How & why do animals play? — Gordon Burghardt

Many animals play. But why?

Play has emerged in species as distinct as rats, turtles, and octopi although they are separated by hundreds of millions of years of evolution.

While some behaviors — hunting or mating for example — are straightforwardly adaptive, play is more subtle. So how does it help animals survive and procreate? Is it just fun? Or, as Huizinga put it, is it the primeval soil of culture?

Our guest this week is Gordon Burghardt, a professor at The University of Tennessee and the author of the seminal The Genesis of Animal Play: Testing the Limits where he introduced criteria for recognizing animal play.

Gordon has spent his career trying to understand the experience of animals. He advocates for frameworks such as critical anthropomorphism and the umwelt so we can judiciously adjust our perspectives. We can play at being other.

Links

Gordon Burghardt — Multiverses Podcast

Milestones

(00:00) Introduction

(2:20) Why study play?

(4:00) Criteria for play

(5:00) Fish don’t smile

(5:50) The five criteria: 1. incompletely functional

(7:40) 2. Fun (endogenous reward)

(8:20) 3. Incomplete

(9:45) 4. Repeated

(10:50) 5. Healthy, stress free

(13:30) Play as a way of dealing with stress (but not too much)

(16:40) Parental care creating a space for play

(17:45) Delayed vs immediate benefits

(20:45) Primary, secondary and tertiary play

(26:00) Role reversal, imitation, self-handicapping: imagining the world otherwise

(31:00) Secondary process: play as a way of maintaining systems

(33:37) Tertiary process: play as a way of going beyond

(34:45) Komodo dragons with buckets on their heads

(39:22) Critical anthropomorphism

(42:40) Umwelt — Jakob von Uexküll

(49:18) Anthropomorphism by omission

(53:00) Play evolved independently — it is not homologous

(53:45) Do aliens play?

(1:00:10) Play signals — how to play with dogs and bears

(1:04:00) Inter species play

(1:09:00) Final thoughts

Language Evolution & The Emergence of Structure — Simon Kirby

Language is the ultimate Lego.

With it, we can take simple elements and construct them into an edifice of meaning. Its power is not only in mapping signs to concepts but in that individual words can be composed into larger structures. 

How did this systematicity arise in language?

Simon Kirby is the head of Linguistics and English Language at The University of Edinburgh and one of the founders of the Centre for Langauge Evolution and Change. Over several decades he and his collaborators have run many elegant experiments that show that this property of language emerges inexorably as a system of communication is passed from generation to generation. 

Experiments with computer simulations, humans, and even baboons demonstrate that as a language is learned mistakes are made – much like the mutations in genes. Crucially, the mistakes that better match the language to the structure of the world (as conceived by the learner) are the ones that are most likely to be passed on.

Dynamic Message Animation

Links

Outline

(00:00) Introduction

(2:45) What makes language special?

(5:30) Language extends our biological bounds

(7:55) Language makes culture, culture makes language

(9:30) John Searle: world to word and word to world

(13:30) Compositionality: the expressivity of language is based on its Lego-like combinations

(16:30) Could unique genes explain the fact of language compositionality?

(17:20) … Not fully, though they might make our brains able to support compositional language

(18:20) Using simulations to model language learning and search for the emergence of structure

(19:35) Compositionality emerges from the transmission of representations across generations

(20:18) The learners need to make mistakes, but not random mistakes

(21:35) Just like biological evolution, we need variation

(27:00) When, by chance, linguistic features echo the structure of the world these are more memorable

(33:45) Language experiments with humans (Hannah Cornish)

(36:32) Sign language experiments in the lab (Yasamin Motamedi)

(38:45) Spontaneous emergence of sign language in populations

(41:18) Communication is key to making language efficient, while transmission gives structure

(47:10) Without intentional design these processes produce optimized systems

(50:39) We need to perceive similarity in states of the world for linguistic structure to emerge

(57:05) Why isn’t language ubiquitous in nature …

(58:00) … why do only humans have cultural transmissions

(59:56) Over-imitation: Victoria Horner & Andrew Whiten, humans love to copy each other

(1:06:00) Is language a spandrel?

(1:07:10) How much of language is about information transfer? Partner-swapping conversations  (Gareth Roberts)

(1:08:49) Language learning  = play?

(1:12:25) Iterated learning experiments with baboons (& Tetris!)

(1:17:50) Endogenous rewards for copying

(1:20:30) Art as another angle on the same problems

The Meaning of Net Zero — Myles Allen

What is net zero?

Easy right? Surely, even LLMs can’t mess this up: “Net zero in terms of climate change refers to achieving a balance between the amount of greenhouse gases (GHGs) emitted into the atmosphere and the amount removed from it.” (Bard) WRONG. ❌

On Multiverses this week Professor Myles Allen of Environmental Change Institute (ECI), University of Oxford and Oxford Martin School tells us what he and other scientists really meant by net zero when they introduced it in COP 21 (Paris 2015).

Listen to get the full account. But here’s the short version:

🌍 Net zero does not mean holding GHGs constant in the atmosphere by balancing sources and sinks to it

🌍 … That would lock in (a lot) more warming

🌍 Net zero means balancing the flow of carbon to/from the Earth’s crust

🌍 … And letting natural sinks gradually reduce atmospheric levels

🌍 … Preventing warming beyond 2050.

Myles also makes a strong case that, if we want to hit the 2050 goals we need to invest more heavily in large-scale geological carbon capture and storage. Many climate activists worry that such a policy would detract from the progress of renewables and give the fossil fuel industry carte blanche to continue emitting. But Myles points out that our reliance on fossil fuels is not falling as quickly as we need, and CCAS is technologically viable, economically feasible, and essential to reaching true geological net zero.

Myles Allen - net zero

(00:00) Intro

(2:29) What is net zero?

(4:12) Net zero is not a stable state but dynamical

(6:20) If we stabilise concentrations of CO2 we would see half as much warming again

(9:10) The meaning of net zero is often confused

(12:20) The danger of carbon accounting double counting

(16:56) The difficulty of establishing additionality

(19:52) Geological net zero is what was originally meant by net zero

(21:30) There are no significant natural sources or sinks of carbon between the biosphere and geosphere

(27:25) COP 28: the fossil fuel industry has got to be part of the solution

(30:50) “It is almost dangerous to claim it’s possible to solve the climate crisis without getting rid of CO2 on a very large scale … injecting it back into the Earth’s crust”

(32:30) Phasing out fossil fuels altogether is effectively letting the industry off the hook

(32:45) To what extent can we trust the fossil fuel industry? The potential dangers of CCAS

(35:30) “The cost with today’s technology of recapturing CO2 from the atmosphere and storing under the North Sea … “ is such that the natural gas industry could recapture all emissions and still be profitable at current prices

(40:10) Carbon pricing has failed: people do the cheapest thing first and the costly, slow-to-develop things (e.g. CCAS) are not coming fast enough

(42:20) The difficulty of getting a carbon capture flywheel going

(45:05) Intermittent energy supply is not a problem for carbon capture

(45:45) Is biochar a viable alternative to geological carbon capture?

(47:08) Biochar can’t hit the scale we need

(48:55) Extended producer responsibility

(50:10) eFuels (synthetic fuels)

(50:44) Final comments: we have the technology but we need to be realistic, we need to start taking carbon back

Feeling Right, Ethics and Emotion — James Hutton

Should we trust our emotions as a guide to right and wrong?

Some ethical frameworks would see us removing our feelings from the picture, acting with impartiality, and following principles such as the greatest good for the greatest number. Yet we can find cases where the consequences of those frameworks don’t feel right.

This week’s guest James Hutton is a philosopher at the Delft University of Technology who argues that emotions provide a way of testing our moral beliefs — similar to the way observations are used in natural sciences as evidence for or against theories.

This is not to say that emotions are infallible, nor that they are not themselves influenced by our moral beliefs, but that they do have a place in our moral inventory. In particular, the destabilizing power they can have — their capability to clash with our beliefs — is an important counterpoint to the entrenchment of poorly justified worldviews.

Listen carefully and you can just about hear me revising my own beliefs throughout this conversation.

AI Risks & Rewards — Santiago Bilinkis

Could AI’s ability to make us fall in love with be our downfall? Will AI be like cars, machines that encourage us to be sedentary, or will we use it like a cognitive bicycle — extending our intellectual range while still exercising our minds? 

These are some of the questions raised by this week’s guest Santiago Bilinkis. Santiago is a serial entrepreneur who’s written several books about the interaction between humanity and technology. Artificial, his latest book, has just been released in Spanish.

It’s startling to reflect on how human intelligence has shaped the Earth. AI’s effects may be much greater.

Links

Outline

(00:00) Intro

(2:31) Start of conversation — a decade of optimism and pessimism

(4:45) The coming AI tidal wave

(7:45) The right reaction to the AI rollercoaster: we should be excited and afraid

(9:45) Nuclear equilibrium was chosen, but the developer of the next superweapon could prevent others from developing it

(12:35) OpenAI has created a kind of equilibrium by putting AI in many hands

(15:45) The prosaic dangers of AI

(17:05) Hacking the human love system: AI’s greatest threat?

(19:45) Humans falling in love may not only be possible but inevitable

(21:15) The physical manifestations of AI have a strong influence over our view of it

(23:00) AI bodyguards to protect us against AI attacks

(23:55) Awareness of our human biases may save use

(25:00) Our first interactions with sentient AI will be critical

(26:10) A sentient AI may pretend to not be sentient

(27:25) Perhaps we should be polite to ChatGPT (I, for one, welcome our robot overlords)

(29:00) Does AGI have to be conscious?

(32:30) Perhaps sentience in AI can save us? It may make it reasonable

(34:40) An AGI may have a meaningful link to us in virtue of humanity being its progenitor

(37:30) ChatGPT is like a smart employee but with no intrinsic motivation

(42:20) Will more data and more compute continue to pay dividends?

(47:40) Imitating nature may not necessarily be the best way of building a mind

(49:55) Is my job safe? How will AI change the landscape of work?

(52:00) Authorship and authenticity: how to do things meaningfully, without being the best

(54:50) Imperfection can make things more perfect (but machines might learn this)

(57:00) Bernard Suits’ definition of a game: meaning can be related to the means, not ends.

(58:30) The Cognitive Bicycle: will AI make us cognitively sedentary or will it be a new way of exercising our intellect and extending its range?

(1:01:24) Cognitive prosthetics have displaced some intellectual abilities but nurtured others

(1:06:00) Without our cognitive prosthetics, we’re pretty dumb

(1:12:33) Will AI be a leveller in education?

(1:15:00) The business model of exploiting human weaknesses is powerful. This must not happen with AI

(1:24:25) Using AI to backup the minds of people

Gömböc, a shape at the limits of possibility — Gábor Domokos

The Gömböc is a peculiar shape. It’s too balanced and poised to appear natural but too clunky to suggest it is the fruit of human design. It seems alien or supernatural. This is appropriate, for the Gömböc is a shape that many thought impossible.

View the interactive version.

The Gömböc is the first known homogenous shape with the properties of having just one stable and one unstable balance point. Its weight is evenly distributed yet, however you put it, it will tumble and roll until resting always in the same position. Unless you pose it most delicately on its unstable point.

For convex, homogenous shapes the problem of finding balance points collapses to that of finding local maximal and minimal points from the centre of mass to the surface. For each minimum, there is a stable balance point, for each maximum an unstable one, and for those shapes that have a maximum and a minimum at the same point (appropriately called saddle points, for they are at the top and bottom of “hills”, like a saddle) — it is stable along one direction and unstable along others.

For many years, many mathematicians believed such a shape to be impossible, fruitlessly trying to produce a theorem to prove their intuition. Their hypothesis was informed by two pieces of evidence:

  • For two-dimensional shapes, it can be shown that 4 balance points are the minimal possible. This is proved by the four-vertex theorem: any closed curve other than the circle must have four vertices — four points that are either local maxima or minima.
  • No shape had been seen in nature.

Evidence can be misleading.

This week Gábor Domokos relates his decade-long quest to find the Gömböc. A tale of mathematical intuition, persistence, and a dose of luck.

But the story of this shape is far more than a mathematical curio.

Its discovery developed ways of thinking and led to a research program that has revolutionized our understanding of how things fall apart. Indeed, the Gömböc and the cube can be understood as two bookends of the evolutionary process by which material disintegrates.

Whether rocks on Mars, pebbles in Pisa, or asteroids flying through space, the Gömböc and the cube delimit the forms that things can take. At the one extreme, the cube sets an upper limit on (or, rather, just above) the number of balance points natural objects take.

Take a large boulder, or block of ice, and fracture it with a pickaxe, the resulting pieces will tend to have a similar number of faces as the cube. Just as randomly drawing lines on paper will produce, on average, shapes with four sides — see the image below, or animation here. As rocks weather, the areas of the highest curvature (the pointiest bits) weather fastest. This will tend to reduce the number of balance points as faces disappear and points of maximal and minimal distance elide.

The Markovian march towars the Gömböc from Pebbles, shapes, and equilibria Gabor Domokos, András Árpád Sipos, Tímea Szabó & Péter Várkonyi

These straightforward techniques for categorizing forms in terms of balance points, average number of faces (and also of vertices, and faces per vertex) have proved incredibly productive. The Platonic pantheon of shapes (tetrahedra, cubes …) and the few others we learn of at school (cones, cylinders … ) are but a few citizens of a world that comes into view. A jostling populace that ineluctably marches towards the Gömböc.

The extraordinary consequence of this is that holding a pebble in your hand you can feel its age, not just in its sea-worn smoothness, but in its geometrical simplicity. In the loss of its stable points.

Things fall apart

View animated full screen version

Reading

Moments

(00:00) Intro

(2:40) Start of conversation — what is a Gomboc?

(4:30) The Gomboc is the “ultimate shape” it has only two balance points

(5:30) The four vertex theorem: why a 2D shape must have 4 balance points

(6:30) (almost) nobody thought a Gomboc existed

(8:30) Vladimir Ilych Arnold’s conjecture

(9:00) Hamburg 1995, the beginning of a quest

(10:30) “Mathematics is a part of physics where experiments are cheap”

(11:50) A hungry scholar sits next to a mathematical superstar

(13:00) Ten years of searching

(15:00) Domokos and Varkonyi’s gift for Arnold

(15:30) Arnold’s response: “good, but now do something serious”

(16:50) We cannot easily speak about shapes.

(18:00) A system for naming shapes

(21:00) “The evolution of shapes is imprinted in these numbers”

(21:50) Pebbles evolve towards the Gomboc, but never get there

(24:50) How to find the balance points of shapes by hand

(30:00) Physical intuition and empirical exploration can inform mathematics

(30:30) A beach holiday (and a marital bifurcation point)

(34:00) “No this was not fun, it was a markov process”

(36:40) Working with NASA to understand the age of martian pebbles

(38:20) An asteroid, or a spaceship?

(43:00) The mechanisms of abrasion

(45:50) The isoperimetric ratio — does not evolve monotonically …

(47:50) … But the drift to less balance points is monotonic

(49:00) The process of abrasion is a process of simplifying

(50:00) We can name the shape of Oumuamua because it is so simple

(51:00) Relationship between Gomboc and (one way of thinking about) entropy

(55:00) Abrasion and the heat equation — curvature is “like” heat and gets smoothed out

(58:00) The soap bar model — why pointy bits become smooth

(1:00:00) Richard Hamilton, the Poincaré conjecture and pebbles

(1:04:00) The connection between the Ricci flow and pebble evolution

(1:09:00) Turning the lights on in a darkened labyrinth

(1:12:00) The importance of geometric objects in physics (string theory)

(1:13:30) Another way of naming natural shapes: the average number of faces and vertices

(1:15:00) “Earth is made of cubes” — it turns out Plato was right

(1:16:30) Could Plato’s claim have been empirically inspired?

(1:17:50) “Everything happens between 20 and 6”

(1:18:30) The Cube and the Gomboc are the bookends of natural shapes

(1:19:30) The Obelisk in 2001 — an unnatural, but almost natural shape

(1:22:00) Poincaré on dreaming: genius taps the subconscious

What is philosophy? — Simon Critchley

From what human need does philosophy emerge? And where can it lead us?

Simon Critchley is Hans Jonas professor of Philosophy at the New School in New York, and a scholar of Heidegger, Pessoa, Football (Liverpool FC), humour. He crosses over between analytic and continental traditions and freely draws on quotes from Hume and British pop bands.

Simon argues that philosophy begins in disappointment, not wonder. But it does not end there, its goals can be wisdom, knowledge, enlightenment, and freedom. Its concerns can be yet more varied: it can work as a tool for developing scientific theories, for exposing ideology, or for tracing the underpinnings of language and experience. Anywhere where other fields fear to tread, that’s where philosophers step in.

Since recording with Simon, one question has kept turning over in my head: how important is context to the understanding of philosophical ideas? An issue we discussed towards the end of the interview and did not quite have sufficient time to loop around as many times as I would have liked.

On the one hand, I believe in such things as facts and truth. I believe that science and some philosophical reasoning can deliver us these — although I recognize that belief cannot be justified beyond doubt. It is an act of faith. However, certain types of things, for example, facts concerning the laws of physics, I take to be impervious to our attitudes and human concerns. Why we believe them, and why we even look for them, are valid sociological and phenomenological questions. Yet the evidence for these facts can be produced usefully without any reference to historical context and the facts themselves do not depend on human factors.

In this way, to the question of whether the sun existed before humans — the subject of a heated discussion between Maurice Merleau-Ponty, Georges Bataille and A J Ayer in a Parisian bar — my answer is yes.

And yet.

There are questions that philosophy asks about issues that have no basis in fact. Impossible objects.

I recently asked ChatGPT to produce some predictions about the future for a project I am working on (What Year is Now? A Hallucinatory Horological Mapping). There are some obvious errors with the below — the tercentenary of the first interdimensional travel falling in 2307 would imply we first made that leap back in 2007. I suppose that’s possible if the dimension in question is time.

More interesting is what is predicted for 2306:

2306: Interdimensional exploration reveals the nature of existence itself

ChatGPT

I do not think that will happen. I don’t think it can. Determining the nature of existence is a question we cannot solve, even though there is value in turning it over, the value is not to get to an answer. It’s a means justify the ends (and btw there are no ends) sort of question.

For questions like this, and more particularly questions about the meaning of existence, context is important. Consider also questions in ethics and meta-ethics. There are no truths to be had here, and what is right for society — perhaps even the right way of thinking for society — will depend on that society. For example, in times of high uncertainty, where predictions are costly and inaccurate (perhaps this moment?) we might have reasons to consider virtue ethics over consequentialist frameworks.

Does it matter that I write this on Sunday morning, in 2023, in a stony city, that the sun — prehistoric or not — is hidden by several layers of cloud? It’s not for me to say.

Some links

Moments

(00:00) Intro
(3:00) Beginning of conversation: disappointment as the start of the journey
(7:55) Punk & Philosophy
(11:20) Trauma and tabula rasa
(12:30) Not making it in a band, becoming a philosopher
(19:30) Wittgenstein as a bridge between analytic and continental philosophy
(21:50) Mill and the origin of the label “continental philosophy”
(24:30) Philosophy has a duty to be part of culture
(28:00) The difficulty with philosophy being an academic tradition
(29:30) The Stone
(32:30) Football as a phenomenon for study that invites people in to philosophy
(35:00) Philosophy as pre-theoretic & Pessoa’s Ultimatum
(39:00) Will analytic philosophy run out for road and be subsumed into science?
(41:00) Two lines of human imagination
(42:00) Should philosophy ever be a single honours subject, or should it always aid other realms of thought?
(43:00) Philosophy as pre-science
(44:30) Phenomenology as reflection on the lived world
(47:00) Alberto Caeiro (Pessoa) and anti-poetry
(48:50) The saying of ordinary things to fascinate angels
(54:00) Impossible objects will keep philosophers busy
(57:00) The task of philosophy as deflationary, as not making progress
(1:00:00) Should philosophy of physics be part of physics?
(1:04:30) Context: What can’t I read Descartes like I’m talking to your right now?
(1:06:00) Is context colour or is it inseparable from ideas?
(1:15:30) Rorty: Continental philosophy as proper names vs problems in analytic philsophy
(1:19:20) Trying to walk the line between two traditions of philosophy
(1:20:00) Obscurantism vs scientism
(1:23:00) Permission to think on their own, to expose ideology
(1:26:00) The internet has been good for philosophy
(1:26:30) Audio as a new platform or agora for philosophy

ChatGPT as a Glider — James Intriligator

Large language models, such as ChatGPT are poised to change the way we develop, research, and perhaps even think (see The Offshoring of Thought and Memory). But how do we best understand LLMs to get the most from our prompting?

Thinking of LLMs as deep neural networks, while correct, is not very useful in practical terms. It doesn’t help us interact with them, rather as thinking of human behavior as nothing more than the result of neurons firing won’t make you many friends. However, thinking of LLMs as search engines is also faulty — they are notoriously unreliable for facts.

Some other models have been proposed:

  • LLMs are “stochastic parrots” as Bender, Gebru, McMillan-Major, and (Sh)Mitchell argue
  • ChatGPT is “A fuzzy JPEG of the web” according to Ted Chiang

These both capture something of how they work, but they do not provide any direction on how to create prompts.

Our guest this week is James Intriligator. James trained as a cognitive neuroscientist at Harvard, but then gravitated towards design and is currently Professor of the Practice in Human Factors Engineering and Director of Strategic Innovation at Tufts University. 

James proposes viewing ChatGPT not as a search engine, parrot, or JPEG, but as a “glider” that journeys through knowledge. By guiding it through diverse domains, it learns your interests and customizes better answers. Dimensional prompts activate specific areas like medicine or economics. 

I believe we’ll need to have various mental models to understand how best to interact with LLMs. This is one for the toolbox.

Links:

MV#9 — The Hunt for H2 — Rūta Karolytė

For many years scientific consensus has averred that hydrogen does not occur naturally in significant quantities without being bound to other atoms (such as in H20, water, or CH4, methane). To obtain the gas — whether as a fuel or for use in fertilizers — we need to strip it from those molecules — typically by electrolysis and steam reformation. But our understanding may be ripe for change.

Website of National Renewable Energy Laboratory from February 2023, following the publication of a New York Times article on natural H2, the text was changed to “Because hydrogen typically does not exist freely in nature” (emphasis mine)

Rūta Karolytė is at the vanguard of prospectors looking for large, naturally occurring reservoirs of hydrogen. She’s a researcher from Oxford specializing in the geochemistry of the Earth and she enlightens us to the mechanisms that are likely to be producing hydrogen in the crust: radiolysis and serpentinization. 

In reviewing the evidence for naturally occurring hydrogen we pass through exotic terrain: a Soviet-era theory of hydrocarbon production, fairy rings, hydrothermal vents and chemosynthetic life. These organisms, remarkably, do not depend on the sun, plants, or any other life forms for their energy. Instead, they draw directly from the power stored in inorganic compounds. Their existence is testimony to the natural occurrence of hydrogen.

This does not guarantee that hydrogen is present in large quantities, but modeling of the processes that produce it — particularly serpentinization — suggests it is. Serpentinization is a kind of rusting whereby rocks are oxidized and hydrogen is freed from water molecules, wherever water and the right kinds of rocks are present and the pressure and temperature are right, hydrogen will be produced. What is more this process could be sped up by the introduction of more water underground.

If Rūta and her fellow prospectors are correct, the tapping of natural hydrogen could have transformative consequences for the “Hydrogen economy” — such as cutting out the substantial fossil fuel emissions associated with deriving fertilizers from methane or creating a cheap basis for building synthetic fuels.

In the first half of the show, we also delve into carbon sequestration — another cool climate topic. But I’ve got so excited writing up the first half, that I’ll leave it here. 

References

Thought Experiments, Mach, Galileo & Phenomenology — Harald Wiltsche

Thought experiments have played a starring role in physics. They seem, sometimes, to pluck knowledge out of thin air. This is the starting point for my discussion this week with the philosopher Harald Wiltsche: what are thought experiments?

How do they function — are they platonic laboratories with no moorings in observations or a way of supercharging our reasoning about phenomena?

What do they deliver? Much emphasis has been put on the paradigm-shattering insights of Einstein where thought experiments appear like midwives in the production of new theories. But they can also function in explaining those theories, in ensuring they are understood.

This leads to the question: what is understanding? Harald argues that it’s the ability to manipulate or deploy knowledge backed up by a mental model. He reasons that thought experiments can help us to make sense of the abstraction of mathematical models.

We discuss many topics: the mathematization of science with Galileo, where thought experiments go wrong, transcendental arguments, the links between Husserl and Mach — it was the latter’s emphasis on grounding physics in phenomenona that inspired the phenonomenological tradition in philosophy.

While there are many notes we touch on, the theme that we dance to is this: there are lots of forms of reasoning that can work well within physics and we need equal pluralism in our philosophy of science to understand the its startling, uncanny success in modeling nature.

Notes

How well does ChatGPT do with thought experiments?

Pretty well.

This question came up when discussing understanding. Large language models are certainly adept at manipulating symbols in ways that sound convincingly human, but how well do they in reasoning (or appearing to reason) about physics?

I go through two sets of prompts here, the second — where I prompt it with a thougth experiment that gets increasingly bizarre — is the more intriguing. It’s possible in all of these cases that a similar experiment has somewhere been discussed and ChatGPT is esstially parroting someone else’s understanding, however, the setup is rather complex: a helicopter magnetically levitating a butterfly in a plastic plane — has that really been dicussed before? I think one is forced to concede that it appears to have a good grasp of the physics.

Asking ChatGPT (GPT4) to think up a thought experiment

User Can you construct a thought experiment to explore the issue of whether space is absolute or relative, the ingredients in the experiment are two brass balls, scissors and a ribbon


ChatGPT
Absolutely, let’s consider a thought experiment, that could potentially show how to understand the difference between the concepts of absolute and relative space.

First, let’s define these terms for clarity:

Absolute Space: This refers to the Newtonian concept of space, which exists independently and objectively, as an unchangeable and infinite background where all physical events occur.

Relative Space: This refers to the Einsteinian concept of space, where space doesn’t exist independently of the things within it. Instead, space and time are interwoven into a four-dimensional fabric known as spacetime, and the presence of mass and energy can distort this spacetime fabric. This is the basis of Einstein’s theory of General Relativity.

Now, let’s proceed to the thought experiment:

Imagine you’re in a spaceship with no windows, floating in deep space, far away from any celestial bodies. In this spaceship, you have two brass balls, a ribbon, and a pair of scissors.

You tie the two balls together with the ribbon and hang them in the middle of your spaceship. Since you’re in deep space with no other forces acting on your spaceship, the balls just float there, not moving relative to the spaceship.

Experiment 1: Now, you give your spaceship a slight spin. After a while, you notice that the balls are now rotating around the center of the spaceship, the ribbon taut, maintaining a fixed distance from each other due to the centrifugal force caused by the rotation of the spaceship. In this case, from the perspective of Newton’s absolute space, you’ve imparted a rotation on the spaceship, and the balls are simply responding to this by moving in a circle.

Experiment 2: Now, imagine an alternate scenario where your spaceship remains stationary, but all the universe around it starts to spin instead. According to the principle of relativity, you wouldn’t be able to tell the difference between these two situations from inside the spaceship. The balls would behave in exactly the same way, spinning around the center due to what appears to be the centrifugal force. However, this time, according to the relative space concept of Einstein’s General Relativity, the mass-energy of the universe spinning around the spaceship would distort the spacetime around it, creating a frame-dragging effect which leads to the balls’ circular movement.

This experiment illustrates that whether space is absolute or relative can dramatically change our interpretation of the same phenomena. Although this is just a thought experiment and not a practical one (we can’t spin the entire universe), it highlights the difference between the Newtonian concept of absolute space and the Einsteinian concept of relative space.

User
If a butterfly is inside a plane, but flying — so not on the seats — does the plane need to generate more thrust to maintain altitude than if the butterfly were absent?

Asking ChatGPT (GPT4) to reason through a thought experiment


ChatGPT
The plane doesn’t need to generate any additional thrust to maintain altitude whether a butterfly is flying or resting within the airplane cabin. This is due to the principle of conservation of momentum.

In the closed system of the airplane, the mass and the momentum are conserved. This means that the butterfly’s presence, flight, or rest doesn’t change the total momentum of the plane. When the butterfly is flying, it pushes air downwards to generate lift. The air pushes back on the butterfly, but it also pushes (very slightly) on the plane. The sum of these forces and reactions remains constant, so no extra thrust from the plane’s engines is necessary to maintain altitude.

In other words, when the butterfly takes off from a perch inside the airplane, it imparts a slight force to the airplane in the opposite direction. But as it flies around, all the movements it makes, the flapping of its wings, the changes in direction, etc., just redistribute the mass and momentum within the plane. The net effect on the plane is zero.

The situation would be the same whether the object in question is a butterfly, a bird, or a passenger walking down the aisle. As long as the action takes place within the closed system of the plane, it won’t affect the thrust needed to maintain the plane’s altitude or direction.

User
But if the butterfly were absent, wouldn’t the plane weigh less and therefore less thrust would be required?

ChatGPT
You are correct that if the butterfly were not present at all, the total weight of the airplane would be marginally less by the weight of the butterfly. The plane would therefore need a tiny amount less lift to maintain altitude, and consequently a tiny amount less thrust to maintain a particular speed.

However, once the butterfly is on board the plane, whether it is flying within the cabin or resting doesn’t affect the thrust required to maintain the plane’s altitude. This is because the weight of the plane system (including the butterfly, passengers, seats, etc.) is the same whether the butterfly is in flight or at rest.

In simpler terms, the energy required to lift the butterfly against gravity is still accounted for within the closed system of the plane, whether the butterfly is using its own wings to stay aloft or if it’s sitting on a seat.

So, to summarize, the plane does weigh less if the butterfly isn’t there at all, which would mean slightly less thrust is required. However, if the butterfly is present in the plane, whether it’s flying or not doesn’t make a difference to the thrust required.

User
What happens if the inside of the plane were a vacuum and the butterfly could levitate (perhaps magnetically) inside the plane, would it contribute to the weight of the plane’s contents then?


ChatGPT
Your scenario is a fascinating one. If we’re assuming the butterfly can somehow levitate magnetically, in a vacuum, inside the plane, then the answer to your question is yes, the butterfly still contributes to the total weight of the plane.

In this case, even if the butterfly is levitating, it doesn’t escape the pull of gravity. The butterfly still has mass, and the Earth’s gravity still acts on it, exerting a force (its weight). That gravitational force doesn’t disappear when it levitates; instead, it’s just counterbalanced by another force (in this case, a magnetic one).

This means that the butterfly’s weight still contributes to the overall weight of the plane. So if the butterfly weren’t present at all, the plane would be marginally lighter by the weight of the butterfly, regardless of whether it’s levitating or not.

The important point here is that gravity acts on all mass, regardless of its state or position. A levitating object in a gravitational field is still subject to gravity and still contributes to the total weight of the system it’s part of.

User
What if the plane were made of plastic, and the magnetic force holding the butterfly in place was one due to a helicopter flying above the plane, would it still contribute to the weight of the plane and thus lead the plane to require a tiny amount more thrust than if the butterfly were absent?

ChatGPT
If the magnetic force attracting the butterfly is not coming from the plane itself, but from an external source like a helicopter above it, then the situation changes.

In this case, the force that’s supporting the levitating butterfly is not being applied by the plane, but by the helicopter. So, the weight of the butterfly (which is the force of gravity acting on its mass) is essentially being “transferred” to the helicopter, not the plane.

Therefore, in this specific scenario, the butterfly’s weight would not contribute to the total weight of the airplane while it’s levitating. As a result, the plane would not require more thrust to maintain altitude than if the butterfly were completely absent.

However, remember that this situation is based on quite a few assumptions that would be very difficult to realize in the real world, and it doesn’t take into account other potential factors that could affect the plane’s flight.