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Machine Learning Street Talk / episode intelligence

Karl Friston - Why Intelligence Can't Get Too Large (Goldilocks principle)

10 Sept 2025 14 published claims 3 attributable people

Speakers in the public record

Claim mix

evaluation 4prediction 4belief 3disagreement 1recommendation 1commitment 1

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14 published records

03 / 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

05 / 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

06 / 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

07 / 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

08 / evaluation

I've never been able to completely pin you down, professor Friston, because there have been so many interpretations of the free energy principle that that lean internalist and externalist and even, the the hybrid version, which Maxwell also wrote a paper about.

“I've never been able to completely pin you down, professor Friston, because there have been so many interpretations of the free energy principle that that lean internalist and externalist and even, the the hybrid version, which Maxwell also wrote a paper about.”
Speaker
Tim Scarfe
Publisher
Machine Learning Street Talk

09 / 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

10 / 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

11 / 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

12 / 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

13 / 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

14 / 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
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