claims
168
Episodes
35
Shows
1
Named items
4

Books, apps, and tools

The evidenced stack.

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tool / uses

MATLAB

“during my PhD, I used Mathematica and MATLAB”

Machine Learning Street Talk · 3 Mar 2026

Evidence receipt · Source ↗

tool / uses

Mathematica

“during my PhD, I used Mathematica and MATLAB”

Machine Learning Street Talk · 3 Mar 2026

Evidence receipt · Source ↗

person / likes

Douglas Hofstadter

“Yes. I I love Douglas Hofstadter. So so there's this kind of self modeling and then second order self modeling and third order self modeling which could be applied to other agents and of course, know, in in the real world, we are computationally bounded.”

Machine Learning Street Talk · 21 Oct 2025

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person / likes

Andy

“I'm I'm huge fan of Andy's, big hero of mine. You probably didn't think that they would be so relevant later on in your career.”

Machine Learning Street Talk · 18 Oct 2025

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Claim ledger

What Tim said.

58 transcript-backed records

01 / belief

I mean, yeah, it is a it is a grotesque metaphor that you can take something which I believe is is a physical property of of stuff in the universe And we can create an abstraction that that seems to work reasonably well for abstract domains like playing chess and and and so on.

“I mean, yeah, it is a it is a grotesque metaphor that you can take something which I believe is is a physical property of of stuff in the universe And we can create an abstraction that that seems to work reasonably well for abstract domains like playing chess and and and so on.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

05 / belief

You mentioned transductive as well which is quite interesting because roughly speaking I think of transduction as you're making a prediction about the specific test instance.

“You mentioned transductive as well which is quite interesting because roughly speaking I think of transduction as you're making a prediction about the specific test instance.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

08 / belief

Like, if we actually had some hypothetical real time adaptive divergent Claude, you know, would it be much better than the Claude that we already have? And, it's also related to the to the work that you guys do, because, the process of intelligence, in my view, is the creation of these coarse grainings, skills.

“Like, if we actually had some hypothetical real time adaptive divergent Claude, you know, would it be much better than the Claude that we already have? And, it's also related to the to the work that you guys do, because, the process of intelligence, in my view, is the creation of these coarse grainings, skills.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

14 / belief

I think that you subscribe to the slightly different idea that that we need to be far more open ended and we need to be using evolutionary algorithms and so on.

“I think that you subscribe to the slightly different idea that that we need to be far more open ended and we need to be using evolutionary algorithms and so on.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

15 / belief

Yeah. Because the discriminative learning rate thing is interesting because I I think the received wisdom at the time was when you fine tune a model, if the learning rate is too high, you kind of blow out the representations.

“Yeah. Because the discriminative learning rate thing is interesting because I I think the received wisdom at the time was when you fine tune a model, if the learning rate is too high, you kind of blow out the representations.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

17 / belief

I I think there's a dichotomy though between continual learning, which is when we want to keep training the thing but maintain generality, versus fine tuning a thing to do something specific.

“I I think there's a dichotomy though between continual learning, which is when we want to keep training the thing but maintain generality, versus fine tuning a thing to do something specific.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

19 / belief

You know, I'm so torn on this because I agree with you. And I'm also skeptical of people who say that organizations, they they they converge onto ways of doing things, they no longer need to evolve.

“You know, I'm so torn on this because I agree with you. And I'm also skeptical of people who say that organizations, they they they converge onto ways of doing things, they no longer need to evolve.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

21 / belief

I look up to her very much and certainly thinking back on many of the episodes we've done in 2025, I can see her influence in the questions I ask and how I think about things.

“I look up to her very much and certainly thinking back on many of the episodes we've done in 2025, I can see her influence in the questions I ask and how I think about things.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

24 / belief

Some of the programs which are learned are just really complicated. They had examples of like I think drawing towers and drawing graphs and stuff like that.

“Some of the programs which are learned are just really complicated. They had examples of like I think drawing towers and drawing graphs and stuff like that.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

25 / belief

We just kind of, generate these post hoc confabulations, and then we explain our behavior, and we kind of pretend that that was what we wanted to do, that we had beliefs and so on, but we just kind of make it up as as we go along using this kind of active inference. So I guess the the the question is, like, we do think of ourselves as being like, even though we are emotional and subjective and, like, you know, like, we believe in religion and lots of things that that we presumably made up, but but we have Wikipedia.

“We just kind of, generate these post hoc confabulations, and then we explain our behavior, and we kind of pretend that that was what we wanted to do, that we had beliefs and so on, but we just kind of make it up as as we go along using this kind of active inference. So I guess the the the question is, like, we do think of ourselves as being like, even though we are emotional and subjective and, like, you know, like, we believe in religion and lots of things that that we presumably made up, but but we have Wikipedia.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

27 / belief

I think I think people conflate the machinations of of language models with how we represent them statistically or or abstractly. Because if you look at lot of papers, they they actually represent it like a probability, you know, like a joint probability distribution.

“I think I think people conflate the machinations of of language models with how we represent them statistically or or abstractly. Because if you look at lot of papers, they they actually represent it like a probability, you know, like a joint probability distribution.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

29 / belief

You need to do things a certain way. And even though it's not technically constraining our brains and how we think, like, live in a very, very constrained and weird world now.

“You need to do things a certain way. And even though it's not technically constraining our brains and how we think, like, live in a very, very constrained and weird world now.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

32 / belief

You had you're talking about Barnes and Noble over there in Seattle, and they they they went up against Jeff Bezos and they said, well, you know, Jeff, we've launched a website and and we think we can do what you do better than they do.

“You had you're talking about Barnes and Noble over there in Seattle, and they they they went up against Jeff Bezos and they said, well, you know, Jeff, we've launched a website and and we think we can do what you do better than they do.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

33 / belief

I think that even though there's this grounding problem, there are many things in the world that can be abstracted and essentialized and we could have this constructive form of understanding, you know, that goes several levels deep.

“I think that even though there's this grounding problem, there are many things in the world that can be abstracted and essentialized and we could have this constructive form of understanding, you know, that goes several levels deep.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

35 / belief

Maybe it just wasn't that hard of a thing to do in the first place. But I think in the case of machine learning, we really need to give credit where it's due here that nobody knew that these superficial statistical regularities have an insane amount of generalization.

“Maybe it just wasn't that hard of a thing to do in the first place. But I think in the case of machine learning, we really need to give credit where it's due here that nobody knew that these superficial statistical regularities have an insane amount of generalization.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

36 / belief

If anything, I think that there is more opportunity now for people to work to fix all of the shit which is generated from language models because it's it's mostly garbage.

“If anything, I think that there is more opportunity now for people to work to fix all of the shit which is generated from language models because it's it's mostly garbage.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

40 / belief

There is a school of thought that our brain works in this way. So we think using, like, the the the symbols and these categories and so on, And then there's and then there's the notion of the universe is a certain way, and we understand the universe with that kind of interface.

“There is a school of thought that our brain works in this way. So we think using, like, the the the symbols and these categories and so on, And then there's and then there's the notion of the universe is a certain way, and we understand the universe with that kind of interface.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

43 / belief

If we learned it constructively, so we, you know, you speak about this in your paper, this complexification, the abstract building blocks, and you can do adaptive computation.

“If we learned it constructively, so we, you know, you speak about this in your paper, this complexification, the abstract building blocks, and you can do adaptive computation.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

48 / belief

We were talking about semantics earlier. So I I think you've done some work basically proving that semantic censorship for language is is impossible and you related it to the halting problem.

“We were talking about semantics earlier. So I I think you've done some work basically proving that semantic censorship for language is is impossible and you related it to the halting problem.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

52 / belief

I think there was a distinction as well that certainly Legg and Hunter, they were very focused on on their simplification of of the model and Occam's razor.

“I think there was a distinction as well that certainly Legg and Hunter, they were very focused on on their simplification of of the model and Occam's razor.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

55 / belief

Mean, first of all, it was really interesting that political and demographic biases would emerge as coherent utility functions. And I I do take umbrage with this word emergence because I think in the emergence literature, there is a little bit more nuance to how machine learning people use the words.

“Mean, first of all, it was really interesting that political and demographic biases would emerge as coherent utility functions. And I I do take umbrage with this word emergence because I think in the emergence literature, there is a little bit more nuance to how machine learning people use the words.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

56 / belief

Another very interesting thing in your paper because when I think about AI risk in general, we we've thought about this a little bit on the show before, is in terms of, stability and destabilization and the relationship between offense and defense.

“Another very interesting thing in your paper because when I think about AI risk in general, we we've thought about this a little bit on the show before, is in terms of, stability and destabilization and the relationship between offense and defense.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

57 / belief

I mean, there's there's a few points here because I guess like what I was, where I was going with this before is, you take y equals x squared, and the reason why we think of it as robust is for any value of y, it kind of does something it does something reasonable.

“I mean, there's there's a few points here because I guess like what I was, where I was going with this before is, you take y equals x squared, and the reason why we think of it as robust is for any value of y, it kind of does something it does something reasonable.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

58 / belief

We could easily discover something that what that wipes YouTube away. So it's about this epistemic gap between what we really want and what we think we want.

“We could easily discover something that what that wipes YouTube away. So it's about this epistemic gap between what we really want and what we think we want.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk
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