Donald Hoffman: Reality is an Illusion - How Evolution Hid the Truth | Lex Fridman Podcast #293

Name: Donald Hoffman: Reality is an Illusion - How Evolution Hid the Truth | Lex Fridman Podcast #293
Uploaded: 2024-05-21T03:56:47.408Z
Duration: 6 h 32 min 16 s

Introduction

In this section, Lex introduces Donald Hoffman and his research on evolutionary psychology, visual perception, and consciousness. He also warns that questioning the fabric of reality can lead to either madness or truth.

Introducing Donald Hoffman

Donald Hoffman is a professor of cognitive sciences at UC Irvine.

His research focuses on evolutionary psychology, visual perception, and consciousness.

He has authored over 120 scientific papers on these topics and his most recent book titled "The Case Against Reality: Why Evolution Hid the Truth from Our Eyes."

Questioning Reality

The world we see with our eyes is not real; it's not even an abstraction of objective reality.

The probability that natural selection would shape sensory systems to see true properties of objective reality is precisely zero except for one kind of structure.

Evolutionary Theory and Perception

In this section, Donald explains how the process of evolution does not maximize for truth but rather for fitness. He also discusses how our senses evolved to guide adaptive behavior rather than to see the truth about objective reality.

Fitness vs. Truth

The process of evolution does not maximize for truth but rather for fitness.

Fitness beats truth, and fitness does not have to be connected to truth.

Our senses evolved to guide adaptive behavior rather than to see the truth about objective reality.

Probability Measures

There is no requirement in standard evolutionary theory for fitness payoff functions to preserve any specific structures of objective reality.

For any scientific theory, there needs to be an assumption that whatever probabilistic structure the world may have is not unrelated to the probabilistic structure of our perceptions.

Measurable Maps

In this section, Donald explains how the map from reality to our senses has to be a measurable map that preserves sigma algebras. He also discusses how this means that it could collapse all sorts of event information.

Measurable Maps

The map from reality to our senses has to be a measurable map that preserves sigma algebras.

This means it could collapse all sorts of event information.

There is no requirement for fitness payoff functions to preserve any specific structures of objective reality.

Conclusion

In this section, Lex concludes the podcast by thanking Donald Hoffman and discussing the importance of questioning our understanding of reality.

Questioning Reality

Questioning our understanding of reality can lead us either to madness or truth.

It's important to continue exploring these ideas and questioning what we think we know about the world around us.

Counting Payoff Functions

In this section, the speaker discusses how to count payoff functions and determine how many of them preserve the total order or topology.

Counting Payoff Functions

To count payoff functions, assign payoffs from zero to a thousand or any desired value and count all the payoff functions using combinatorics.

Determine how many of those payoff functions preserve the total order or topology by counting them and dividing.

As the number of states in the world and the number of payoff values goes very large, take the limit to get zero every time.

Perception vs Reality

In this section, the speaker discusses how our perceptions are not real in the way we think they are.

Perception vs Reality

Our perceptions guide adaptive behavior but are not there to show us truth. They hide truth because it is too complicated.

Evolution gave us perceptions that guide adaptive behavior, which means hiding truth and giving eye candy.

Scientific theories can tell us certain limits but cannot tell us what reality is. We see a user interface but do not know what it is or how it's built.

Our scientific theories are precise enough and rigorous enough to tell us certain limits but even these limits have their own limitations.

The End of Space-Time

In this section, the speaker discusses how physicists are saying that space-time is doomed and there is no such thing as space-time fundamentally in the laws of physics.

Physicists' View on Space-Time

Physicists are saying that space-time is doomed and there's no such thing as space-time fundamentally in the laws of physics.

This comes out of gravity together with quantum field theory, which entails that space-time cannot be fundamental.

Particles in space-time cannot be fundamental; they're just irreducible representations of the symmetries of space time.

What Do You Mean by Space-Time?

In this section, the speaker explains what he means by "space-time" and why it's doomed.

Definition of Space-Time

When referring to "space-time," physicists mean both space and time united into Einstein's theory.

Physicists are looking for new mathematical structures beyond Einstein's four-dimensional spacetime or supersymmetric version geometric algebra signature two comma four kind.

Why Space-Time Is Doomed

Physicists believe that even quantum theory will not have Hilbert spaces as a fundamental concept.

They're finding new ways to compute scattering amplitudes outside of spacetime, which turns billions of terms into one term when computing processes in colliders.

Enforcing locality and unitarity properties in spacetime leads to complicated computations with multiple loops. However, doing it outside spacetime captures deeper symmetries true to data.

The Search for Deeper Structures Beyond Space-Time

In this section, the speaker discusses how physicists are searching for deeper structures beyond space-time and the challenges they face in doing so.

Insights into Symmetries

Physicists are trying to turn computations from billions of terms to one or two or a handful of terms to gain insights into symmetries.

They need a flashlight to look beyond space-time because Einstein's theory and quantum theory can't tell us what's beyond them.

Physicists are making informed guesses about these structures, trying to ask what deeper structure could give us the stuff that we're seeing in space-time without certain commitments that we have to make in space-time like locality.

Reductionism Has Been a Fantastic Methodology

Two pillars of modern science, quantum field through with gravity on the one hand and evolution by natural selection on the other, have very clearly said space time has had a good run. Reductionism has been a fantastic methodology.

Every new idea that we come up with beyond space time must project precisely into space time and it better give us back everything that we know and love in space time or generalizations or it's not going to be taken seriously and it shouldn't be.

Evolution by Natural Selection Could Be an Interface

Even evolution by natural selection and quantum field theory could be interfaces into something that doesn't look anything like them. The framework that emerges from whatever is beyond space-time must look like evolution by natural selection when projected into space-time or it's wrong.

Perceptual Space and Time

In this section, the speaker discusses how our perceptual space and time have been used as the basis for creating Newtonian space versus time as a mathematical extension of our perceptions. Einstein then extended it even further into the Einsteinian formulation.

Relationship between Evolution and Physics

Our perceptual space-time is just a user interface effectively.

The physicists are finding that even the mathematical extension of that into the Einsteinian formulation has to be as well.

The relationship between them is that they are formulated as sort of rigorous extensions of our perceptual space, making it mathematically rigorous and laying out the symmetries that they find there.

Reductionism and Interfaces

In this section, the speaker talks about reductionism and interfaces as we march forward from Newtonian physics to quantum mechanics.

Interfaces in Science

Reductionism and interfaces are all in your view interfaces.

These interfaces are strongly predictive about some aspects of our reality.

They help us get closer to objective reality.

Constraints on Theories

One critical constraint on all of our theories is that they are empirically tested and past experiments.

We have good reason to believe that science will never get a theory of everything.

Even with mathematics, any finite accidentalization sophisticated enough to do arithmetic can't prove certain statements.

Connection Between Money and Reality

In this section, the speaker discusses whether it's better to connect social interactions with each other to some degree with reality or operate in something that's a complete illusion.

Settlement of Transactions

Settlement of transactions is often talked about in cryptocurrency especially.

When money was on the gold standard, it represented some stable component of reality.

Connecting Social Interactions to Reality

It's better from an evolutionary perspective to connect social interactions to some degree with reality.

Hyperinflation can occur when you deviate very far away from the underlying reality.

Decentralization and Evolution

In this section, the speaker discusses the importance of decentralization in human society from an evolutionary perspective.

Decentralization as a Solution

The speaker argues that putting too much faith in a few central controllers is not wise because it depends on their veracity and trustworthiness.

Democracy is a step towards decentralization, but it still has limitations.

The Defi movement is an even bigger step towards democratization.

Power Corrupts

The idea that power corrupts is a consequence of evolution.

Mad men and women throughout history might be useful to teach us what we can learn from our negative examples.

Science and Evolutionary Interface

In this section, the speaker discusses whether the evolutionary interface idea unhinges science from some important tests for theories.

Tethering Our Theories

We can only test things in terms of what we can measure with our senses in space and time.

There's no problem tethering our theories to test them.

Reverse Engineering Neuroscience

Our best theories are telling us that pointers are just pointers, and even they themselves are not objective reality.

We have to reverse engineer what is going on beyond space-time that gives us things that look like neurons and neural networks.

There will be lots more work for neuroscience, which will be far more complicated and challenging.

Perceptual Creation

When you look at a piece of paper with a little sketch of something called the Necker cube, you perceptually create the cube.

The Mapping of Objective Reality

In this section, the speaker discusses the possibility of mapping objective reality in a concrete and predictable way to space-time.

Mapping Objective Reality

The speaker suggests that it is possible to map objective reality in a concrete and predictable way to space-time.

Physicists are finding new theories beyond space-time that have tethering, which shows precisely how an amplitude can be projected into four dimensions of space-time.

They are also finding static geometric structures with symmetries that are true of the data but cannot be seen in space-time.

A Theory of Consciousness Beyond Space-Time

In this section, the speaker talks about his interest in finding a theory beyond space-time that is dynamical and relates to consciousness.

Dynamics of Consciousness

The speaker expresses his desire to find a theory beyond space-time that is dynamical and relates to consciousness.

He believes that if we can find such a theory, we would have a completely different way of looking at how consciousness is related to the physical world.

Currently, most scientists assume that particles, elements, atoms, neurons, and brains are part of objective reality within space-time. However, our best theories suggest that space-time is doomed.

Reductionism vs Scientific Explanation

In this section, the speaker explains reductionism as a particular kind of scientific explanation and distinguishes it from scientific explanation.

Reductionism vs Scientific Explanation

Reductionism is a particular kind of scientific explanation where one starts with fundamental laws at smaller scales in space-time and builds up to more complicated ones.

Scientific explanation, on the other hand, is a broader concept that does not necessarily involve reductionism.

The Role of Reductionism in Science

In this section, the speaker discusses the role of reductionism in science and how it has been useful in certain areas of physics.

Reductionism vs. Simplification

The laws of physics for uniform motion are universal for all observers, and they are not a reductionist concept.

Simplification is a bigger thing than just reductionism.

Reductionism has been particularly useful in thermodynamics, where heat can be reduced to molecules or atoms bouncing around with energy.

Limits of Reductionism

There is a limit to how far reductionism can go, as we know now that it stops at 10^-33 centimeters and 10^-43 seconds.

To find the next step beyond Einstein's theory of relativity and quantum theory, scientists need to let go of space-time and think outside the box.

Cellular Automata and Data Structures

In this section, the speaker discusses cellular automata and data structures as potential avenues for exploring physics beyond space-time.

Thinking Outside Space-Time

Stephen Wolfram's proposal for a data structure that could be used to explore physics beyond space-time is exciting because it deals with very tiny numbers.

If scientists want to explore physics beyond space-time using cellular automata, they must do so prior to space-time itself.

Understanding Dynamics Beyond Causality

When thinking about dynamics beyond causality, everything becomes an interface. However, our understanding of what "dynamical" means may be limited.

Understanding the Human Mind and Neurons

In this section, the speaker discusses how neuroscience can be used to understand the human mind and neurons. He talks about the importance of having a computational theory, an algorithm, and hardware to truly understand a system.

The Three-Level Approach

David Marr's three-level approach involves having a computational theory, an algorithm, and hardware to truly understand a system.

The speaker was drawn to this approach because it emphasized that if you can't build something, you don't truly understand it.

To really understand the brain and its architecture, we need to have an understanding of all three levels: computational theory, algorithm, and hardware.

Top-Down Model

To reverse engineer a computing system like a laptop or understand the brain through neuroscience, we need to have a top-down model of what is being computed and why.

We need to know why certain features exist in order to fully comprehend their circuitry.

Fictional Interface of Reality

In this section, the speaker discusses how our perception of reality is just an adaptive fiction. He explores whether this fictional interface helps us build intuition about deeper truths.

Fictional Interface

Our perception of reality is just an adaptive fiction created by evolution through natural selection.

Literary fiction helps us build intuition about reality in indirect ways. Similarly, observing reality may help us build intuition about deeper truths.

Positing Deeper Theories

Each theory proposed will give its own answer as to whether our fictional interface helps us build intuition about deeper truths.

We need to posit new, deeper theories and try to answer questions within the framework of those theories. However, we must acknowledge that there will always be an even deeper theory.

Paralyzing Effect

The idea that we may never truly introspect to the bottom can be paralyzing for a scientific mind.

However, it is important to note that there is still value in positing theories and trying to understand reality as deeply as possible.

The Ground of Being

In this section, the speaker discusses the idea that space and time may not be fundamental but rather an illusion. They also explore the concept of being in contact with the deep ground of being that transcends any particular conceptual understanding.

Space and Time as Illusion

Space and time may not be fundamental but rather an illusion.

Introspection can lead to something beyond conceptual thought, which is being in contact with the deep ground of being.

If consciousness is important or fundamental in the universe, it may be a never-ending exploration.

Personal Science

Science could become personal all the way down if we are in touch with this ground of being.

The scientific method would still be used for conceptual understanding even if we cannot understand ourselves all the way.

Consciousness could be getting at a deeper truth of reality, but we still do not know what it means.

Job Security for Scientists

In this section, the speaker explores whether pursuing science is a never-ending exploration or if there are other ways to spend our time. They discuss how scientists might become useless as we understand more about our world.

Exploration vs. Living Maximally

As we understand more about our world, exploration may no longer be fruitful.

There are other ways to live maximally that do not involve exploration.

Artificially generating challenges for oneself can provide a sense of fulfillment.

Pushing Back on Job Security Concerns

Scientists could become holders of ancient wisdom that allows us to study our own history.

Faraday's experiments with magnets and electricity demonstrate the importance of scientific exploration.

Theories Beyond Space-Time

In this section, the speaker discusses how theories beyond space-time can lead to new technologies and possibilities for exploration.

Possibilities of Theories Beyond Space-Time

Theories beyond space-time have opened up new technologies that allow people to communicate around the world.

Most galaxies are going away from us at the speed of light or beyond, making it impossible to reach them. However, if we recognize that space-time is just a data structure in our perceptions, we may be able to go around it and explore these unreachable areas.

Endless sequences of theories could lead to remarkable insights into the potentialities and possibilities that would seem miraculous to us. This exploration could motivate scientists to continue their work.

The act of being may be a place where scientists get many of their ideas and pull them into conceptual systems.

Evolutionary Game Theory

In this section, the speaker discusses evolutionary game theory and when humans started deviating from reality.

Deviation from Reality

According to David Maher's book "Vision," more primitive sensory systems were less realistic than more complicated ones like those found in humans.

As creatures become more complex with 86 billion neurons like humans, they can compute parts of the truth needed for survival.

Evolutionary Game Theory and the Limits of Scientific Theories

In this section, the speaker discusses evolutionary game theory and its limitations. He emphasizes that scientific theories should not be taken as gospel but rather as the latest ideas that we have. He also talks about how his colleagues have tried to show that their simulations are wrong.

Evolutionary Game Theory and Scientific Theories

Studying evolutionary game theory helps us understand how genes evolve.

As a scientist, it is important to use the best tools available with humility and not believe any of our current scientific theories as gospel.

We should assume that everything we think is brilliant now will be laughed at in a century from now.

The speaker acknowledges pushback from colleagues who have tried to show that their simulations are wrong.

Limits of Game Theory

The speaker expresses suspicion towards game theory because it can oversimplify models and make flawed assumptions.

Colleagues at Yale suggested using thousands of payoff functions instead of one or two to find conditions where truth-seeking organisms would evolve.

Probability zero does not mean something cannot happen infinitely often; it just means probability close to zero.

Probability, Infinites and Mathematics

In this section, the speaker discusses the concept of probability and how it relates to infinites in mathematics. They also touch on the debate between intuitionist and algorithmic approaches to mathematics.

Probability of Zero

The speaker explains that there are objects in probability theory that have a measure of precisely zero but contain infinitely many points.

They note that things with a probability of zero can happen infinitely often in principle, even though we never see infinity in real life.

Intuitionist vs Algorithmic Approaches

The speaker discusses the debate between intuitionist and algorithmic approaches to mathematics.

They mention Nicholas Giesen's work on how intuitionist mathematics can effectively quantize Newtonian theory and make it similar to quantum theory.

Discrete vs Continuous Reality

The speaker raises the question of whether the world is discrete or continuous in some general sense.

They note that this ultimately boils down to a deep philosophical issue about how we should think about reality.

Common Sense Reasoning

The speaker notes that common sense reasoning doesn't always apply when dealing with infinities and probabilities.

They argue that we need to use the best interfaces available to reason about the world, even if they don't always align with our common sense notions.

Game Theory as an Interface for Reality?

In this section, the speaker discusses game theory as an interface for understanding reality. They also touch on evolutionary game theory and its limitations.

Game Theory as an Interface

The speaker questions whether game theory is the best interface we have for understanding reality.

They note that if someone were to present a better mathematical tool, they would be open to using it.

Evolutionary Game Theory

The speaker discusses evolutionary game theory and its limitations.

They mention the work from Yale on dealing with ensembles of fitness functions and how organisms can create data structures to deal with them.

Objects and Perception Systems

In this section, the speaker discusses objects and perception systems. They touch on hierarchical clustering of fitness payoff functions and how organisms can use data structures to deal with them.

Creating Data Structures

The speaker discusses how organisms can create data structures to deal with ensembles of fitness functions.

They mention hierarchical clustering as a way to group similar fitness payoff functions together into objects.

Evolutionary Theories and Fitness Functions

In this section, the speaker discusses evolutionary theories and fitness functions. They explain that objects have different payoffs for different actions, and that fitness functions are not necessarily based on reality. The speaker also suggests that the distinction between living and non-living is an artifact of our interface.

Objects as Data Structures

Objects are data structures encoding a convenient way of looking at various fitness payoffs.

Different objects have different sets of payoff functions for various actions.

Origin of Fitness Functions

Fitness functions originate from a black box that gives us different fitness payoffs for different objects.

Reality is not a good generator of fitness functions because it does not take into account the different uses of objects.

Evolutionary Game Theory

Evolutionary game theory assumes the existence of fitness payoffs and strategies with payoffs to explain behavior.

It cannot explain where these fitness payoffs come from or how physics evolves biology.

Fundamental Nature of Space-Time

Space-time is not fundamental but rather an interface that hides certain aspects of reality.

The distinction between living and non-living is an artifact of our interface.

Deeper Theory than Space-Time

To understand where evolution comes from, we need a deeper theory than space-time in which there may not be the notion of time.

This deeper theory would show how dynamics can exist without time and how evolution by natural selection emerges from it.

The Emergence of Death

In this section, the speaker discusses how death is an important component of natural selection and evolution.

The Importance of Death

Death is a crucial component of natural selection and evolution.

Fitness functions are necessary for natural selection to occur.

Without life and death, there would be no concept of an organism or evolution.

Defining Living Organisms

In this section, the speaker discusses how living organisms are defined by their ability to move and maintain their integrity over time.

Defining Living Organisms

A living organism is defined by its ability to move and maintain its integrity over time.

An organism has a wall that separates it from the environment, defining what is inside and outside.

The ability to move combined with maintaining separation from the environment defines an organism as alive.

Probabilistic Inferences in Life

In this section, the speaker discusses how probabilistic inferences may play a role in keeping organisms alive.

Probabilistic Inferences in Life

Dynamics within a Markov blanket seem to be trying to estimate properties of the outside world in ways that might keep an organism alive through probabilistic inferences.

Interesting work is being done on Bayesian networks built on the notion of a Markov blanket that could help explain how organisms stay alive through probabilistic inference.

Consciousness and Reality

In this section, the speaker discusses the concept of consciousness and how it relates to reality.

Consciousness and Reality

The face we see is just a symbol that we create, but there is a deeper reality beyond what we see.

Consciousness is always present, even when the symbols we use to represent it are not.

When looking at different entities, such as cats or protons, we create symbols that represent them differently based on our beliefs about their consciousness.

It's possible that even entities like protons could have some form of consciousness behind them.

The Portal of Consciousness

In this section, the speaker discusses the concept of a portal to consciousness and how it varies in complexity across different organisms.

Building Portals to What's Behind Space-Time

Elementary particles such as quarks, leptons, and gluons are just symmetries of space-time. They do not provide much insight into what is behind space-time.

As we move up the levels of complexity, we start building portals to what's behind space-time.

The interface between humans allows for a good representation of ideas and memories. However, constructing models about each other may still be distant from an underlying reality.

Signaling Games

Signaling games explore how people can coordinate and communicate effectively.

A study on evolving color words found that dichromats had an outsized influence on how colors were labeled due to their unique perspective.

Game theory and signaling games can be used to explore communication strategies that are useful.

The Role of Consciousness

In this section, the speaker delves into the topic of consciousness and its role in human experience.

Defining Consciousness

Consciousness is a beautiful and powerful thing that makes us human.

It is difficult to define consciousness but it involves subjective experience, awareness, attention, intentionality, and self-awareness.

Theories on Consciousness

There are many theories on consciousness including Integrated Information Theory (IIT), Global Workspace Theory (GWT), Higher Order Thought (HOT), among others.

IIT proposes that consciousness arises from integrated information while GWT suggests that conscious processing occurs in a global workspace accessible by multiple brain regions.

HOT posits that higher-order thoughts are necessary for consciousness.

The Hard Problem of Consciousness

The hard problem of consciousness is the question of how subjective experience arises from physical processes.

It is difficult to explain how neurons firing can give rise to subjective experience.

Some theories suggest that consciousness may be a fundamental aspect of the universe.

The Emergence of Consciousness

In this section, the speaker discusses different theories on how consciousness emerges and what properties are necessary for it to exist.

Theories on Consciousness

Consciousness arises from complicated systems of matter with the right functional properties.

Orchestrated collapse of quantum states of microtubules in neurons is a theory proposed by Hamroff and Penrose.

Integrated information theory suggests that if something physical has the right kind of functional properties, then it can have consciousness.

Panpsychism adds consciousness as an additional property to particles in space and time.

Fundamental Elements

Space-time is not fundamental, which challenges the current framework for consciousness research.

Earth, air, fire, and water were once thought to be fundamental elements until the discovery of quarks leptons and gluons.

Quarks leptons and gluons are irreducible representations of the symmetries of space-time.

Implications

The current framework for consciousness research may hinder progress.

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Consciousness and the Black Hole of Consciousness

In this section, the speaker discusses his theory of consciousness and its assumptions. He explains that conscious experiences are fundamental and subjective, and that they trigger other conscious experiences probabilistically. The speaker also clarifies that his theory applies to all consciousness, not just human consciousness.

Assumptions of the Theory

The speaker's theory assumes that there are conscious experiences which are fundamental and subjective.

These experiences are not derived from physics or functional properties of particles; they exist like space-time.

Conscious experiences have consequences and can trigger other conscious experiences probabilistically.

The speaker uses the term "conscious agent" as a technical term to describe a mathematical structure that includes a probability measure, a probability space of possible conscious experiences, and a Markovian kernel describing how these experiences affect other agents.

Generalization of the Theory

The speaker clarifies that his theory applies to all consciousness, not just human consciousness.

Human consciousness is only one type among countless varieties of consciousnesses.

Even within humans, there are many different types of consciousnesses (e.g., left vs. right hemisphere).

However, the speaker notes that cats lack compassion and capacity for consciousness.

Conclusion

The speaker's theory assumes that there are fundamental and subjective conscious experiences which trigger other conscious experiences probabilistically. This theory applies to all types of consciousnesses beyond just human beings.

Conscious Agent Networks

In this section, the speaker discusses how networks of conscious agents can be used to build a theory of consciousness.

Definition of Conscious Agents

Two conscious agents interacting satisfy the definition of a single conscious agent.

Networks of conscious agents are computationally universal and can capture any computable theory.

Building Memory and Learning

To have a notion of self, learning, memory, problem-solving, intelligence, and planning, networks of conscious agents must be built.

Conscious agent networks can be used to build memory and primitive kinds of learning.

The Hard Problem of Consciousness

The hard problem is typically thought of as explaining how the experience of taste or other sensations emerge from physical things like neurons or silicon.

The speaker changes the problem by asking how to build up space and time from conscious experiences instead.

Brains are something that consciousness makes up; they are not what produce consciousness.

Solving the Hard Problem

In this section, the speaker explains his approach to solving the hard problem by building up space and time from conscious experiences.

Building Up Space and Time

The speaker's approach starts with conscious experiences rather than physical things like neurons or silicon.

He asks how to build up what we call brains from consciousness rather than explaining how brains produce consciousness.

Brains are an ephemeral experience in consciousness; they are not fundamental.

Data Structures in Consciousness

Neurons are a data structure created on-the-fly when observed but garbage collected when not observed.

Similarly, physical objects like cubes only exist as data structures when observed.

Limitations on Computation

Markovian dynamics is not restricted to computable functions because events themselves may not be computable.

Non-computable interactions between conscious agents are possible.

The Space of Data Structures

In this section, the speaker discusses the possibility of different data structures for consciousness and how it relates to mathematics.

Consciousness and Mathematical Structures

Investigating consciousness may not lead to similar data structures.

If consciousness is fundamental, mathematical structure can only be about possibilities of consciousness.

There could be an infinite variety of consciousnesses that use a vanishingly small fraction of space-time data structures.

Mathematics is not the fundamental reality in this framework; rather, it is to consciousness like bones are to an organism.

Infinite Variety of Consciousnesses

There's an infinite variety of conscious experiences and signaling games that they could interact via.

Space and time are just one of an infinite variety of data structures.

As we go outside our little space-time bubble, we will encounter utterly alien forms of conscious experience that we may not comprehend.

Singular Consciousness

The set of possible experiences you can have in a subjective way is basically a singular consciousness.

Two conscious agents interacting in mathematics satisfy the definition of a conscious agent.

One big conscious agent infinitely complicated but fortunately we can break it down all the way to the simplest conscious agent which has one conscious experience.

Consciousness as Fundamental Reality

In this section, the speaker proposes that consciousness is more fundamental than space-time as we perceive it.

Consciousness vs. Space-Time

Consciousness is more fundamental or at least much more in the direction of the fundamental than space-time as we perceive it.

The speaker's proposal is to show how dynamical systems of conscious agents could lead to what we call space and time and neurons and brain activity.

Consciousness Without Form

In this section, the speaker discusses how consciousness can emerge within a system of networks of conscious agents. They also talk about the two miracles in their theory and how they hope to get beyond them.

Conscious Experiences as Fundamental

The speaker took conscious experiences as fundamental in their theory.

There are two miracles in their theory: conscious experiences and the probabilistic relationship between them.

The speaker is not explaining where conscious experiences come from in the current version of their theory.

Probability Space for Consciousness

The probability space for possible conscious experiences corresponds to consciousness without any content.

The structure is just sitting there, and there's going to be a dynamics that happens on it.

One way to think about that fundamental probability space is that it transcends any particular content.

Solving the Hard Problem

The problem of how you start with conscious experiences and build up space and time and brains is tough but solvable.

Networks of conscious agents create what we call brains, not the other way around.

This theory of consciousness will be even deeper than the structures that physicists are finding.

The Mystery of Consciousness

In this section, the speakers discuss the mystery of consciousness and how it is difficult to understand how formless gives birth to form. They also talk about their ideas on consciousness and unconsciousness.

Understanding Consciousness

The speakers acknowledge that they may never fully understand how formless gives birth to form.

They caution that all theories will eventually become outdated and be replaced by new ones.

The speakers discuss interesting distinctions between their ideas of consciousness and those of other experts in the field.

They explore some sticking points with Annika Harris' ideas on consciousness, but ultimately find that they are mostly on the same page.

Annika Harris cautions against using misleading language when discussing conscious agents.

Defining Consciousness

Language can be ambiguous when discussing topics like consciousness, which can lead to miscommunication.

The speaker proposes a way of thinking about consciousness as a dynamics not in space and time, but abstractly.

Entropy and Consciousness

In this section, the speaker discusses how any projection of a Markov chain by conditional probability will have increasing entropy. They also discuss the concept of entropic time and how it relates to consciousness.

Entropy and Markov Chains

Any projection of a Markov chain by conditional probability will have increasing entropy.

The entropy of xn is equal to the entropy of xn-1 for all n, but h(xn| x1) is greater than or equal to h(xn-1| x1).

The assumption of stationarity is used many times in discussing stationary systems.

A stationary system has certain properties in terms of entropy.

Consciousness and Limited Resources

Even if the dynamics of consciousness are stationary, any projection will have the artifact of entropic time due to limited resources.

More constraints lead to more predictive and powerful statements about a system's behavior under different properties.

Competition, evolution, and nature red in tooth and claw may be an artifact of a deeper system where those aren't fundamental.

Evolution via Projection

Networks of conscious agents give rise to evolution by natural selection via a projection.

Competition leads to life and death situations that give rise to notions like self-separation from other selves.

Self as an Artifact

Anytime conscious agents interact they form a new conscious agent leading to one conscious agent in any projection.

The notion of self can be an artifact of the projection of a conscious agent.

The Notion of Self and Consciousness

In this section, the speaker discusses the notion of self and consciousness. He talks about how individual selves and physical objects may be a projection of consciousness. He also mentions that there is a deeper self that precedes any particular conscious experience.

The Projection of Consciousness

Natural selection suggests that individual selves and physical objects may be a projection of consciousness.

There is a deeper self that precedes any particular conscious experience.

Our little "s" selves could be artifacts of projection, projected down into a self that calls itself Dawn or Lex.

Learning About Ourselves

Through conversations like this, consciousness is learning about itself.

We are not separate from each other or from the thing dressed up as us today.

Physicalism vs Reductionism

In this section, the speaker talks about physicalism and reductionism. He defines these terms and explains why he walked away from physicalism.

Physicalism vs Reductionism

A physicalist takes space-time and the objects within space-time as ontologically fundamental.

Reductionists say that smaller scales in space have more fundamental laws.

The speaker walked away from physicalism because it became clear that we couldn't start with unconscious ingredients and boot up consciousness.

Booting Up Conscious Experiences

In this section, the speaker challenges his colleagues to give one specific conscious experience that can be booted up from physical systems. He discusses various theories of consciousness.

The Challenge

The speaker challenges his colleagues to give one specific conscious experience that can be booted up from physical systems.

He asks for a precise structure that accounts for the taste of chocolate and why it couldn't possibly be vanilla.

Theories of Consciousness

There is not one theory that can account for all conscious experiences.

Integrated information theory, collapse of microtubules, and global workspace theory are all theories of consciousness.

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