- The speaker believes that every star has planets with emerging life, but the ability to communicate with alien life may be difficult due to different causal cones.
- The speaker expresses the need to create alien life in the lab to build architectures that can intersect with alien intelligence.
- The conversation transitions to discussing assembly theory, which quantifies the complexity of objects by determining the number of steps it took to create them and if they were built through a process similar to evolution.
- An object is defined as finite, countable, decomposable, and having a set of constraints to construct it from elementary building blocks.
- The assembly index is the minimum number of steps needed to reproduce an object by adding its parts together.
- The speaker explains that the assembly index can be measured for molecules by breaking them apart and reassembling them, and this can also be done for language and mathematical theorems.
- The computational complexity of determining the shortest path to construct an object varies depending on its size, but shortcuts and physical measurements can be utilized.
- The speaker discusses using mass spectrometry techniques, such as infrared and nuclear magnetic resonance, to correlate data with the assembly index for molecules.
- The applicability of these shortcuts to chemistry and beyond is still being explored, as the assembly theory paper aims to provide a general theory of objects in the universe.

- The speaker is working on assembly theory of emoticons, where they pixelate emojis and calculate the assembly index of each emoji.
- They are trying to determine the spatial data of emojis and how many can be made on the path of emoji.
- The speaker explains the process of computing the assembly index of a graphical object by determining resolution, surface area, and adding pixels together.
- Assembly theory involves the assembly universe, assembly possible, assembly contingent, and assembly observed, which represent different scales in the combinatorial universe.
- The speaker emphasizes that assembly theory is not about compression but about the amount of information required in a chain of events.
- They discuss how the universe must construct a system that allows for selection and the emergence of a factory-like environment.
- The shortest path in building molecules is important as it represents the minimal amount of information required to propagate a motif in time and space.
- The speaker acknowledges that there are other driving forces and compromises in assembly, but overall efficiency is still a key factor.

- The speaker discusses the concept of nesting in construction and how it relates to efficiency.
- They mention the idea of parallelization in complex objects and the need to understand parallel processes.
- The speaker introduces the concept of assembly depth and its relationship to assembly index in molecules.
- They speculate about applying these concepts to economic processes and the limitations of capitalism.
- The speaker discusses the reactions and criticisms received for their paper on selection and evolution.
- They explain the definition of selection as the ability of an object to persist in an environment over time, while being continually destroyed and made by processes.

- The concept of selection and evolution requires turnover in time and the continuous production of objects
- The environment acts as the factory in the process of selection and evolution
- In biology, selection and evolution are robust, allowing for survival in various environments
- The assembly equation can be used to measure the amount of selection occurring in a system
- The assembly index can be used to identify artifacts produced by life, such as molecules with high molecular weight and multiple fragments
- The number of copies of a molecule indicates its complexity and structure
- The concept of identical molecules depends on the detection system and resolution used.

- The speaker discusses the art and science of choosing a detection system when exploring new planets.
- They mention the use of standardized detection systems for comparing molecules and the need to consider different scales and levels of complexity.
- The speaker suggests using mass spectrometry and sampling techniques to search for evidence of primitive life on planets like Mars or Titan.
- They propose the idea of a "life meter" that can detect complex molecules and potentially living cells.
- The speaker explains the process of using mass spectrometry and infrared analysis to measure complexity and abundance in samples.
- They emphasize the importance of looking for complexity without bias towards Earth chemistry or biology.
- The speaker mentions their previous experiments with prebiotic chemistry and the extraction of volatile molecules from inorganic minerals and whiskey samples.

- The speaker discusses the process of using mass spectrometry to measure the assembly index of various samples, including whiskey, beer, E. Coli, and samples from NASA.
- The assembly index is a measure of molecular complexity, with higher assembly indices indicating better quality.
- The speaker successfully identified living and non-living samples based on their assembly indices.
- The speaker also mentions using assembly theory to map the tree of life without gene sequencing, by analyzing coexisting molecules and their joint assembly space.
- The speaker suggests using assembly theory to study old fossil samples and potentially discover new forms of life that cannot be sequenced using DNA.

- The speaker discusses the concept of using assembly theory to date death and trace the tree of life.
- They mention the possibility of using carbon-13 levels to estimate the age of living organisms.
- The speaker acknowledges criticism of their paper on assembly theory, particularly from evolutionary biologists and physicists.
- They argue that the origin of life is not a solved problem and that time is fundamental in the universe.
- The speaker defends their paper, stating that it presents a concrete and testable theory that can be built upon or disproven.
- They address criticism that their ideas are not new or obvious, emphasizing that their approach quantifies selection, complexity, and copy number in a novel way.

- The speaker believes that every star has planets with emerging life, but communicating with alien life may be difficult due to different causal cones.
- The speaker emphasizes the need to create alien life in the lab to understand and intersect with alien intelligence.
- Assembly theory quantifies the complexity of objects by determining the number of steps it took to create them and if they were built through a process similar to evolution.
- The assembly index measures the minimum number of steps needed to reproduce an object by adding its parts together.
- The computational complexity of determining the shortest path to construct an object varies depending on its size, but shortcuts and physical measurements can be utilized.
- Mass spectrometry techniques, such as infrared and nuclear magnetic resonance, can be used to correlate data with the assembly index for molecules.
- Assembly theory aims to provide a general theory of objects in the universe, applicable to chemistry and beyond.
- The speaker is working on assembly theory of emoticons, calculating their assembly index and spatial data.
- Assembly theory involves different scales in the combinatorial universe and is about the amount of information required in a chain of events, not compression.
- Selection and evolution require turnover in time and the continuous production of objects, with the environment acting as the factory.
- The assembly equation and index can be used to measure selection and identify artifacts produced by life.
- Mass spectrometry and sampling techniques can be used to search for evidence of primitive life on other planets.
- The speaker suggests using mass spectrometry and infrared analysis to measure complexity and abundance in samples without bias towards Earth chemistry or biology.
- Assembly theory can be used to map the tree of life, date death, and potentially discover new forms of life that cannot be sequenced using DNA.
- The speaker defends their paper on assembly theory, stating that it presents a concrete and testable theory that quantifies selection, complexity, and copy number in a novel way.

- The speaker discusses the application of assembly theory to various levels of complexity, from molecules to cells to multicellular creatures.
- They mention the potential application of assembly theory to different types of diseases and cultural phenomena such as language and images.
- The speaker emphasizes the need for a common set of building blocks and the understanding of the anatomy and features of different organisms.
- They suggest using machine learning and image recognition to discover and measure features in assembly theory.
- The speaker also discusses the potential application of assembly theory to technology, such as microprocessor architecture.
- They mention the possibility of using assembly theory to analyze language models and embed more intelligence in them.
- The speaker discusses the relationship between selection and intelligence, as well as the potential for assembly theory to measure higher-level evolution.
- They differentiate assembly theory from Kolmogorov complexity, which requires a computer and a Turing machine.

- The speaker discusses the differences between Komagolov complexity and assembly theory.
- Komagolov complexity is about compressing data sets, while assembly theory focuses on the process of life evolution.
- Assembly theory looks at objects and infers their history based on the shortest path.
- It allows for the understanding of how deep an object is in time and the existence of a process.
- Assembly theory can be applied to drug discovery by focusing on molecule evolution rather than protein evolution.
- It does not require simulating all of chemistry, but instead focuses on minimal constraints on the graph.
- The speaker argues that chemical reactions do not exist, but rather it is the application of constraints that enables transformations.
- Assembly theory provides a way to understand the emergence of transformations.

- The speaker discusses the use of chemical reactions as a shorthand in chemistry and how they are assumed to be applicable in natural language conversation.
- They mention the emergence of grammar in chemistry through reactions, but doubt the accessibility of certain reactions on Venus.
- The speaker talks about the process of rewriting and editing their paper for publication, including removing equations and receiving critical feedback from reviewers.
- They reflect on the psychological impact of the rejection and the determination to continue pushing for publication.
- The speaker shares their personal experience with learning difficulties and the desire to prove their intelligence, relating it to their persistence in arguing their case with editors and reviewers.
- They mention a previous paper that went through multiple rounds of review and rejection before being published elsewhere.
- Ultimately, the speaker's paper was accepted for publication, which they find cool.

- The speaker's paper was unexpectedly accepted and published, leading to backlash
- The editor reassured the speaker that the paper was great and controversy is part of scientific discourse
- The speaker sees the backlash as a positive sign that the paper is making an impact
- The paper introduces a new approach to understanding biological evolution
- The speaker reflects on their struggles with learning difficulties in school
- Despite challenges, the speaker persisted and pursued their passion for science
- The speaker encourages others not to give up and believes in the value of curiosity and perseverance
- The speaker enjoys being around smart people and finds value in confusing them with their ideas
- The speaker values constructive criticism and seeks consistent reasons for disagreement
- The speaker appreciates the opportunity to have new ideas in academia.

- The speaker values constructive criticism and believes it is important for nurturing new ideas.
- They have had the support of colleagues, collaborators, funders, and mentors who provide actionable criticism to improve their work.
- The speaker engages in critical discussions with others to refine their ideas and make them better.
- They discuss the concept of time and its fundamental role in assembly theory.
- They mention a mathematical argument about free will and the need for time to be fundamental.
- The speaker argues that the universe cannot contain the future and that time is fundamental because the law of the excluded middle does not apply to the future.
- They discuss the idea that Earth is the largest place in the universe due to the complexity and evolution of life on our planet.
- The speaker expresses concern about the possibility of not being able to intersect with alien intelligence due to the vastness of combinatorial space.

- The speaker discusses the idea of creating a planet simulator and the potential for communicating with other life forms.
- They propose creating different types of life based on known constraints and using this knowledge to search for other life in the universe.
- The speaker suggests that intelligence allows for the recognition of regularities in the universe and the potential for communication with aliens.
- They acknowledge the vastness and complexity of the universe but argue that it is still possible for life forms to detect each other.
- The speaker also discusses the concept of time and its relationship to the precision of initial conditions in determining the future of the universe.

The speaker discusses the application of assembly theory to various levels of complexity, from molecules to cells to multicellular creatures. They mention the potential application of assembly theory to different types of diseases and cultural phenomena such as language and images. The speaker emphasizes the need for a common set of building blocks and the understanding of the anatomy and features of different organisms. They suggest using machine learning and image recognition to discover and measure features in assembly theory. The speaker also discusses the potential application of assembly theory to technology, such as microprocessor architecture. They mention the possibility of using assembly theory to analyze language models and embed more intelligence in them. The speaker discusses the relationship between selection and intelligence, as well as the potential for assembly theory to measure higher-level evolution. They differentiate assembly theory from Kolmogorov complexity, which requires a computer and a Turing machine. The speaker discusses the differences between Komagolov complexity and assembly theory. Komagolov complexity is about compressing data sets, while assembly theory focuses on the process of life evolution. Assembly theory looks at objects and infers their history based on the shortest path. It allows for the understanding of how deep an object is in time and the existence of a process. Assembly theory can be applied to drug discovery by focusing on molecule evolution rather than protein evolution. It does not require simulating all of chemistry, but instead focuses on minimal constraints on the graph. The speaker argues that chemical reactions do not exist, but rather it is the application of constraints that enables transformations. Assembly theory provides a way to understand the emergence of transformations. The speaker discusses the use of chemical reactions as a shorthand in chemistry and how they are assumed to be applicable in natural language conversation. They mention the emergence of grammar in chemistry through reactions, but doubt the accessibility of certain reactions on Venus. The speaker talks about the process of rewriting and editing their paper for publication, including removing equations and receiving critical feedback from reviewers. They reflect on the psychological impact of the rejection and the determination to continue pushing for publication. The speaker shares their personal experience with learning difficulties and the desire to prove their intelligence, relating it to their persistence in arguing their case with editors and reviewers. They mention a previous paper that went through multiple rounds of review and rejection before being published elsewhere. Ultimately, the speaker's paper was accepted for publication, which they find cool. The speaker's paper was unexpectedly accepted and published, leading to backlash. The editor reassured the speaker that the paper was great and controversy is part of scientific discourse. The speaker sees the backlash as a positive sign that the paper is making an impact. The paper introduces a new approach to understanding biological evolution. The speaker reflects on their struggles with learning difficulties in school. Despite challenges, the speaker persisted and pursued their passion for science. The speaker encourages others not to give up and believes in the value of curiosity and perseverance. The speaker enjoys being around smart people and finds value in confusing them with their ideas. The speaker values constructive criticism and seeks consistent reasons for disagreement. The speaker appreciates the opportunity to have new ideas in academia. The speaker values constructive criticism and believes it is important for nurturing new ideas. They have had the support of colleagues, collaborators, funders, and mentors who provide actionable criticism to improve their work. The speaker engages in critical discussions with others to refine their ideas and make them better. They discuss the concept of time and its fundamental role in assembly theory. They mention a mathematical argument about free will and the need for time to be fundamental. The speaker argues that the universe cannot contain the future and that time is fundamental because the law of the excluded middle does not apply to the future. They discuss the idea that Earth is the largest place in the universe due to the complexity and evolution of life on our planet. The speaker expresses concern about the possibility of not being able to intersect with alien intelligence due to the vastness of combinatorial space. The speaker discusses the idea of creating a planet simulator and the potential for communicating with other life forms. They propose creating different types of life based on known constraints and using this knowledge to search for other life in the universe. The speaker suggests that intelligence allows for the recognition of regularities in the universe and the potential for communication with aliens. They acknowledge the vastness and complexity of the universe but argue that it is still possible for life forms to detect each other. The speaker also discusses the concept of time and its relationship to the precision of initial conditions in determining the future of the universe.

- The speaker believes in free will and therefore believes that time is fundamental.
- They argue that a deterministic universe without time would mean no free will.
- The speaker wants to prove that time is fundamental and that the universe generates novelty.
- They disagree with the concept of a Boltzmann brain and argue that it neglects the causal chain of evolution.
- The speaker discusses the origin of novelty and suggests that it is not about randomness but about constrained opportunity.
- They believe that life is a novelty miner from the future that is actualized in the present.
- The speaker argues that the universe is deterministic in the past but undetermined in the future.
- They propose that the breakdown in precision in initial conditions leads to a non-determined future.
- The speaker wants to crack the non-life to life transition and understand the mechanism behind it.
- They believe that the future is bigger than the past and that the universe should be able to contain the future.

- The speaker discusses the concept of assembly theory and how it relates to the complexity of molecules and evolutionary processes.
- They mention that taxol, a complex natural product, was an accidental invention by biology and is unique to Earth.
- Cellular automata (CA) are also discussed, with the speaker questioning how they can produce complexity with basic rules and initial conditions.
- The speaker suggests that CAs are evidence that the universe is too big to contain itself and that there is space for creativity and unpredictability.
- They also discuss the concept of time as a fundamental resource and its role in generating complexity.
- The speaker expresses frustration with the current AI doomsday scenario, stating that AGI is far away and the concerns are exaggerated.
- They argue that the AI doomers lack the correct understanding of knowledge and epistemology.
- The speaker concludes that while AI tools are powerful, we need to be cautious in their use to avoid manipulation and fakery.

- The speaker discusses the percentages of individuals who believe in AGI doom, with Yudkowsky at 95% and Scott Aronson at 2%.
- They argue that a 2% chance of doom is not significant enough to warrant concern.
- The speaker believes that AGI doom is unlikely and that human decision-making is essential, as AI lacks true decision-making abilities.
- They highlight the limitations of AI intelligence and argue against the idea of superintelligence.
- The speaker emphasizes the importance of unintended consequences and the need to consider the potential harm caused by highly capable AI systems.
- They criticize the paperclip scenario as unrealistic and discuss the limitations of resource availability for AI.
- The speaker compares the interplay between evolution and propagation in nature to the potential risks of AI.
- They suggest that a consensus should be established to prevent the development of harmful AI technologies.
- The speaker questions the motivations of those who propagate AGI doom and argues against baseless claims of human extinction.

- The speaker believes that there is a role for people who emphasize the potential dangers and threats in society, as it helps create proper concern and awareness.
- The speaker expresses concern about the lack of attention given to the threat of nuclear weapons and the potential for a world war.
- The speaker discusses the idea of AI doomers and the potential for unintended consequences and suffering if AI is not handled properly.
- The speaker suggests the idea of using AI to regulate world politics and distribute nuclear weapons in order to reduce war and conflict.
- The speaker acknowledges the possibility of bad actors and terrorist organizations taking advantage of distributed nuclear weapons.
- The speaker proposes burning nuclear material for energy and creating a virtual simulation to deter the use of nuclear weapons.
- The speaker discusses the concept of a chemical brain as a mechanism for creating conscious AI.
- The speaker believes that current hardware architectures and obsession with data and dopamine hits limit true intelligence.

- The speaker reflects on how easily fooled they are and questions the intelligence of the brain.
- They discuss the brain's ability to integrate information across domains and generate knowledge.
- They argue that AI lacks the ability to generate universal explanations and is limited to inductive thinking.
- The speaker wonders what makes the human mind capable of creating generalities and novelty.
- They discuss the potential for future language models to impress with humor and insights, but question if they can truly generate something novel.
- The speaker suggests that current machine learning technologies may help reveal the fundamental nature of time.
- They discuss the role of humans in training and correcting language models, and the limitations of AI in generating algorithms and reasoning.
- The speaker proposes using gel as hybrid hardware for processing information and training models more efficiently.
- They discuss the difference between trial and error and the generation of new knowledge.
- The speaker questions the misappropriation of the term "artificial intelligence" and argues that models lack reasoning and intention.
- They express the desire for superintelligence that can generate fundamental new ideas and truly novel outputs.
- The speaker acknowledges that current language models can produce shallow novelty, but argues that true novelty comes from the human mind.
- They reflect on the limitations of AI and the continued importance of human intelligence.

- The speaker has been using chat GPT and found it initially cool but later time-consuming to correct. They mention that recent changes to the system are not good and may involve censorship.
- The speaker is interested in characterizing novelty and differentiating it from interpolation.
- They discuss their work in using a GPT-like system to generate molecules based on electron density data. They explain the process of training the model and generating molecules that can bind to hosts.
- The speaker acknowledges that the generated molecules may not be truly novel but are new to them. They highlight the importance of different causal chains overlapping to generate genuine novelty.
- They express concerns about the limitations and potential consequences of AI systems, particularly in the context of social media. They mention the need for authenticated users and data, and the importance of ethics in their work.

- The speaker believes in free will and argues that time is fundamental for it.
- They disagree with the concept of a Boltzmann brain and discuss the origin of novelty.
- The speaker believes that the universe is deterministic in the past but undetermined in the future.
- They discuss the complexity of molecules, cellular automata, and the role of time in generating complexity.
- The speaker expresses skepticism towards the AI doomsday scenario and emphasizes the importance of human decision-making.
- They highlight the limitations of AI intelligence and the need to consider unintended consequences.
- The speaker suggests establishing a consensus to prevent the development of harmful AI technologies.
- They propose using AI to regulate world politics and distribute nuclear weapons to reduce conflict.
- The speaker discusses the limitations of current hardware architectures and the potential of gel as hybrid hardware.
- They question the true nature of artificial intelligence and emphasize the importance of human intelligence.
- The speaker discusses their work in using a GPT-like system to generate molecules and express concerns about the limitations and consequences of AI systems.

- The speaker believes that AI systems are like tools and can provide meaningful experiences, but they do not possess sentience or legal rights.
- The concept of God is seen as a creation of the human mind, similar to the concept of super intelligence.
- The universe is believed to have a creative force, but it is not sentient.
- The speaker is an atheist but not an angry one, and has faith in certain things.
- Selection is seen as the force in the universe that creates novelty.
- Free will is believed to occur at the boundary between the past and the future.
- Imagination is seen as having a causal effect on the future, which is intriguing and breaks the laws of physics.
- The speaker finds beauty in the undecided and open nature of the universe, and the pursuit of answers to endless questions.
- The idea of leaving a legacy and unpredictability in human interactions is valued.
- Life is seen as a process of selection that affects the universe, and universes with life are fundamentally different.
- Assembly theory is considered to be obvious in retrospect, but may require a new discipline in the future.

- The speaker is a fan of watching the person create things in the world
- The speaker thanks the person for talking and it is a pleasure for them
- The person being interviewed is Lee Cronin
- The podcast has sponsors that can be checked out in the description
- The video ends with a quote from Carl Sagan about progress and truth

The speaker discusses various topics including AI systems, the concept of God, the universe, free will, imagination, and the value of leaving a legacy. They express their atheism but have faith in certain things, and find beauty in the open nature of the universe. The speaker is a fan of watching people create things and thanks the person being interviewed, Lee Cronin. The podcast has sponsors and ends with a quote from Carl Sagan about progress and truth.

Lee Cronin is a chemist at University of Glasgow. Please support this podcast by checking out our sponsors:
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TRANSCRIPT:
https://lexfridman.com/lee-cronin-3-transcript

EPISODE LINKS:
Lee's Twitter: https://twitter.com/leecronin
Lee's Website: https://www.chem.gla.ac.uk/cronin/
Nature Paper: https://www.nature.com/articles/s41586-023-06600-9
Chemify's Website: https://chemify.io

PODCAST INFO:
Podcast website: https://lexfridman.com/podcast
Apple Podcasts: https://apple.co/2lwqZIr
Spotify: https://spoti.fi/2nEwCF8
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Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4
Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41

OUTLINE:
0:00 - Introduction
1:15 - Assembly theory paper
21:45 - Assembly equation
34:57 - Discovering alien life
53:16 - Evolution of life on Earth
1:01:12 - Response to criticism
1:18:50 - Kolmogorov complexity
1:30:40 - Nature review process
1:51:34 - Time and free will
1:57:59 - Communication with aliens
2:19:57 - Cellular automata
2:24:26 - AGI
2:41:15 - Nuclear weapons
2:47:00 - Chem Machina
2:59:54 - GPT for electron density
3:09:24 - God

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Every star in the sky probably has planets, and life is probably emerging on these planets.

But I think the commentarial space associated to these planets is so different.

Our causal cones are never going to overlap, or not easily.

And this is the thing that makes me sad about alien life, why it's why we have to create alien life in the lab as quickly as possible, because I don't know if we are gonna be able to build architectures that will intersect with alien intelligence architectures.

And intersect, you don't mean in time or space?

Yeah, my biggest fear in a way is that life is everywhere, but we become infinitely more lonely because of our scaffolding in that conventorial space.

The following is a conversation with Lee Cronin, his third time on this podcast.

He is a chemist from University of Glasgow who is 1 of the most fascinating, brilliant, and fun to talk to scientists I've ever had the pleasure of getting to know.

To support it, please check out our sponsors in the description.

And now, dear friends, here's Lee Cronin.

So your big assembly theory paper was published in Nature.

It created, I think it's fair to say, a lot of controversy, but also a lot of interesting discussion.

So maybe I can try to summarize assembly theory and you tell me if I'm wrong.

So assembly theory says that if we look at any object in the universe, any object, that we can quantify how complex it is by trying to find the number of steps it took to create it, and also we can determine if it was built by a process akin to evolution by looking at how many copies of the object there are.

So there's a central equation I'd love to talk about, but definition-wise, what is an object?

Yeah, an object, so if I'm gonna try to be as meticulous as possible, objects need to be finite, and they need to be decomposable into subunits.

So an object is finite and countable and decomposable, I suppose mathematically.

But yeah, I still wake up some days and go, to think to myself, what is an object?

Persists over time, I'm quoting from the paper here, an object that's finite is distinguishable, I'm sure that's a weird adjective, Distinguishable.

We've had so many people offering to rewrite the paper after it came out, you wouldn't believe it's so funny.

Persists over time and is breakable such that the set of constraints to construct it from elementary building blocks is quantifiable.

Such that the set of constraints to construct it from elementary building blocks is quantifiable.

So, okay, so what defines the object is its history or memory, whichever is the sexier word.

I'm happy with both, depending on the day.

Okay, so the set of steps it took to create the object, so there's a sense in which every object in the universe has a history.

And that is part of the thing that is used to describe its complexity, how complicated it is.

So the assembly index, if you're to take the object apart and be super lazy about it or minimal, say what it cause my, you know, it's like, you've got a really short term memory.

So what you do is you lay all the parts on the path and you find the minimum.

Number of steps you take on the path to add the parts together to reproduce the object and that minimum number is the assembly index, is a minimum bound.

And it was always my intuition the minimum bound in assembly theory was really important.

I only worked out why a few weeks ago which is kind of funny because I was just like no this is sacrosanct I don't know why it will come to me 1 day and then when I was pushed by a bunch of mathematicians we came up with the correct physical explanation which I can get to, but it's the minimum and it's really important, it's the minimum.

And the reason I knew the minimum was right is because we could measure it.

So almost before this paper came out, we'd published papers explaining how you can measure the assembly index of molecules.

Okay, so that's not so trivial to figure out.

So when you look at an object, we can say a molecule, we can say object more generally, to figure out the minimum number of steps it takes to create that object, that doesn't seem like a trivial thing to do.

So with molecules, it's not trivial, but it is possible because what you can do, and because I'm a chemist, so I'm kind of like, I see the lens of the world through just chemistry, I break the molecule apart and break bonds.

And if you take a molecule and you break it all apart, you have a bunch of atoms.

And then you say, okay, I'm going to then take the atoms and form bonds and go up the chain of events to make the molecule.

And that's what made me realize, take a toy example, literally a toy example, take a Lego object, which is broken up of Lego blocks.

In this case, the Lego blocks are naturally the smallest, they're the atoms in the actual composite Lego architecture.

But then if you maybe take a couple of blocks and put them together in a certain way, maybe they're offset in some way, that offset is on the memory.

You can use that offset again with only a penalty of 1, and you can then make a square, triangle, and keep going.

And you remember those motifs on the chain.

So you can then leap from the start with all the Lego blocks or atoms just laid out in front of you, and say, right, I'll take you, you, you, connect, and do the least amount of work.

So it's really like the smallest steps you can take on the graph to make the object.

And so for molecules, it came relatively intuitively, and then we started to apply it to language.

We've even started to apply it to mathematical theorems, But I'm so well out of my depth, but it looks like you can take minimum set of axioms and then start to build up kind of mathematical architectures in the same way.

And then the shortest path to get there is something interesting that I don't yet understand.

So what's the computational complexity of figuring out the shortest path with molecules, with language, with mathematical theorems?

It seems like once you have the fully constructed Lego castle or whatever your favorite Lego world is, figuring out how to get there from the basic building blocks isn't like a, is that an empty heart problem?

It's a heart problem, but actually If you look at it, so the best way to look at it, let's take a molecule.

So if the molecule has 13 bonds, first of all, take 13 copies of the molecule and just cut all the bonds, so cut 12 bonds, and then you just put them in order.

So, and you keep looking for symmetry or copies, so you can then shorten it as you go down, and that becomes, commentarily, quite hard.

For some natural product molecules, it becomes very hard.

It's not impossible, but we're looking at the bounds on that at the moment.

But as the object gets bigger, it becomes really hard.

And, but that's the bad news, but the good news is there are shortcuts.

And we might even be able to physically measure the complexity without computationally calculating it, which is kind of insane.

Well, in the case of molecule, so if you shine light on a molecule, let's take an infrared, the molecule has, each of the bonds absorbs the infrared differently in what we call the fingerprint region.

And so it's a bit like, because it's quantized as well, you have all these discrete kind of absorbances.

And my intuition after we realized we could cut molecules up in mass spec, that was the first go at this.

We did it with using infrared and the infrared gave us an even better correlation, assembly index, and we used another technique as well in addition to infrared called NMR, nuclear magnetic resonance, which tells you about the number of different magnetic environments in a molecule, and that also worked out.

So we have 3 techniques, which each of them independently gives us the same or tending towards the same assembly index for a molecule that we can calculate mathematically.

Okay, so these are all methods of mass spectrometry, mass spec, you scan a molecule, it gives you data in the form of a mass spectrum, and you're saying that the data correlates to the assembly index.

How generalizable is that shortcut, first of all to chemistry, and second of all, beyond that?

Because that seems like a nice hack and you're extremely knowledgeable about various aspects of chemistry so you can say, okay, it kind of correlates.

But the whole idea behind assembly theory paper and perhaps why it's so controversial is that it reaches bigger.

It reaches for the bigger general theory of objects in the universe.

So I've started assembly theory of emoticons with my lab, believe it or not.

So we take emojis, pixelate them and work out the assembly index of the emoji.

And then work out how many emojis you can make on the path of emoji.

So there's the uber emoji from which all other emojis emerge.

And then you can, so you can then take a photograph and by looking at the shortest path, by reproducing the pixels to make the image you want, you can measure that.

So then you start to be able to take spatial data.

What is then the definition of the object?

And so we're just learning all this right now.

So how do you compute the, How would you begin to compute the assembly index of a graphical, like a set of pixels on a 2D plane that form a thing?

So you would, first of all, determine the resolution.

are the number on the x and y plane, and then look at the surface area.

And then you take all your emojis and make sure they're all looked at the same resolution.

And then we were basically then do the exactly the same thing we would do for cutting the bonds.

You'd cut bits out of the emoji and look at the, you'd have a bag of pixels, so and you would then add those pixels together to make the overall emoji.

Wait a minute, but like, first of all, not every pixel's, I mean, this is at the core of sort of machine learning and computer vision.

Not every pixel is that important and there's like macro features, there's micro features and all that kind of stuff.

Like you know the eyes appear in a lot of them, the smile appears in a lot of them.

So in the same way in chemistry, we assume the bond is fundamental, what we do in AI is we assume the resolution at the scale at which we do it is fundamental.

And you're right, that will change, right?

Because as you take your lens out a bit, it will change dramatically.

But it's just a new way of looking at not just compression, what we do right now in computer science and data.

1 big kind of misunderstanding is assembly theory is telling you about how compressed the object is.

It's a how much information is required on a chain of events.

Because the nice thing is if in when you do compression in computer science, we're wandering a bit here, but it's kind of worth wondering, I think.

You assume you have instantaneous access to all the information in the memory.

In assembly theory, you say, no, you don't get access to that memory until you've done the work.

And then when you've done access to that memory, you can have access, but not to the next 1.

And this is how in assembly theory we talk about the 4 universes, the assembly universe, the assembly possible, and the assembly contingent, and then the assembly observed.

And they're all scales in this combinatorial universe.

Yep, so the assembly universe is like anything goes, just as just commentarial kind of explosion in everything.

Assembly universe, assembly possible, assembly contingent, assembly observed.

And on the y-axis is assembly steps in time.

And in the x-axis is as the thing expands through time, more and more unique objects appear.

So yeah, so assembly universe, everything goes.

Assembly possible, laws of physics come in, in this case in chemistry bonds.

So the way to look at it, you've got all your atoms, They're quantized, you can just bung them together.

So then you can become a kind of, so in the way in computer science speak, I suppose the assembly universe is just like no laws of physics.

Things can fly through mountains beyond the speed of light.

In the assembly possible, you have to apply the laws of physics, but you can get access to all the motifs instantaneously with no effort.

Then the assembly contingent says, no, you can't have access to the highly assembled object in the future until you've done the work in the past on the causal chain.

And that's really the really interesting shift where you go from assembly possible to assembly contingent.

That is really the key thing in assembly theory that says You cannot just have instantaneous access to all those memories.

The universe has to have somehow built a system that allows you to select that path rather than other paths.

And then the final thing the assembly observed is basically us saying, oh, these are the things we actually see.

We can go backwards now and understand that they have been created by this causal process.

Wait a minute, So when you say the universe has to construct the system that does the work, is that like the environment that allows for like selection?

That's the thing that does the selection.

You could think about in terms of a von Neumann constructor versus a selection, a ribosome, Tesla plant assembling Teslas.

You know, the difference between the assembly universe in Tesla land and the Tesla factory is, everyone says, no, Teslas are just easy, they just spring out, you know how to make them all in a Tesla factory, you have to put things in sequence and out comes a Tesla.

Super important point is that when I talk about the universe having a memory or there's some magic, it's not that.

It's that tells you that there must be a process encoded somewhere in physical reality, be it a cell, a Tesla factory, or something else that is making that object.

I'm not saying there's some kind of woo-woo memory in the universe, you know, morphic resonance or something.

I'm saying that there is an actual causal process that is being directed, constrained in some way.

So it's not kind of just making everything.

Yeah, but Lee, what's the factory that made the factory?

So what is the, so first of all, you assume the laws of physics as just sprung to existence at the beginning.

Those are constraints, but what makes the factory the environment that does the selection?

This is the question of, well, it's the first interesting question that I want to answer out of 4.

I think the factory emerges in the environment, the interplay between the environment and the objects that are being built.

And here, let me, I'll have a go at explaining to you the shortest path.

Imagine you've got, I'm gonna have to go chemistry for a moment and then abstract it.

So imagine you've got a given environment that you have a budget of atoms, you're just flinging together.

And the objective of those atoms that are being flung together in, say, molecule A, have to make, they decompose.

So the molecules in this environment, in this magic environment, have to not die, but they do die, they have a half-life.

So the only way the molecules can get through that environment out the other side, let's pretend the environment is a box, and go in and out without dying, and there's just an infinite supply of atoms coming or a large supply.

The molecule gets built but the molecule that is able to template itself being built and survives in the environment will basically reign supreme.

Now, let's say that molecule takes 10 steps, and it's using a finite set of atoms, right?

Now let's say another molecule, smart-ass molecule we'll call it, comes in, and can survive in that environment, and can copy itself, but it only needs 5 steps.

The molecule that only needs 5 steps, because both molecules are being destroyed, but they're creating themselves faster than they can be destroyed, you can see that the shortest path reigns supreme.

So the shortest path tells us something super interesting about the minimal amount of information required to propagate that motif in time and space.

And it's just like a kind of, it seems to be like some kind of conservation law.

So 1 of the intuitions you have is the propagation of motifs in time will be done by the things that can construct themselves in the shortest path.

So like, you can assume that most of the objects in the universe are built in the shortest, in the most efficient way.

Yeah, Yes and no, because there are other things.

So in the limit, yes, because you want to tell the difference between things that have required a factory to build them and just random processes.

But you can find instances where the shortest path isn't taken for an individual object, an individual function.

And people go, ah, that means the shortest path isn't right.

Because, so of course, Because there are other driving forces, it's not just 1 molecule.

Now when you start to consider 2 objects, you have a joint assembly space.

And now it's a compromise between not just making A and B in the shortest path, you want to make A and B in the shortest path.

Which might mean that A is slightly longer, you have a compromise.

So when you see slightly more nesting in the construction, when you take a given object, that can look longer, but that's because the overall function is the object is still trying to be efficient.

And this is still very hand wavy, and maybe having no legs to stand on, but we think we're getting somewhere with that.

And there's probably some parallelization, right?

The building is, I guess when you're talking about complex objects, you don't have to work sequentially, you can work in parallel, you can get your friends together and they can...

Yeah, and the thing we're working on right now is how to understand these parallel processes.

Now there's a new thing we've introduced called assembly depth.

And assembly depth can be lower than the assembly index for a molecule when they're cooperating together because exactly this parallel processing is going on.

And my team have been working this out in the last few weeks because we're looking at what compromises does nature need to make when it's making molecules in a cell?

And I wonder if, you know, I may be like, Well, I'm always leaping out of my competence.

But in economics, I'm just wondering if you could apply this in economic process.

It seems like capitalism is very good at finding shortest path,

But there are ludicrous things that happen because actually the cost function has been minimized.

And so I keep seeing parallels everywhere where there are complex nested systems, where if you give it enough time and you introduce a bit of heterogeneity, the system readjusts and finds a new shortest path.

But the shortest path isn't fixed on just 1 molecule now, it's in the actual existence of the object over time.

And that object could be a city, it could be a cell, it could be a factory, but I think we're going way beyond molecules and my competence probably should go back to molecules, but hey.

All right, Before we get too far, let's talk about the assembly equation.

Now let me just even read that part of the paper.

We define assembly as the total amount of selection necessary to produce an ensemble of observed objects, quantified using equation 1.

The equation basically has A on 1 side, which is the assembly of the ensemble, and then a sum from 1 to N, where N is the total number of unique objects, and then there is a few variables in there that include the assembly index, the copy number, which we'll talk about.

That's an interesting, I don't remember you talking about that.

That's an interesting addition, and I think a powerful 1.

Has to do with what, that you can create pretty complex objects randomly.

And in order to know that they're not random, that there's a factory involved, you need to see a bunch of them.

just to make sure that more than 1 object, 1 object could be a 1 off and random.

And then you have more than 1 identical object.

2 of a thing is super important, especially if the assembly index is high.

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Lee Cronin: Controversial Nature Paper on Evolution of Life and Universe | Lex Fridman Podcast #404