Multiway Systems as Models to Understand Mind and Universe - a Conversation with Stephen Wolfram

Name: Multiway Systems as Models to Understand Mind and Universe - a Conversation with Stephen Wolfram
Uploaded: 2022-04-13T14:46:08.000Z
Duration: 3 h 54 min 39 s

Introduction

In this section, Tanya introduces the speakers and their backgrounds.

Speakers

Stephen Wolfram is the creator of Mathematica and the author of "A New Kind of Science."

Joshua is a cognitive scientist and AI researcher at Intel Labs.

Opening Statement

In this section, Joshua gives an opening statement about Stephen's work and his perspective on physics and computation.

Stephen's Work

Stephen has discovered something that philosophy is struggling to discover.

Mathematics is a code base that needs to have a new footing.

Steven set out to write his own code base as a tool for making sense of the world.

Steven shares his understanding with the world as a platform to explore the universe in a more systematized fashion.

Existence as Default

In this section, Joshua discusses existence as default and how it relates to epistemology.

Existence as Default

The easiest explanation for why there is something rather than nothing is that existence is the default.

Everything that can potentially exist does actually exist.

The universe could be comprehended in some kind of language that can form representations.

The universe is something like the superposition of all finite automata.

Ruliat: The Entangled Limit of Everything

In this section, Joshua discusses Stephen's text on Ruliat, which explores the superposition of all automata.

Ruliat: The Entangled Limit of Everything

Ruliat is basically the superposition of all automata.

We have to explain structure by gaps in existence.

We have to think about why certain events can have all possible consequences but only some.

Causal Structure and Paradigms

In this section, the speaker discusses the actual causal structure and how it differs from the way we think of causal structure. They also introduce the idea of a non-deterministic Turing machine as a new paradigm for describing theories.

Actual Causal Structure

The actual causal structure is different from how we think of it in our minds.

It exists as low-dimensional and discrete functions that are compositional algorithms.

It explains state transitions of a system by a low-dimensional and discrete function.

Non-Deterministic Turing Machine

The non-deterministic Turing machine is introduced as an arcane concept to compute the complexity of algorithms that cannot be implemented.

The resulting complexity of programs for non-deterministic Turing machines is different than for deterministic ones.

This idea could be a new paradigm in the way we think about things, not just in physics but also in biology, economy, social sciences, and even the mind.

Consciousness and Perception

In this section, the speaker talks about consciousness and perception. They discuss how our belief that we follow a single thread of experience may not be true of the universe.

Persistence in Time

Our perception of consciousness involves believing that we are persistent in time.

However, this may not be true of the universe; it's simply a way we choose to sample things that happen.

Perception and Laws of Physics

To what extent is our perception of the world determined by our beliefs about laws of physics?

We don't have much choice about putting the world together in certain ways based on how we are wired.

Introduction

The speaker discusses the trajectory of the universe and how information can be lost in it. They also talk about the difference between a deterministic and non-deterministic universe.

Universe Trajectory and Information Loss

The universe's trajectory is affected by information loss.

In a non-deterministic Turing machine, information can be lost, which affects our understanding of the universe.

Quantum mechanics is an example of a nondeterministic Turing machine that differs from Minecraft's deterministic universe.

Understanding Physics

To understand how minds interact with physics, we must first understand physics.

There is an interesting conversation about conscious thinking versus unconscious thinking and whether they correspond to single or multiple threads of experience.

What Is Our Universe Made Of?

The speaker explains what our universe is made of and how it is constructed.

Space Atoms

Everything in the universe is made up of space atoms.

Space has a definite structure like water, consisting of molecules. Similarly, space consists of atoms that are connected to each other forming a hypograph or generalized graph.

There are no coordinates for these atoms because there is no background space. All we have is connectivity information about how these atoms are connected to each other.

Locations That Hold Information

Locations are places that hold information but don't hold much themselves.

The set of all trajectories that information can take between locations makes up spacetime.

The representation of the state of the universe consists of n-tuples of things with UUIDs.

Connectivity Changes

The connectivity between locations changes the state of the universe.

A rule is applied to transform a piece of graph into another.

Introduction to Multi-Way Graphs

In this section, Stephen Wolfram introduces the concept of multi-way graphs and explains how they represent the evolution of a system.

Computational Rules and Multi-Way Graphs

The progress of time is the progressive application of computational rules.

Multi-way graphs represent the evolution of a system from one complete state to several possible future states.

Every path through that graph is a possible history for the universe.

Perception in a Branching Universe

In this section, Stephen Wolfram discusses how we experience multi-way graphs and how our perception is determined by our position within the system.

Observers in a Branching Universe

We are observers who are embedded within the system.

Quantum mechanics is really a story of how a branching brain perceives a branching universe.

Laws of Physics and Perception

The laws of physics are determined by our perception of them.

Our perception is limited by our computational abilities, which means we can only describe things at certain scales.

Perception of the Universe

In this section, the speaker discusses our perception of space and time and how it relates to our belief in a continuum.

Continuum and Space

Our belief that space is a continuum is due to the fact that we are much bigger than atoms of space.

The elementary length might be 10^-100 meters, which is really small compared to the universe's size.

Space as a continuous substrate never made sense to the speaker.

Constructive Perspective

It doesn't make sense from a constructive perspective because you cannot construct a continuum.

Geometry is the set of operators that our brain can compute efficiently in the limit.

Persistence in Time

Our belief in persistence in time implies a certain continuum.

Information preservation is necessary for generalizing over observations and forming any kind of model.

Observers

The speaker notices gaps in their memory and thinking, making their own models of themselves as an observer approximate.

There needs to be a foundational theory of observers similar to computation.

Introduction

In this section, the speaker introduces the concept of an observer and how it relates to science and technology.

What is an Observer?

An observer is something that registers in our brains.

Science constructs technology by extending transduction from the real world to what we perceive in our brains.

Our description of the physical world depends on laws that work for us as observers.

The view of the universe we have depends on coarse properties of us as observers, such as being computationally bounded and believing we are persistent in time.

Perception of Physics

In this section, the speaker discusses how we perceive physics and how it relates to our understanding of objects.

Perception of Physics

We can only directly perceive things about physics that register in our brains.

Our perception is limited by computational power, so we rely on laws that work for us as observers.

Objects are constructs based on whether they give us a useful description.

Objects are somewhat arbitrary divisions imposed on the state vector of the universe to interpret our observations.

Understanding Objects

An object is something that remains constant when perspective changes.

Vortexes of cigarette smoke at some point become meaningless to treat as objects.

Some objects are more solid and persistent than others.

What is an Electron?

In this section, the speaker explains what an electron is in their model of the world.

Model of the World

There's nothing in the world except space; it's just a big network of atoms of space.

An electron is some persistent thing in that network executing rules.

The semantics of links in space's graph hold state.

A rule operates on clusters turning them into different ones.

Introduction

In this section, Stephen Wolfram and Lex Fridman discuss the concept of rules and where they come from.

The Origin of Rules

Rules are everywhere and can be applied to many things.

It is difficult to determine where a rule comes from or why it is chosen over another.

The discussion leads into the topic of electrons.

Electrons

In this section, Stephen Wolfram and Lex Fridman discuss the structure of electrons.

What Are Electrons?

Electrons are believed to be like vortices in space-time.

They have some topological features that may be similar to vortices but not in terms of visual appearance.

Electrons are persistent structures that survive for a certain amount of time.

Describing Vortices as Objects

In this section, Stephen Wolfram and Lex Fridman discuss how vortices behave like objects.

Vortex Behavior

Vortices behave like objects because they have an identity that moves around.

Although the molecules that make up a vortex are continually changing, there is a collective motion that corresponds to a vortex.

As a practical matter, we can describe vortices as objects even though it might be hard to determine their exact boundaries.

Black Holes vs. Electrons

In this section, Stephen Wolfram and Lex Fridman compare black holes with electrons.

Similarities Between Black Holes and Electrons

There could be a close analogy between black holes which are structures in space-time and electrons which we also think of structures in space-time both made up of space.

Every electron seems to be the same although it's not clear if that's really true.

Black holes only expose certain things to the outside, and it could be very much the same with electrons.

Conclusion

In this section, Stephen Wolfram and Lex Fridman conclude their discussion on electrons.

The Role of Electrons in the Universe

The vast majority of activity in the universe is concerned with knitting together the structure of space.

Electrons are a tiny piece of froth on top of this main activity.

It is a little disappointing that most activities in the universe are collisions between molecules rather than collective motions like vortices.

Understanding the Observer in Quantum Mechanics

In this section, the speakers discuss the concept of an observer in quantum mechanics and how it relates to consciousness. They also explore the collapse of the wave function and its implications.

The Nature of Dissolving Patterns

Patterns dissolve into different patterns, occupying a particular region in space.

An observer is a pattern with functional properties that can be made out of multiple materials.

The observer is an abstraction that we don't fully understand yet.

Consciousness as a Virtual Character

Consciousness is part of a fiction created by our brain to make sense of sensory data.

Our brain implements an observer that observes patterns and abstract functions over them.

We construct superpositional states in our mind when observing quantum mechanical phenomena.

Collapse of the Wave Function

The collapse of the wave function is special because it marks a point beyond which we cannot pretend that the universe is classical.

Something has to come in and collapse all those threads of history and take us down to just one classical thread.

To understand more about this collapse, we need to take apart the hammer that collapses all those threads.

Coarse Graining in Branchial Space

Our minds exist as branching things in this multi-way universe, coarse-graining not only physical space but also bronchial space.

We have an extent in bronchial space just like we have an extent in physical space.

The Question of Consistency in Conflating Different Parts of History

In this section, the speaker discusses the question of whether it is consistent to conflate different parts of history and what it means if it is or isn't consistent.

Conflating Different Parts of History

We can consider threads of history to be the same by conflating them together.

This allows us to simplify our understanding and think about many detailed paths of history as one.

The big question is whether it is consistent to do this.

If we can maintain the fiction that we can course grain things, then we can transport our simple description forward in time. However, if the actual time evolution of the system causes the course graining to fall apart, then we may no longer have a simple description.

Example: Pythagorean Theorem

In meta mathematics, there are many different ways to formulate the Pythagorean theorem using different definitions and axiom systems.

Each formulation can be brought together and considered as just the Pythagorean theorem.

However, if a deduction based on a specific formulation is affected by which model was used in formulating it, then we would no longer have an aggregate thing that we can think about.

Implications for Physics

The fact that our simple description as abstracting observers can be transported forward in time is a fact about physics but may not always be true.

It could be possible that even at an aggregate level, there's no simple description for a system due to its complex time evolution.

The Observer and Aggregated Descriptions

In this section, the speaker discusses how the observer chooses to make an aggregated description of things and how there are infinite possible descriptions that can be made.

Aggregated Descriptions

The observer is choosing to make an aggregated description.

There is an underlying thing viewed from the outside.

There are infinite possible aggregated descriptions that can be made.

Assumptions About the Observer

In this section, the speaker talks about how certain assumptions about the observer can lead to deductions about what they can observe.

Deductions About What Can Be Observed

If you assume that the observer is computationally bounded and persistent in time, it follows that space-time must follow Einstein's equations for general relativity.

It also follows that the multi-way graph for the universe must follow final path integral rules for quantum mechanics.

Quantum mechanics and nondeterministic Turing machines are traditionally not defined in the same way.

The multi-base systems described are not exactly the same formulas as those used in physics for quantum mechanics and quantum computers.

Quantum Mechanics and Multi-Way Space

In this section, the speaker discusses how quantum mechanics relates to multi-way space.

Quantum States and Amplitudes

A full quantum state is a slice across a multi-way graph.

Superposition is just considering two threads together in a multi-ray graph.

Position in branching space is quantum phase.

Magnitude of a quantum amplitude is just path counting of how many different ways there are to reach a particular place in branchial space.

Branchial Space

Branchial space is a different kind of space than physical space.

It is defined by entanglements and common ancestries of different states.

The limit of the branchial graph is what we call branchial space.

Destructive Interference

Destructive interference happens when photons can go through two slits.

Two possibilities end up at opposite ends of branch hill space.

No observer will knit together those two completely separated pieces of branchial space.

Quantum Circuit Optimization and Phonons

In this section, Stephen Wolfram discusses the possibility of using quantum circuit optimization on multi-way graphs to prove that it is the same as traditional quantum mechanics. He also talks about the potential for using phonons in quantum computing.

Quantum Circuit Optimization

Quantum circuit optimization can be done using theorem proving methods on multi-way graphs.

Gates are not Hamiltonians, but a complicated limit from taking the step-by-step in time Hamiltonian of evolution for a quantum system and turning that into a gate.

Multi-way systems package the universe into each node of the multi-way system, which is like quantum mechanics.

Phonons in Quantum Computing

Phonons are quasi-particles used to describe the movement of sound to solid objects.

Traditional methods for making quantum computers do not relate to phonons, but there is no reason why they couldn't be used.

The main issue with phonons is that interaction between them is needed to make something that actually does computation.

Computation can be made out of almost anything, and a universal computer can undoubtedly be made out of phonons.

Multibase Systems and Quantum Field Theory

In this section, Stephen Wolfram discusses multibase systems and how they relate to quantum field theory.

Multibase Systems

Would phonons be better described using multibase systems?

Hypergraphs are limiting structures that do not necessarily correspond to integer dimensional space. Calculus is built only for interdimensional space.

Building a Bridge Between Computational Models and Human Understanding

In this section, Stephen Wolfram discusses the challenge of bridging the gap between computational models and human understanding. He explains that while computers can perform complex computations, humans need a way to understand these computations in a way that makes sense to them.

The Role of Mathematics in Bridging the Gap

Mathematics has been used for centuries as a way to describe complex models.

Wolfram's work involves building a computational language that serves as a bridge between what we think about with our brains and what is possible to do computationally.

While AI systems can perform complex computations, they are limited by their programming and cannot go beyond their set parameters.

Exploring the Space of Possible Simple Games

Mathematics is essentially the space of all possible simple games.

Human mathematics is limited by our ability to discover simple games using our brains.

AIs have access to all possible simple games but struggle with connecting it to human understanding.

The Future of Science and Technology

We are at the threshold of building systems where humans don't need to tinker anymore but can automate exploration beyond what Mathematica is doing.

Making AIs powerful enough to discover all of science is almost trivial; the challenge lies in making a bridge between what we care about and what AIs can compute.

The Discovery of Quantum Mechanics

In this section, the speaker discusses the discovery of quantum mechanics and how it was influenced by the invention of electronic amplifiers.

The Influence of Electronic Amplifiers on Quantum Mechanics

Electronic amplifiers were invented, allowing small signals to be amplified.

This led to the discovery of quantum mechanics and features of the world that were previously unknown.

The progress of science and technology involves noticing physical effects in the world and building technology stacks on top of them.

Identifying Useful Features in the World

In this section, the speaker discusses identifying useful features in the world and building technology stacks on top of them.

Protein Folding as an Example

There may be words for describing features in the world that we should have noticed but didn't, such as motifs in protein folding.

Once these motifs are identified, they can be used to describe how a protein will fold.

Image identification networks make distinctions that we don't currently have words for.

Agency and Perspective

In this section, the speaker discusses agency and perspective when it comes to understanding artificial intelligence (AI).

Understanding AI from a Human Perspective

It's problematic to not understand what an AI is doing or connect it to anything humans are doing.

Physicists may say that mathematical concepts are correct but irrelevant if they cannot connect them to anything their community is doing.

The speaker's perspective is part of a larger perspective that is multi-way and involves many ideas.

There will be intermediate steps in understanding AI that we don't get until we ask the AI to explain it to us.

The universe is mostly intelligible, but sometimes it's difficult to make ends meet. Ultimately, what matters is what changes can be produced in the universe.

The Intelligibility of the Universe

In this section, the speaker discusses the idea that the universe is intelligible and how it can be consistently described at a certain level of description.

The Universe as Intelligible

The universe as we observe it can be intelligible to us as observers.

With our methods of observation, we can consistently describe the universe at a certain level of description.

There is not a consistent type of description for the whole universe given any kind of observer. However, there is consistency in describing the universe at a certain level.

Expanding Our Domain in Physical Space

In this section, the speaker talks about expanding our domain in physical space and how it relates to exploring knowledge.

Expanding Our Domain in Physical Space

As we explore physical space, we are expanding our domain and trying to expand our knowledge.

The speaker wants to come back to discussing AI and minds later on.

Why This Rule for the Universe?

In this section, the speaker discusses why there is a particular rule for the universe and not another one.

Applying All Possible Rules Everywhere

Instead of having one particular rule for the universe, imagine applying all possible rules everywhere you can.

Even though you might think that applying all possible rules would result in complete structurelessness, it actually results in structure due to equivalence between different rules.

Slicing All Possible Computations

Looking at all possible computations run from all possible initial conditions for an infinite time results in an object that is the entangled limit of all possible computations.

This object can be sliced in many different ways, with one typical slice being looking at it progressing through time.

Uncertainty and Finiteness of Scientific Induction

There is a limit to determining which particular rule the universe is using due to the finiteness of scientific induction within a finite number of experiments.

However, there are still many things that we can say about the universe that don't depend on exactly where we are in real space and how big the cloud of possible rules is.

Rural Space and the Universe

In this section, the speaker discusses how our understanding of the universe is shaped by our existence in a particular place in rural space. He also explores how extraterrestrial aliens may have a different description of the universe due to their existence in a different part of rural space.

Description of Rural Space

Our understanding of the universe is influenced by our existence in a particular place in rural space.

Extraterrestrial aliens living in a different part of rural space would have an utterly incoherent description of the universe compared to ours.

The causal mechanism we use to describe the brain and control hierarchy we discover in the universe are unique to our existence in this part of rural space.

Different Parts of Rural Space

It's difficult to conceptualize what other parts of rural space are like since it requires making a jump that's equivalent to 100,000 human paradigm shifts away.

There seem to be constraints on what can exist based on how we operate. For instance, there could be no planetary surfaces in 4D because there can be no stable orbits.

Beings that live on planetary surfaces are contingent on living in a subset of bullied space that can be described as a curved 3D universe.

Observers and Shared Language

Observers from other areas may not form the same mathematics as us, making it impossible for us to translate their observations into something meaningful.

Motion is another example where pure motion may not exist when describing how objects move from one place to another.

Our constraints as observers give us some pretty big pieces of physics, and we only need those constraints qualitatively to understand why something like that might be true.

Translation between Cognitive Models

In this section, the speakers discuss the challenges of translating cognitive models from one system to another. They explore the difficulties in describing concepts that do not have a direct translation and how this affects our ability to understand and interpret different systems.

Challenges of Translating Cognitive Models

The difficulty in translating cognitive models arises when there are concepts that do not have a direct translation.

While some aspects of physics like gravity can be translated, other concepts may require grinding down to machine code before building back up again.

The challenge is finding a description language that is useful and faithful while also connecting with humans.

It is unclear how we can translate what's going on inside neural networks into our way of describing things.

Identity and Multi-Year Modeling

In this section, the speakers discuss identity and multi-year modeling. They explore how identity does not exist beyond projection and how we construct continuity between different selves.

Constructing Continuity Between Different Selves

When projecting ourselves through space, identity does not exist beyond projection.

Continuity between different selves is constructed by having similar configurations as self-reflecting observers who tell stories using similar concepts.

Transporting oneself between dream self and day self or selves at different times in life requires constructing continuity using similar relational primitives.

The question is whether underlying rules are so similar that we can identify what is being translated.

Identifying Relevant Lumps in the Ocean of Computation

In this section, Stephen Wolfram discusses the purpose of creating a computational language that can identify relevant lumps in the ocean of computation that are significant and important to humans at this time in history.

Computational Language for Humans

The goal is to create a computational language that cuts across a decent swath of different use cases of humans.

There could be a computational language for the 30-year-old me, one for the 40-year-old me, etc., but it's more useful to have something that allows you to merge between those kinds of things.

Multi-Way Systems and Multiple Paths

Our brains are full of 100 billion neurons that are all firing and doing all kinds of things yet we have this perception that there is a definite thread of attention consciousness whatever we call it.

The mind is like a measuring device that is somehow taking these different threads and conflating them together.

The intermediate language of neuroscience beyond the level of saying "there are 100 billion neurons firing at a time" needs further exploration.

Mind as a Multi-Branched System

In this section, Stephen Wolfram discusses how our minds work as multi-branched systems where we go through multiple potential states before collapsing into definite representations.

Collapse as an Interesting Concept

The notion of collapse is super important and interesting.

Is it just the states where branches merge in the branch shield space state face or is there something more going on?

Quantum Mechanics Formalism for Mental States

Jerome Bosemeyer believes our mental states are best described using the formalism of quantum mechanics not because he believes our brain is literally a quantum computer but because of superpositional states in our thoughts and mental representations that then collapse into definite representations.

The mind is a multi-base system in which we go through a multitude of potential states and then collapse.

Unconscious vs Conscious

In the unconscious, there's all this stuff bubbling around, all these different paths being followed, and somehow our thread of attention picks out this one path.

The mechanisms by which the mind does this are not yet fully understood.

The Role of Formalism in Different Fields

In this section, Stephen Wolfram discusses the role of formalism in different fields and how it can be used to create an intermediate language.

Formalism in Physics

Physics has been a successful formalized field that has ingested lots of fancy mathematics.

Most other fields have not done that and most people who work in other fields really don't know that there's a big tower to climb instead of the formalism of existing mathematics.

Challenges in Other Fields

Many fields require formalism that is not the same kind as elementary mathematics.

There are different parts of the population space by humans, and sometimes you need to travel from one part to another.

Foundations for Towers of Mathematical Physics

Our physics project provides foundations for many towers of mathematical physics built over the last 50 years.

People can see the attachment between their towers and our models, making it meaningful even if they don't necessarily understand the full story.

Applying Formalism to Other Fields

Our methods can be used for quantum circuit optimization or making models for numerical general relativity without believing in our models' ontology.

Our formalism can provide intuition from physics to all these other fields.

Using Formalism to Study Neuroscience and AI

In this section, Stephen Wolfram talks about using his team's formalism to study neuroscience and AI.

Using Physics as a Foundation

The team gets to use physics because their formalism applies to physics, and they get to import the intuition from that giant tower to all these other fields.

Separate Towers

The team's towers are not built on their foundation for the most part in their intellectual traditions.

Christian civilization destroyed our ability to construct a rational model of reality, and in some sense, our sciences started out with fake.

The Integration of Science and Philosophy

In this section, the speaker discusses how science and philosophy have stopped looking for systemic models and instead have built separate towers that are largely incompatible.

Postmodernism and the End of Systemic Models

After the end of modernism, philosophy stopped having systemic models.

Instead of building a joint tower of babel, we now have lots of different towers that exist next to each other.

There is a lot of overlap between econ and computer science, with many algorithms discovered by economicalists being rediscovered in AI.

Neuroscience has also invented its own tools to deal with statistics.

Integrative Forces in Science

Computation and multi-computation are integrative forces in science.

Computation leads to lots of integration, while multi-computation leads to another level of integration.

Multi-computational processes allow observers to make predictive statements that correspond to core results in physics.

Historical Context

Many questions addressed by computational irreducibility were thought about by theologians and philosophers hundreds or thousands of years ago.

Mathematical notation was invented 400 years ago, leading to integration across many fields.

The particulars of mathematical science were so successful that they whizzed off into their own discussion, leaving behind questions about why the universe exists.

Common Underlying Framework

Having a common underlying framework allows for interplay between different fields.

Without a common underlying formalism, it is difficult to make connections between different fields.

Understanding Different Fields

In this section, Stephen Wolfram talks about his level of understanding in different fields and how he tries to apply the same innovation methodology to basic science that he has applied to technology development.

Applying Innovation Methodology to Basic Science

Stephen Wolfram has some level of understanding in lots of different fields.

He tries to apply the same innovation methodology to basic science that he has applied to technology development.

The physics project is an example of applying the same kind of innovation methodology to basic science.

There is a huge expansion of their product line in a sense that they are seeing connections between different fields such as chemistry, economics, and linguistics.

They are launching the Wolfram Institute construct as a vehicle for having organized exploration of all those different kinds of things.

Organizational Question

In this section, Stephen Wolfram asks about the interviewer's schedule and suggests wrapping up soon. They briefly discuss an interesting question about making measurements inside the mind and inside physics.

Making Measurements Inside the Mind and Inside Physics

Stephen Wolfram asks about the interviewer's schedule and suggests wrapping up soon.

The interviewer asks an interesting question about what it means to make a measurement inside of the mind and inside of physics.

Stephen Wolfram does not know the answer but thinks it is an interesting question.

He discusses how our brains have definite structures that try to maintain attention and single-threadify things, which is similar to attractors in any kind of system.

They have been looking at raw material for making a theory, such as the world's most complete collection of units that people use to measure things and a good inventory of measuring devices.

Understanding Quantum Computing

In this section, the speaker talks about the process of turning degrees of freedom of molecules into larger inertia degree of freedom and how it relates to quantum computing. The speaker also discusses the question of what is inside a quantum computer and how it can be measured.

Turning Degrees of Freedom into Larger Inertia Degree

The story is about turning lots of degrees of freedom of the molecules into one larger inertia degree.

The speaker does not know how this generalizes and would like to understand what kind of thing measurement might be.

What is Inside a Quantum Computer?

There's a question about what's inside a quantum computer.

It could be an ion trap, neutral atoms, or some squid type thing with superconductors.

There's a cascade of measurement that happens in quantum computing. The speaker was interested in understanding what's really going on and what's the qualitative story behind it.

Closing Remarks

The speaker thanks everyone for attending and apologizes for not being able to take questions from the audience due to multitasking.

Tanya goes through some questions from the chat, including one about predictions that can be made from computational models and another about explaining existing physics theories such as relativistic physics emerging from quantum mechanics.

Non-deterministic Turing machines go into all possible states at once, which means that if you are free to ignore how long it takes in your substrate, you can go through all these states simultaneously.

Overall, this section provides insights into understanding quantum computing by discussing turning degrees of freedom into larger inertia degree, what is inside a quantum computer, and the cascade of measurement that happens in quantum computing. The section ends with closing remarks from the speaker and a summary of questions from the chat.

Implications of Multi-Computation Theory for AI Learning

In this section, the speaker discusses the implications of Stephen's theory of multi-computation for AI learning. The nature of learning is explored, and the question is raised as to whether it is an additive process or one that necessarily implies losing something as we acquire a new distinction.

Nature of Learning

The frameworks located in different parts of the neural system can require hundreds of thousands of paradigm shifts to get to a new distinction.

Is learning an additive process? Does it imply losing something as we acquire a new distinction?

Our minds will only approximate multivariate systems if there are multiple systems. What is the better approximation?

Stephen's Work and Its Reception by Scientists

This section focuses on Stephen's work and how it has been received by scientists. The speaker notes that Stephen is doing excellent work but is not being given enough credit.

Reception by Scientists

People compare him to the whole of physics that he is trying to displace with his work and not individual physicists.

He is acting as if he is giving a new foundation to scientists, but they are not taking it from him.

It's regrettable that there is no direct link and interaction between his ideas and what's happening.

Multiverse Systems in Our Mind

In this section, the speaker explores whether our mind can be considered a multi-base system and how much complexity can be stored in activation states of neurons.

Multiverse Systems in Our Mind

Our mind can be considered a multi-base system, but it's probably a leaky one.

There is a certain saturation that you can have in the activation of neurons, and there is a boundary to the information content in your brain at any given time.

People end up with different descriptions, and our minds will only approximate multivariate systems if there are multiple systems.

Resources for Understanding Multiverse Systems

This section provides resources for understanding multiverse systems and the branchial space concept.

Resources

Links to Steve's posts on multiverse systems on the wall are provided and are very helpful to understanding what he means by the branchial space concept.

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