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Keith Duggar

Published podcast speaker

Claims
31
Episodes
6
Shows
1
Named items
0

Claim ledger

What Keith said.

31 transcript-backed records

01 / belief

If if my history serves me correctly, even after the signing of that of that treaty, there were there were countries that still continued, like, and and a couple at least, that maybe or probably developed, you know, nuclear weapons. And I think that the problem with hypothetical, like the hypothetical AI is that it's so powerful.

“If if my history serves me correctly, even after the signing of that of that treaty, there were there were countries that still continued, like, and and a couple at least, that maybe or probably developed, you know, nuclear weapons. And I think that the problem with hypothetical, like the hypothetical AI is that it's so powerful.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

06 / evaluation

I need, like, a very concrete example because I completely agree with you, which is that the symbols we use, the language we use are just simplicity is so fundamental to our ability to, like, reason at higher and higher levels.

“I need, like, a very concrete example because I completely agree with you, which is that the symbols we use, the language we use are just simplicity is so fundamental to our ability to, like, reason at higher and higher levels.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

07 / evaluation

It's like I'm gonna have this shape EIN sum followed by this linearity feeds into this shape followed by so I'm still gonna have to do that kind of, like, you know, structuring of the network, if you will, except now in Tensor Logic. And in my opinion, that's 1 of the biggest limitations right now is these are all just divined cantation structures that people have come up with.

“It's like I'm gonna have this shape EIN sum followed by this linearity feeds into this shape followed by so I'm still gonna have to do that kind of, like, you know, structuring of the network, if you will, except now in Tensor Logic. And in my opinion, that's 1 of the biggest limitations right now is these are all just divined cantation structures that people have come up with.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

09 / evaluation

I'm not sure. But, I mean, you know, the what I experienced is that, you know, having parameters in a model, even if they're very, very small because some you know, I put in some term in the objective function that forced them to be small is not the same thing as actually the simpler model that just didn't have them at all.

“I'm not sure. But, I mean, you know, the what I experienced is that, you know, having parameters in a model, even if they're very, very small because some you know, I put in some term in the objective function that forced them to be small is not the same thing as actually the simpler model that just didn't have them at all.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

10 / belief

You could if you wanted to simulate these kinds of things, you could read the DNA as the code that the priors that specify the structure. And, you know, I think that if if if you think of DNA as prescribing the structure of your generative model or your world model or your factor graph that will be fit for purpose and is learnable.

“You could if you wanted to simulate these kinds of things, you could read the DNA as the code that the priors that specify the structure. And, you know, I think that if if if you think of DNA as prescribing the structure of your generative model or your world model or your factor graph that will be fit for purpose and is learnable.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

12 / evaluation

Oh, naughty. So, yeah, and I think, you know, people like Neil Seth make a very similar point quite earnestly, you know, that intelligence and and consciousness are completely orthogonal, that you're making agency and consciousness are completely orthogonal, and I would agree entirely.

“Oh, naughty. So, yeah, and I think, you know, people like Neil Seth make a very similar point quite earnestly, you know, that intelligence and and consciousness are completely orthogonal, that you're making agency and consciousness are completely orthogonal, and I would agree entirely.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

13 / disagreement

I don't think you can do this on a on a Von Neumann architecture because the the Markov blankets of a Von Neumann architecture where you're reading and writing from memory make it very difficult for the memory to self organize.

“I don't think you can do this on a on a Von Neumann architecture because the the Markov blankets of a Von Neumann architecture where you're reading and writing from memory make it very difficult for the memory to self organize.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

14 / recommendation

You install that cause effect structure into your computer architecture, which is again the argument against von Neumann architectures, which is why 1 might, I think, look to all the processing in memory, neuromorphic photonics, possibly quantum computation, but think that's gone off the boil recently.

“You install that cause effect structure into your computer architecture, which is again the argument against von Neumann architectures, which is why 1 might, I think, look to all the processing in memory, neuromorphic photonics, possibly quantum computation, but think that's gone off the boil recently.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

15 / prediction

At which point, I think you would you would find it very difficult to find something that was intelligent in the sense we're talking about because we have to have this recurrence, this solenoidal aspect in order to revisit the states.

“At which point, I think you would you would find it very difficult to find something that was intelligent in the sense we're talking about because we have to have this recurrence, this solenoidal aspect in order to revisit the states.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

16 / prediction

You mentioned consciousness which you shouldn't really do with me but if we stay here for long enough for more than 5 minutes, we will ultimately become completely entangled.

“You mentioned consciousness which you shouldn't really do with me but if we stay here for long enough for more than 5 minutes, we will ultimately become completely entangled.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

17 / commitment

You know, you you need to have that conditional independence to separate the thing from everything else or the self from from the non self. And everything's fine because the active states are hiding behind the sensory states, so the external states can't influence the active states, so that's tick 1, that's what we need.

“You know, you you need to have that conditional independence to separate the thing from everything else or the self from from the non self. And everything's fine because the active states are hiding behind the sensory states, so the external states can't influence the active states, so that's tick 1, that's what we need.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

18 / evaluation

Being able to communicate the free energy principle in a way that people find a useful and obvious sort of tool or method to apply could have, I think, gone better.

“Being able to communicate the free energy principle in a way that people find a useful and obvious sort of tool or method to apply could have, I think, gone better.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

19 / prediction

I think that there is a Goldilocks regime, means that we can only exist at this scale with, as you say, this sort of yin yang, this admixture of dissipative dynamics and conservative dynamics.

“I think that there is a Goldilocks regime, means that we can only exist at this scale with, as you say, this sort of yin yang, this admixture of dissipative dynamics and conservative dynamics.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

20 / prediction

So what he would talk about there is not the synchronization between the inside and the outside or me and you and everything else like me and you, but entanglement. So the principle of unitarity is just basically well you can read the free energy principle as just the principle of unitarity which just means if we stay here for long enough, for more than 5 minutes, we will ultimately become completely entangled which means classically we will be engaged in a generalized synchrony.

“So what he would talk about there is not the synchronization between the inside and the outside or me and you and everything else like me and you, but entanglement. So the principle of unitarity is just basically well you can read the free energy principle as just the principle of unitarity which just means if we stay here for long enough, for more than 5 minutes, we will ultimately become completely entangled which means classically we will be engaged in a generalized synchrony.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

23 / belief

I mean it's it's brilliant, it's insightful, it's important, It's visually 1 of the most beautiful papers I've seen in a in a long time. And I think even people just looking at this, will get the insight that you're talking about right now, like with Einstein, you know, because I mean, sure, we're not Einstein, but I think anybody who introspects the way they think, the way they think about solving problems, the way they think about a skull, the way they think about an apple, you know, they're gonna find that the images in this paper completely reflect the way we think about the world, the way we model the world.

“I mean it's it's brilliant, it's insightful, it's important, It's visually 1 of the most beautiful papers I've seen in a in a long time. And I think even people just looking at this, will get the insight that you're talking about right now, like with Einstein, you know, because I mean, sure, we're not Einstein, but I think anybody who introspects the way they think, the way they think about solving problems, the way they think about a skull, the way they think about an apple, you know, they're gonna find that the images in this paper completely reflect the way we think about the world, the way we model the world.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

24 / belief

I think if you still found a way to do this kind of evolutionary building up from simpler, you know, mappings, what you would end up doing is there would be there would be kind of an a a simple higher order layer that say took the spiral and chopped it up into 4 quadrants, like nice nice quadrants.

“I think if you still found a way to do this kind of evolutionary building up from simpler, you know, mappings, what you would end up doing is there would be there would be kind of an a a simple higher order layer that say took the spiral and chopped it up into 4 quadrants, like nice nice quadrants.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

25 / belief

I think, you know, your communication of open ended search and and kind of these this take on it has has been sharpened, you know, significantly since like 4 years ago when we talked.

“I think, you know, your communication of open ended search and and kind of these this take on it has has been sharpened, you know, significantly since like 4 years ago when we talked.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

26 / belief

I think there's a a direct or deep connection with, you know, poet like the work, you know, your earlier paper, right, on this kind of increasingly complex curriculum and environment where you start off training in simple cases and make them more and more complex.

“I think there's a a direct or deep connection with, you know, poet like the work, you know, your earlier paper, right, on this kind of increasingly complex curriculum and environment where you start off training in simple cases and make them more and more complex.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

27 / belief

I think about 4 years ago that we interviewed Kenneth the first time and it was eye opening then and and it and, you know, it's it's opened a lot of great open ended exploration for me personally.

“I think about 4 years ago that we interviewed Kenneth the first time and it was eye opening then and and it and, you know, it's it's opened a lot of great open ended exploration for me personally.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk

29 / evaluation

Like not butterflies, dragonflies. And and therein is the crux of the problem because we did this open ended cool thing and I mean part of the, let's say, downside of an open ended search is you don't know where you're gonna end up.

“Like not butterflies, dragonflies. And and therein is the crux of the problem because we did this open ended cool thing and I mean part of the, let's say, downside of an open ended search is you don't know where you're gonna end up.”
Speaker
Keith Duggar
Publisher
Machine Learning Street Talk
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