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Karl Friston is one of the greatest neuroscientists in history, cited over 245,000 times, known for many influential ideas in brain imaging, neuroscience, and theoretical neurobiology, including the fascinating idea of the free-energy principle for action and perception.

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So you've also formulated a fascinating principle, the free energy principle.

Can we maybe start at the basics and what is the free energy principle?

Well, in fact, the free energy principle inherits a lot from the building of these data analytic approaches to these very high dimensional time series you get from the brain.

So I think it's interesting to acknowledge that.

And in particular, the analysis tools that try to address the other side, which is a functional integration, so the connectivity analysis.

On the 1 hand, but I should also acknowledge it inherits an awful lot from machine learning as well.

So the free energy principle is just a formal statement that the existential imperatives for any system that manages to survive in a changing world can be cast as an inference problem in the sense that you could interpret the probability of existing as the evidence that you exist.

And if you can write down that problem of existence as a statistical problem, then you can use all the maths that has been developed for inference to understand and characterize the ensemble dynamics that must be in play in the service of that inference.

So technically what that means is you can always interpret anything that exists in virtue or being separate from the environment in which it exists as trying to minimize variational free energy.

And if you're from the machine learning community, you will know that as a negative evidence lower bound or a negative elbow, which is the same as saying you're trying to maximize, or it will look as if all your dynamics are trying to maximize the compliment of that, which is the marginal likelihood or the evidence for your own existence.

So that's basically the free energy principle.

But to even take a sort of a small step backwards, you said the existential imperative.

There's a lot of beautiful poetic words here, but to put it crudely, it's a fascinating idea of basically of trying to describe, if you're looking at a blob, how do you know this thing is alive?

And so you can look at the brain, you can look at parts of the brain, or this is just a general principle that applies to almost any system.

That's just a fascinating, sort of philosophically, at every level, question and a methodology to try to answer that question.

So that's a huge endeavor and it's nice that there's at least some, from some perspective, a clean answer.

So maybe can you talk about that optimization view of it?

So what's trying to be minimized and maximized?

A system that's alive, what is it trying to minimize?

But you've assumed that the thing exists in a state that could be living or non-living.

So I may ask you, what licenses you to say that something exists?

So if you drill down onto the definition of things that exist, then they have certain properties if you borrow the maths from non-equilibrium steady-state physics that enable you to interpret their existence in terms of this optimization procedure.

So it's good you introduced the word optimization.

So what the free energy principle in its sort of most ambitious but also most deflationary and simplest says is that if something exists, then it must by the mathematics of non-equilibrium steady state exhibit properties that make it look as if it is optimizing a particular quantity.

And it turns out that particular quantity happens to be exactly the same as the evidence lower bound in machine learning or Bayesian model evidence in Bayesian statistics or, and then I can list a whole other, you know, list of ways of understanding this key quantity which is a bound on surprisal, self-information, if you're in information theory.

There are a number of different perspectives on this quantity.

It's just basically the log probability of being in a particular state.

I'm telling this story as an honest attempt to answer your question and I'm answering it as if I was pretending to be a physicist who was trying to understand the fundaments of non-equilibrium steady state.

And I shouldn't really be doing that because the last time I was taught physics I was in my 20s.

What kind of systems, when you think about the free energy principle, what kind of systems are you imagining?

As a sort of more specific kind of case study.

I'm imagining a range of systems, but at its simplest, a single-celled organism that can be identified from its econics or its environment.

So at its simplest, that's basically what I always imagined in my head.

And you may ask, well, how on earth can you even elaborate questions about the existence of a single drop of oil, for example?

Why doesn't the oil, why doesn't the thing, the interface between the drop of oil that contains an interior and the thing that is not the drop of oil, which is the solvent in which it is immersed, How does that interface persist over time?

Why doesn't the oil just dissolve into solvent?

So what special properties of the exchange between the surface of the oil drop and the external states in which it's immersed.

If you're a physicist, say it would be the heat path.

You know, you've got a physical system, an ensemble again, we're talking about density dynamics, ensemble dynamics, an ensemble of atoms or molecules immersed in the heat path.

But the question is, how did the heat bath get there and why does it not dissolve?

I mean, it's such a fascinating idea of a drop of oil and I guess it would dissolve in water, it wouldn't dissolve in water.

And how do you mathematically describe, I mean it's such a beautiful idea, and also the idea of where does the drop of oil end, and where does it begin?

Right, so I mean, you're asking deep questions, deep in a non-millennial sense here.

But what you can do, So this is the deflationary part of it.

Can I just qualify my answer by saying that normally when I'm asked this question, I answer from the point of view of a psychologist when we talk about predictive processing and predictive coding and the brain as an inference machine?

But you haven't asked me from that perspective.

I'm answering from the point of view of a physicist.

So the question is not so much why, but if it exists, what properties must it display?

So that's the deflationary part of the free energy principle.

The free energy principle does not supply an answer as to why, it's saying, if something exists, then it must display these properties.

That's the sort of thing that's on offer.

And it so happens that these properties it must display are actually intriguing and have this inferential gloss, this sort of self-evidencing gloss that inherits on the fact that the very preservation of the boundary between the oil drop and the not oil drop requires an optimization of a particular function or a functional that defines the presence or the existence of this oil drop, which is why I started with existential imperatives.

It is a necessary condition for existence that this must occur because the boundary basically defines the thing that's existing.

So it is that self-assembly aspect it's that you were hinting at in biology, sometimes known as autopoiesis in computational chemistry with self-assembly.

It's the, what does it look like, sorry, how would you describe things that configure themselves out of nothing?

Where they clearly demarcate themselves from the states or the soup in which they are immersed.

So from the point of view of computational chemistry, for example, you would just understand that as a configuration of a macromolecule to minimize its free energy, its thermodynamic free energy.

It's exactly the same principle that we've been talking about, that thermodynamic free energy is just the negative elbow.

So the very emergence of existence, of structure, of form that can be distinguished from the environment or the thing that is not the thing necessitates the existence of an objective function that it looks as if it is minimizing, it's finding a free energy minima.

And so, just to clarify, I'm trying to wrap my head around, so the free energy principle says that if something exists, these are the properties it should display.

So what that means is we can't just look, we can't just go into a soup and there's no mechanism.

A free energy principle doesn't give us a mechanism to find the things that exist.

Is that what's implying, is being implied that you can kind of use it to reason, to think about like, study a particular system and say, does this exhibit these qualities?

That's an excellent question, but to answer that, I'd have to return to your previous question about what's the difference between living and non-living things.

Yes, well, actually, sorry, so yeah, maybe we can go there.

You kind of drew a line, and forgive me for the stupid questions, but you kind of drew a line between living and existing.

So, things do exist, grains of sand, rocks on the moon, trees, you.

So all of these things can be separated from the environment in which they are immersed and therefore they must at some level be optimizing their free energy.

Taking this sort of model evidence interpretation of this quantity that basically means that self-evidencing.

Another nice little twist of phrase here is that you are your own existence proof, you know, statistically speaking, which I don't think I, I said that, somebody did, but I love that phrase.

I'm gonna have to think about that for a few days.

So the step through to answer your question about what's it good for, we go along the following lines.

First of all, you have to define what it means to exist, which now, as you've rightly pointed out, you have to define what probabilistic properties must the states of something possess so it knows where it finishes.

And then you write that down in terms of statistical independences.

Again, it's not what's connected or what's correlated or what depends upon what, it's what's not correlated and what doesn't depend upon something.

Again, it comes down to the deep structures, not in this instance hierarchical, but the structures that emerge from removing connectivity and dependency.

And in this instance, basically being able to identify the surface of the oil drop from the water in which it is immersed.

And when you do that, you start to realize, well, there are actually 4 kinds of states in any given universe that contains anything.

The things that are internal to the surface, the things that are external to the surface and the surface in and of itself, which is why I use a metaphor, a little single-celled organism that has an interior and exterior, and then the surface of the cell.

And that's mathematically a Markov blanket.

Just to pause, I'm in awe of this concept that there's the stuff outside the surface, stuff inside the surface, and the surface itself, the Markov blanket, it's just the most beautiful kind of notion about trying to explore what it means to exist mathematically.

But it came out of California, so that's.

So anyway, so what, you were just talking about the surface, about the marker plane.

Yeah, so this surface or these blanket states that are the, because they are now defined in relation to these independences and what different states, internal or blanket or external states, which ones can influence each other and which cannot influence each other.

You can now apply standard results that you would find in non-equilibrium physics or steady state or thermodynamics or hydrodynamics, usually out of equilibrium solutions and apply them to this partition.

And what it looks like is if all the normal gradient flows that you would associate with any non-equilibrium system apply in such a way that 2, part of the Markov blanket and the internal states seem to be hill climbing or doing a gradient descent on the same quantity.

And that means that you can now describe the very existence of this oil drop.

You can write down the existence of this oil drop in terms of flows, dynamics, equations of motion, where the blanket states, or part of them, we call them active states and the internal states now seem to be, and must be, trying to look as if they're minimizing the same function, which is a log probability of occupying these states.

Interesting thing is that, what would they be called if you were trying to describe these things?

So what we're talking about are internal states, external states and blanket states.

Now let's carve the blanket states into 2 sensory states and active states.

Operationally it has to be the case that in order for this carving up into different sets of states to exist, The active states, the Markov blanket, cannot be influenced by the external states.

And we already know that the internal states can't be influenced by the external states because the blanket separates them.

Well, it means the active states, the internal states, are now jointly not influenced by external states.

So now you've got a picture of an oil drop that has autonomy.

It has autonomous states in the sense that there must be some parts of the surface of the oil drop that are not influenced by the external states and all the interior.

And together those 2 states endow even a little oil drop with autonomous states that look as if they are optimizing their variational free energy or their negative elbow, their moral evidence.

And that would be an interesting intellectual exercise.

And you could say, you could even go into the realms of panpsychism, that everything that exists is implicitly making inferences on self-evidencing.

Now, we make the next move, but what about living things?

I mean, so let me ask you, What's the difference between an oil drop and a little tadpole or a little larva or a plankton?

The picture was just painted of an oil drop.

Just immediately, in a matter of minutes, took me into the world of panpsychism where you just convinced me, made me feel like an oil drop is a living, certainly an autonomous system, but almost a living system.

So it has a capability, sensory capabilities and acting capabilities and it maintains something.

So what is the difference between that and something that we traditionally think of as a living system?

That it could die or it can't, I mean, yeah, mortality.

I'm not sure what the right answer there is.

Because they can move, like movement seems like an essential element to being able to act in the environment, but the oil drop is doing that.

The oil drop will be moved, but does it in and of itself move autonomously?

Well, the surface is performing actions that maintain its structure.

I was, I didn't mind a passive little oil drop that's sitting there at the bottom of the top of a glass of water.

What I'm trying to say is you're absolutely right.

If it comes from the inside, then you've got, I think, something that's living.

What I mean is that the internal states that can influence the active states, where the active states can influence, but they're not influenced by the external states, can cause movement.

So there are 2 types of oil drops, if you like.

There are oil drops where the internal states are so random that they average themselves away and the thing cannot balance on average when you do the averaging move.

So a nice example of that would be the Sun.

The Sun certainly has internal states, and there's lots of intrinsic autonomous activity going on.

But because it's not coordinated, because it doesn't have the deep in the millennial sense, a hierarchical structure that the brain does, there is no overall mode or pattern or organization that expresses itself on the surface that allows it to actually swim.

It can certainly have a very active surface, but en masse at the scale of the actual surface of the sun, the average position of that surface cannot in itself move because the internal dynamics are more like a hot gas.

Whereas your internal dynamics are much more structured and deeply structured.

And now you can express on your Markov and your active states with your muscles and your secretory organs, your autonomic nervous system, and its effectors, you can actually move.

And that's something which, if you haven't thought of it like this before, I think it's nice to just realize there is no other way that you can change the universe other than simply moving.

Whether that moving is articulating with my voice box or walking around or squeezing juices out of my secretory organs, there's only 1 way you can change the universe, it's moving.

And the fact that you do so non-randomly makes you alive.

So that's what, and that would be manifest, it would be realized in terms of essentially swimming, essentially moving, changing 1 shape, a morphogenesis that is dynamic and possibly adaptive.

So that's what I was trying to get up between the difference from the oil drop and the little tadpole.

The tadpole is moving around, its active states are actually changing the external states and there's now a cycle, an action perception cycle, if you like, a recurrent dynamic that's going on that depends upon this deeply structured autonomous behavior that rests upon internal dynamics that are not only modeling the data impressed upon their surface or the blanket states, but they are actively resampling those data by moving.

They're moving towards chemical gradients and chemotaxis.

So they've gone beyond just being good little models of the kind of world they live in.

For example, an oil droplet could, in a panpsychic sense, be construed as a little being that has now perfectly inferred it's a passive, non-living oil drop living in a bowl of water.

But to now equip that oil drop with the ability to go out and test that hypothesis about different states of beings.

So it can actually push its surface over there, over there, and test for chemical gradients.

Then you start to move to much more lifelike form.

This is all fun, theoretically interesting, but it actually is quite important in terms of reflecting what I have seen since the turn of the millennium, which is this move towards an inactive, an embodied understanding of intelligence.

And you say you're from machine learning.

So what that means, the central importance of movement, I think has yet to really hit machine learning.

It certainly has now diffused itself throughout robotics.

And perhaps you could say certain problems in active vision where you actually have to move the camera to sample this and that.

But machine learning of the data mining deep learning sort simply hasn't contended with this issue.

What it's done instead of dealing with the movement problem and the active sampling of data, it's just said, we don't need to worry about it, we can see all the data because we've got big data.

So that, for me, is an important omission in current machine learning.

The current machine learning is much more like the oil drop.

But an oil drop that enjoys exposure to nearly all the data that you will ever need to be exposed to, as opposed to the tadpoles swimming out to find the right data.

Let's go and move and ingest food, for example, and see what that, you know, is that evidence that I'm the kind of thing that likes this kind of food.

So the next natural question, and forgive this question, but if we think of sort of even artificial intelligence systems, which has just painted a beautiful picture of existence and life, so Do you ascribe, do you find within this framework a possibility of defining consciousness or exploring the idea of consciousness?

What self-awareness and expanded to consciousness, yeah, how can we start to think about consciousness within this framework?

Well, yeah, I think it's possible to think about it, whether you'll get it.

Get it, you heard it, it's another question.

And again, I'm not sure that I'm licensed to answer that question.

I think you'd have to speak to a qualified philosopher to get a definitive answer there.

But certainly there's a lot of interest in using not just these ideas, but related ideas from information theory to try and tie down the maths and the calculus and the geometry of consciousness, either in terms of sort of a minimal consciousness, even less than a minimal selfhood.

And what I'm talking about is the ability effectively to plan, to have agency.

So you could argue that a virus does have a form of agency in virtue of the way that it selectively finds hosts and cells to live in and moves around.

But you wouldn't endow it with the capacity to think about planning and moving in a purposeful way where it countenances the future.

Whereas you might think an ant's not quite as unconscious as a virus.

It talks to its friends en route during its foraging.

It has a different kind of autonomy, which is biotic, but beyond a virus.

So there's something about, so there's some line that has to do with the complexity of planning that may contain an answer.

I mean, it would be beautiful if we can find a line beyond which we can say a being is conscious.

These are wonderful lines that we've drawn with existence, life, and consciousness.

1 little wrinkle there, and this is something I've only learned in the past few months, is the philosophical notion of vagueness.

So you're saying it would be wonderful to draw a line.

I had always assumed that that line at some point would be drawn until about 4 months ago, and a philosopher taught me about vagueness.

So I don't know if you've come across this, but it's a technical concept, and I think most revealingly illustrated with at what point does a pile of sand become a pile?

Is it 1 grain, 2 grains, 3 grains or 4 grains?

So at what point would you draw the line between being a pile of sand and a collection of grains of sand?

In the same way, is it right to ask, where would I draw the line between conscious and unconscious?

Having said that, I agree with you entirely.

I think it's systems that have the ability to plan.

So just technically what that means is your inferential self-evidencing, by which I simply mean the dynamics, literally the thermodynamics and gradient flows that underwrite the preservation of your oil droplet-like form are described as a, can be described as an optimization of log Bayesian model evidence, your elbow.

That self-evidencing must be evidence for a model of what's causing the sensory impressions on the sensory part of your surface or your Markov blanket.

If that model is capable of planning, it must include a model of the future consequences of your active states or your action, just planning.

So we're now in the game of planning as inference.

Now notice what we've made though, we've made quite a big move away from big data and machine learning, because again, it's the consequences of moving.

It's the consequences of selecting those data or those data or looking over there.

And that tells you immediately that even to be a contender for a conscious artifact or a strong AI or generalized AI as it's called nowadays, then you've got to have movement in the game.

And furthermore, you've got to have a generative model of the sort you might find in, say, a variational autoencoder that is thinking about the future conditioned upon different courses of action.

Now that brings a number of things to the table which now you start to think, well, those who've got all the right ingredients talk about consciousness.

I've now got to select among a number of different courses of action into the future as part of planning, I've now got free will.

The act of selecting this course of action or that policy or that policy or that action suddenly makes me into an inference machine, a self-evidencing artifact that now looks as if it's selecting amongst different alternative ways forward as I actively swim here or swim there or look over here, look over there.

So I think you've now got to a situation if there is planning in the mix, you're now getting much closer to that line, if that line were ever to exist.

I don't think it gets you quite as far as self-aware though.

I think you, and then you have to, I think, grapple with the question, how would formally you write down a calculus or a maths of self-awareness?

I don't think it's impossible to do, but I think there'll be pressure on you to actually commit to a formal definition of what you mean by self-awareness.

I think most people that I know would probably say that a goldfish, a pet fish, was not self-aware.

They would probably argue about their favorite cat, but would be quite happy to say that their mom was self-aware.

But that might very well connect to some level of complexity with planning.

It seems like self-awareness is essential for complex planning.

Again, the line is unclear, but it seems like integrating yourself into the world, into your planning, is essential for constructing complex plans.

So mathematically describing that in the same elegant way as you have with the free energy principle might be difficult.

I don't think that, well, perhaps we should just, can we just go back?

And I think if I just unpacked it, you'd see the truisms that you've just exposed for us.

But let me, sorry, I'm mindful that I didn't answer your question before.

Well, what's the free energy principle good for?

Is it just a pretty theoretical exercise to explain non-equilibrium steady states?

It can be regarded, it's going to sound very arrogant, but it is of the sort of theory of natural selection or a hypothesis of natural selection.

Beautiful, undeniably true, but tells you absolutely nothing about why you have legs and eyes.

It tells you nothing about the actual phenotype and it wouldn't allow you to build something.

So the free energy principle by itself is as vacuous as most tautological theories.

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You Are Your Own Existence Proof (Karl Friston) | AI Podcast Clips with Lex Fridman