Le Jeu de la Vie.

Today, we're going on a journey. And it's not just you and me, we're going with this little creature who's going to be our guide through a mathematical simulation with very simple rules on a theoretically infinite 2D grid, in a universe whose simple rules wouldn't let the neophyte that you probably are imagine what's going on there for a single second. This is what we call the soup.

Some call it the primordial soup. It's a notion that is initially less illustrated than what you're looking at, because originally, it's a concept that hypothesizes how life might have begun on Earth 3 to 4 billion years ago. It's a theory that suggests a kind of soup, an environment rich in organic compounds from which life could have emerged.

It's a solid theory, even if there are other possible hypotheses. The advantage for us is that we can create the primordial soup we're going to talk about today, and watch it evolve before our very eyes, in a 50-year-old game with very simple rules that anyone can run on its PC and have fun playing with the initial parameters. That said, you don't have to do anything, I'll take care of everything.

In fact, it's our little creature that we're going to follow throughout this video to discover the world in which it evolves. And while I'm sure you'll find that this world doesn't look much at the moment, I can assure you that it’s much more than that. By the way.

Here is a link in the description to a website that will make it easier to keep track and to help you follow along if it gets too complicated. There I summarize our little journey in outline, with rules, dates, configuration categories. In short.

Enough to land on your feet if needed, and by the way, don't thank me, this website is homemade with my little hands thanks to this video's sponsor: Odoo. Odoo, for those who don't know, is a platform that offers a wide range of applications for managing your business, including, among others, a quick and easy way to create a website. In other words, it's designed so that anyone can get familiar with it quickly, and that's literally what I did with this one.

When I start, I choose my goals, my color palette, add my pages, choose my theme and then it's all straightforward: the website is already created. To customize it, it's like a big Lego game where you simply take blocks to drag and drop. If I want a title and an image, I take the right block, then I drag and drop.

For comparisons, it’s the same. A timeline right here, columns, numbers, a map, all of this, I drag and drop. And once it's done, I can edit the text, images, colors and animations.

And if I don't feel like writing, even if I'm not inspired, Odoo features an AI that can write according to what I ask it to. In short, the main aim of this tool is simplicity, to be able to create intuitively. That's what enabled me to build this website, even though I knew nothing about it.

By the way, it's a website that didn’t cost me anything because the first Odoo application you choose is free for life, with unlimited hosting and support. On top of that, Odoo offers a personalized domain name for one year. And if you're interested, you'll find a link in the description and in the comments that you can click on to get started with Odoo.

And another link, of course, to help you follow our little journey more easily. A little journey we're about to resume. In fact, here we are, back in our primordial soup, and you don't understand a word of it, so let's start with the basics.

This is what is called Conway's Game of Life, because this version was developed by a mathematician named John Conway in 1970. This Game of Life belongs to a rather special category of games known as zero-player games, meaning that it is played on its own. Here, more specifically, we're dealing with what's known as a cellular automaton.

A cellular automaton is a mathematical model composed of cells that interact with each other according to precise rules. Let's keep it simple and work with what we see here to understand. Here, we have a theoretically infinite 2D grid.

All the little squares you see formed by the grid are cells that can be in one of two states: dead, in black, or alive, in white. Each cell is surrounded by eight other cells called neighbors. Okay, that's the basics.

Now, how do we bring all this to life? First of all, the game works in generations, one by one. The state of the current generation, so what we’re seeing here, will determine the state of the next one.

And we move forward generation by generation. The big question is: how each generation is generated? The advantage for us is that the whole point of Conway's Game of Life is to have very simple rules and then see how complex things can get.

And it's hard to get much simpler than that, since the Game of Life only has two rules, which are easy to understand if you think of cells as real populations. The first rule is that a dead cell with exactly three alive neighbors becomes alive. Basically, life in the right quantities creates life.

The second rule is that a living cell with two or three alive neighbors stays alive. With more than three neighbors, the cell dies, as if it was overpopulated. With less than two neighbors, the cell dies as if it was underpopulated.

Let's use an example to help you assimilate the concept more easily. Here are three living cells side by side. For each cell in the group, we're going to calculate what's going to happen in the next generation.

Okay, for this cell, we look at what's around it, in its direct environment it has two living neighbors, so according to this rule, it stays alive. For this cell too, two neighbors, so it stays alive. And for this cell too.

So these three living cells stay alive. But what happens to this dead cell? It has not only two living neighbors, but three.

Which means, according to the first rule, that it becomes alive. The right amount of life creates life. Well, we've just created something.

That’s not bad. But what happens in the next generation? Well, as each living cell has three living neighbors, all the cells stay alive, resulting in what's known as a block, one of the most common configurations in Conway's Game of Life.

This is how the Game of Life works. For each generation, the software calculates the state of each cell that’s on the grid at the same time. Let’s move forward, I’ll take care of the speed, depending on our meetings.

In short, this block belongs to a large category of configurations known as "still lifes". Basically, they're configurations that don't move. There are lots of them.

We call this one the "beehive", this one the "mirrored table". And that's fine, it makes pretty drawings, but it's not very exciting either. We want some movement.

So I'll show you. Here are three living cells side by side, and this is your first exercise. Pause the video, and I'll let you think about what it’s going to look like.

Okay, let's go through each cell again. This one has only one living neighbor, so it will die in the next generation. Same for this one, dead.

The one in the middle has two living neighbors, so it stays alive. Now we can look at the dead cells around it. This one has only two living neighbors, so not enough to become alive.

Same for these three. But this one has three living neighbors, and this one too, so they come to life, leading, in the next generation, to this. And when we leave it running, here's our first slightly interesting life form: the blinker.

It moves, it's pretty, but we can do better. The blinker belongs to the large category of oscillators. These are configurations that repeat themselves after a certain number of generations.

This, for example, is the "ring of fire". Like the blinker, it's an oscillator that works in two generations, meaning it takes two generations to return to its initial state. And we can go further in generations.

In three generations, we have the "pulsar", in four, we have the "Catherine wheel", in eight, the "figure eight", in twenty, the "145P20", in thirty-seven, the "Beluchenko’s p37". In short, it can go very high. But among the oscillators that need more generations, we find things I'd like to tell you about later, so we'll keep that under our hat.

But maybe there's something you're starting to ask yourself as you look at these configurations. How do you go from the soup to this? No kidding?

Because when I start a soup at home, I don't get anywhere. And that's where the title of zero-player game may have misled you. The Game of Life isn't just a game you launch and watch.

It's a game you explore and experiment with. And when the game was created in 1970, there were a lot of people exploring, trying, finding, naming and sharing. And I was very surprised to find myself completely overwhelmed by the amount of information on the Game of Life wiki, including explanations of concepts and categories.

There are lists of configurations with their components, how they work, and their creators, who themselves have pages listing all their finds, always with very inspired names. There's the "French kiss", there's the "mini pressure cooker", there's the "washing machine". You can really feel it's homemade.

In short, people have discovered these configurations, and they started as soon as the game was released. So John Conway creates the Game of Life, and publishes his research the same year in a journal called the Scientific American. People read the article and think: "Well, that's exciting.

I want to do that too. " So people try it at home. The thing is, in 1970, people had to find other ways, because at the time, computers weren't very accessible.

So people find ways. They start drawing their grids, placing tokens to represent the living cells, and they run their trials, generation after generation, by hand. It's slow, it's easy to make mistakes, but there's nothing to stop passionate people from continuing their passion.

And Conway is one of those people. In Cambridge, the university where he teaches, he was already doing this even before his paper was published, of course, with a go game. It was complicated to do everything by himself, and especially to keep track of the smallest configurations.

So he asked one of his friends, Richard, to be his blinker watcher. Basically, he was in charge of the blinkers and all the little periodic configurations. So he thinks, he tries different configurations.

Then one day, Richard says to Conway: "Hey, my blinker is moving? " Except it's not a blinker. Richard has just discovered the little creature we're going to travel with from now on: the glider.

When you want to create a glider, you place your living cells like this. In fact, depending on the direction you want to give it, you can rotate it vertically or horizontally. I place it like this so that it goes… Well this can be our second exercise if you like, you don't have to, but if you feel like it, just pause the video and guess where we're going.

If you're feeling lazy, stay with me. This is long. Well, I won't drag out the suspense, let’s launch our glider towards the top right.

Well, we've got our vehicle. We can explore the Game of Life and we've got a long way to go. Our first meeting is with another ship called the "lightweight spaceship".

I call it the fish, because it looks like a fish. You'll notice that its structure is very similar to our glider, only slightly larger, with two extra blocks at the rear. But the real difference with our own vehicle is that this ship travels orthogonally, while ours travels diagonally.

A little further away, we find slightly larger versions of the lightweight spaceship: the "middleweight spaceship" and the "heavyweight spaceship", which simply require the ship's hull to be lengthened. These three configurations, and our glider too, are what we call "natural spaceships", meaning that they can be found naturally in the soup without human intervention. So far, 54 natural spaceships have been found, sorted according to their relative frequency, the frequency of appearance of all naturally occurring ships.

Typically, the glider represents 99. 8% of natural ship occurrences. This probability immediately drops to 15/10,000 for the lightweight spaceship.

For this slightly larger configuration it’s only 2/10 million. We're rapidly dropping into billions, then trillions. In short, there's very little chance of finding them.

And that's for simple and rather boring configurations, we want more. And the good news is that we're approaching something far more exciting. I know it doesn't look like a ship, but it is one, called the "2-engine Cordership".

The 2-engine Cordership doesn't look that impressive, yet, it's a ship that was voted Pattern of the Year in 2017 on the forums of conwaylife. com. Why?

First of all, when you speed up the simulation a bit, you realize that it's not just a jumble of cells, but an entity that moves forward. Next, it's important to understand why we're talking about a 2-engine Cordership. In this ship, the engine is a so-called "switch engine", which produces a copy of itself after 48 generations and can be used to propel other ships.

It's worth noting that the very first cordership was discovered in 1991 and had thirteen engines. The growing complexity of Cordership discoveries hasn't been about adding more engines, but about removing some, and managing to build with less engines. A 10-engine Cordership was found the same year, a 7-engine one in 1993, a 6-engine one in 1998, until 2017 with this 2-engine Cordership, which won its small prize.

So it's a beautiful machine. But when looking at it, it looks a bit like clouds of cells moving side by side, without much connection to each other. But I can leave it running in the background and encourage you to stare at one piece all the way through, you'll see that in fact, everything is connected.

The ship's parts interact between them and influence each other to move the whole ship forward and keep it in a coherent, yet very fragile, state. Allow me a little sabotage. Let’s pause this, remove one random cell, and we can see that it doesn't fly as well.

The reason we haven't yet found a 1-engine cordership is that these engines are very chaotic. Here is another switch engine, by itself it gets out of control. So if a ship has to be propelled, to prevent the leftovers produced from destroying the whole thing, engines have to be accumulated so that they nullify their destructive effects.

That's why it's so hard to find new Cordership configurations. Finding the perfect combination of switch engines to move the ship forward and maintain its coherence despite the chaotic nature of the engines, well that's not easy. By the way, while I was recording this switch engine building plan, this happened.

Well. (I'm proud of my discovery) Anyway, switch engines: chaotic. Finding the right configuration: complicated.

But people have succeeded, and the 2-engine Cordership is moving very slowly. Well. .

. Very, very slowly. The speed of the 2-engine Cordership is written like this: C/12.

So 1/12th of C. C being the speed of light in the Game of Life. 1/12th of C is really slow.

In comparison, our glider moves at a speed of C/4, so let’s keep moving and drift away. But not really because we come across another 2-engine Cordership, then another. .

. Okay, what's going on here? Well, let’s keep moving, we've got a long way to go.

The advantage is that I can go faster. . .

A bit more. . .

Okay, here we are. Here is a 2-engine Cordership factory. To understand what we're looking at, we need to go back to simpler things.

John Conway enjoyed testing configurations on the go game, but not too much. So after the discovery of the glider, he offered a prize to anyone who could find a way to build a glider factory. To make sure he got results, he decided to offer the prize to the first person who could create a configuration capable of generating an infinite population.

So a small group of MIT students decided to work on it, and finally discovered this. This is what is called a "gun", more specifically a "glider gun", even more specifically a "gosper glider gun". Well, I don't like calling them guns, I think it's too violent for nothing.

So I call them dad and mom. But for the purpose of credibility, we're going to call them progenitors. I'll let you have a look at these progenitors for a few seconds, so that you can understand what's going on.

Well, it's quite simple actually, there's not much to understand. Basically, when two different groups of cells meet, two things happen at once. First, a glider is created from the encounter.

Second, each group goes its own way, hits those blocks and comes back for another encounter. There are all kinds of progenitors. A lot of different things can be produced at different timings, and this is once again one of the areas in which players impress me the most.

Because they don't hesitate to combine to create more. Typically, with a bee and two blocks, we can create the basic shuttle, which we can combine to make the gosper glider gun, which then can be used to create the "period 60 glider gun", or the "5 and dime", a generator that takes 150 generations to produce a glider, that’s quite long. And it may seem useless, but I'm going to use it.

In fact, the game even pushed me to combine things when I thought I was just a watcher of the Game of Life. So, back to our 2-engine Cordership factory. Actually, it's not a factory at all, it's a converter.

I couldn't find a complete factory. When I searched on the wiki, I found 3-engine or 6-engine Cordership factories, but not a 2-engine one. All I found was this machine that turns a glider into a 2-engine Cordership.

But once the glider's gone, well that's it. So we have no factory. That said, of course, I didn't have much left to do.

All I had to do was find a progenitor for gliders, put it in the right place and that’s it. Except that it broke the factory because combining gliders to that extent takes time and the glider production was too fast. So I looked for progenitors that took longer to produce.

Typically, I was thinking about the "five and dime" that I introduced to you before, which produces a glider every 150 generations. I thought it would be slow enough and that it would work. But it doesn’t, it's still too fast, it still breaks the factory.

I just picked a progenitor from the 3-engine Cordership factory. This one's pretty slow, which resulted in this little factory. Well, nothing complicated here, but I still had to do some fixing and that gave me enough time to fully understand how the factory works, and it’s very simple.

It consists in a progenitor which releases its product into a pipe which carries the glider here, causing a reaction that generates more gliders, which are then carried into the pipes. All the gliders come together here and slowly form a 2-engine Cordership. This is how factories work all the time.

The encounter of different cell groups leads to the creation of one or more other cell groups. And then, it can always get bigger. Here's the "V gun".

Well, I don't mind calling this one a gun, it's. . .

Intimidating. This one is the "maximum volatility gun". It's big.

And yet, it’s known as a single barrelled gun, meaning that it only produces a single current of ships, only gliders, right here. And it's always really interesting to look at these constructions to understand how they work. That's what I do before I start talking about it, I take a look and try to understand it.

By the way, I'm far from being an expert. I'm like a kid at playtime who wants to show his friends what he's found. And you’re my friends.

So this whole video is me coming to you to show you the pretty stones I've found in the playground. Well, I'll show you. The maximum volatility gun is quite easy to understand, but it still surprised me.

Looking at it from afar, I thought there was a source of gliders which then bounced on these bumpers to be sent into space. And I thought: "Well, it's meant to look pretty, to go round and round and that’s fine. ” But it's not really like that.

I think the next minute is pretty messy, but I've drawn some nice lines of color. We already have oscillators all over the place, which are all these structures oscillating all the time. In some places, these oscillators act as bumpers, redirecting the gliders that bump on them.

This current, for example, hits here, then here, then here and finally ends up here. At this spot, however, something different happens. The line of gliders we were following meets two other lines of gliders that have also just bounced off several bumpers.

So we know the process: groups of cells colliding and producing another group of cells. But there's more than that. You might think that it's just their collision that produces a ship.

But it's not. Look, if I pause the game, remove this oscillator and restart. Well, the machine is broken and when I accelerate, there's no more production flow.

So let’s go back, this is one of the oscillators that doesn't work as a bumper, but that is used as an object which, if it's there, has an impact on the objects passing by. And at this spot, with the arrival of the three glider flows, a ship is created and moves off to the left. So we keep going this way with our new ship and we witness the same thing a little further away.

Three gliders collide, this time without oscillators, giving rise to the same ship just a little smaller. Just after, the ships pass by other oscillators and their passage causes the creation of other gliders, which then bounce off bumpers to produce other ships. Finally, we reach the second-to-last oscillator in the line, which has an impact on the small ship, which then has an impact on the large ship, producing a glider that finally leaves between two other gliders in the void.

And the little ship at the top encounters one last oscillator that transforms it into a glider and sends it back into the line. That’s clever, isn’t it? Nothing is wasted, everything works.

We've got a nice factory. I like it, and I also like the flows of ships crossing without ever hitting each other. It's a well-oiled machine.

Well, there are plenty of other, even bigger factories, producing even bigger ships. This one is pretty intimidating. It produces 6-engine Corderships, and it's quite something.

It's like watching a huge space factory in action. I think It's pretty awesome to watch. Let’s keep moving.

Maybe it’s a lot of information, but we can catch our breath. Our next encounter allows us to do so. This is a "Mathusalem", a configuration that requires a large number of generations to stabilize and that becomes much larger than its initial configuration at a given stage in its evolution.

Except that we're at the very beginning, and this specific Mathusalem takes 52,513 generations to stabilize. So there's still a long time to go before we see the end of it, and that allows us to catch our breath. Who knows what it'll look like in the end?

We're already drifting away. We won't know, that's life. I like this one.

This is the "Pony Express". This is what we call a puffer, a configuration that moves like a ship, but leaves leftovers behind. Typically, the configuration I discovered earlier, well, I didn't discover it because it's here in the leftovers of the Pony express, which can prevent us from getting through, so we just have to hurry.

Like that. So I repeat, this is a puffer that leaves leftovers behind, and many ships might leave leftovers but they manage to clean up after themselves. This one, for example, leaves a long trail of leftovers behind it, but it uses a sweeper ship to make it collapse.

This ship does the same with a dominos game. This one with little missiles. This one's really special: the leftovers exit at the back, are transformed into gliders, go up through the center, and are eliminated at the front by blinkers that move back to the right place each time.

I really like this one. Ah, this one is the Backrake 3. It's another puffer, but in a very particular subcategory of puffers, the rake.

Basically, it also leaves leftovers behind. Except these leftovers are ships. And behind it, it's starting to get impressive.

But that's nothing compared to this. Here is the Breeder 1, the first breeder ever discovered. It's a big configuration, but it's still tiny compared to what it can become because its growth is infinite.

In fact, it's even more than that. The Breeder 1 is the first configuration found to exhibit what we call a quadratic growth, which we summarize as: "the infinite growth whose rate is proportional to the square of the number of periods (T) elapsed since the beginning of the observation of the phenomenon. " Basically, this means that its growth is not linear, it's not constant, but it accelerates over time.

And if you're wondering how this is possible with the Breeder 1, let me explain. This configuration is a puffer, a configuration that moves forward like a ship, but leaves leftovers behind. Those of you who've been following closely might think that this is a rake.

If you remember, this is the puffer sub-configuration that leaves behind not only leftovers, but ships. This is what we're looking at, right? Ships produced by the Breeder 1.

Well, not exactly. In fact, the Breeder 1 isn't a rake, it's a puffer The twist is that the Breeder 1 produces factories as leftovers. These leftovers are glider factories that stay at the same place forever, producing gliders over and over.

And that’s what we get. Okay, we've figured out that we can make big things, but it's not the most interesting, the most interesting thing starts smaller. Let’s go back to the basics.

One of John Conway's goals when he created the Game of Life was to have a game with simple rules to see how complex things could get. There’s one thing that could really fulfill this principle of complexity, and that Conway was hoping from the start, that was to make his game Turing complete. So I'll give you the definition of Turing complete (Homemade definition): It's a fundamental principle in computer science, which refers to the ability of a computing system to simulate any Turing machine, which would mean, without going into too much detail, that it could run any algorithm or solve any computational problem, provided that it was formally described and given enough space and time.

Is it possible to do that with the Game of Life? Is it possible to switch from ships to a computer? Well, we can try.

First of all, we need to be able to send signals, to find substitutes for electricity. That's something we can do with progenitors. We can send gliders at regular or irregular intervals.

Then, we need to be able to use these signals with logic gates. The "and" gate, for example, is there to check that it's receiving two currents. Could we do this in the Game of Life?

Well, let's place our two currents, A here, B here, not yet activated. The aim would be to have a door that would only let a current pass through here if it received two signals, so C would only activate if A and B were activated. To do this, we can use an activated progenitor that sends a current X in this direction, and it's this X that will act as the gate.

Now, if we only activate A, the flow starts, but the current is interrupted by X and doesn't reach C. So it doesn't work. If we only activate B and, just as before, the flow is interrupted by X.

So there's nothing in the end. Now, if we activate A and B at the same time, B will interrupt X and allow A to go through. This results in a current reaching C.

We have an "and" gate that only activates when it receives two signals. Okay, that's not bad. That's how players manage to make logic gates.

And with the same principle, we can build the two other main logic gates, "or" and "not", used to create all the other logic gates. Then, reflectors are used to make adapters that allow signals to be converted and adjusted between the different parts of the circuit to ensure smooth communication between them, allowing these logic gates to be connected to perform more complex operations. It can be used as an adder to perform additions of binary numbers.

This is an essential component for building arithmetic entities capable of more complex calculations within this environment. Let’s continue. The players build what we call an "ALU", an "Arithmetic & Logic Unit", responsible for arithmetic and logic operations, which allows data to be manipulated according to programmed instructions, in this case with 8-bit instructions.

Now it's essential to store all this information. Can we do that? Can we create a memory in the Game of Life?

Of course we can. Here's a memory unit that uses “RS” flip-flops and logic gates to store bits of binary information to keep the state of each piece of information until an opposite instruction is received, but it also serves to read and write instructions with three modules on the far left to read and decode addresses. And what do we do with all this?

Well, we need instructions. Here's a program with the decoder, instructions, addresses, data that can be modified with a Python script to program the computer we're building, and how do we see what we're doing? Well, here's the screen.

. . Which is starting to fill up according to instructions.

Except that it takes a long time. Wow, it's really long and my PC struggles a bit when I speed up. But we've got it, our computer “by Nicolas Loizeau”, we've got our Turing complete computer with a grid and two rules.

And Conway had already thought about this when he created his game. Except that it didn't seem so obvious at first. What made him realize that it should be possible was the discovery of the glider, for which he had already imagined the potential for data transmission.

Our glider is now close to the end of its journey. It has seen many things: still lifes, oscillators, ships, Corderships, factories, puffers, rakes, breeders. But I guarantee you it has never seen what it's getting close to.

Because what makes Conway's Game of Life being Turing complete so interesting, and why I told you about it, is not just to show you that you can make additions inside, it’s to finish in the best way possible by reminding you that being Turing complete means being able to run any algorithm. At this point, we couldn't ask for a better way to end our journey. And when I see this, I tell myself: “It's amazing what we can do with so little.

” “But why limit ourselves to so little? ” And that sentence was the start of a new adventure for me, it was my gateway to a world far from stopping at the limits of Conway's Game of Life. Firstly, because there are plenty of Games of Life out there, created by people who didn't stop at the discovery of configurations in the original Game of Life, but who thought: “Well, that's exciting, but we're going to change the rules.

” Highlife, for example, takes the same basics, deciding instead that a cell can become alive if it is surrounded by exactly six living cells. This may sound like nothing, but it completely changes the dynamics of the game with the appearance of replicators, configurations that can reproduce themselves exactly at a certain distance from themselves, with a defined number of generations. Conway himself said about this game: “It seems to me that this is the game I should have found, as it's so rich in beautiful things.

” And there are so many variants: Wireworld, which simulates the performance of electric wires, Langton's ant, in which an ant moves on a grid similar to the Game of Life, changing the state of the cells it passes over and following the direction indicated by the cell it lands on. Turmites uses the same principle with more color shades for the cells and more than two directions of rotation. And personally, I just keep going on, discovering more and more.

Lenia is another example. It's a kind of new version of Conway's Game of Life. It's a continuous, multi-state cellular automaton model.

Basically, the goal is to make it more organic. It drops the idea of progressing generation by generation, and instead evolves continuously over time, and also drops the grid idea, replacing it with a continuous space allowing cell configurations to have not only one state, dead or alive, 0 or 1, but allowing the use of decimals, so a cell can now be 0. 23 or 0.

77, giving life to creatures that immediately look more organic, like real little things, and whose creator later allowed the use of AI to learn how to move more optimally. And I continue my journey and come across so many algorithms and so many models that I'll probably have to tell you about them in a second video. What's clear is that I'm becoming obsessed with the creation of artificial life.

I'm falling headlong into what's known as artificial life. This is a field of research that studies man-made systems imitating the behaviors, processes and phenomena of biological life. In other words, it's about exploring the fundamental principles of life, and creating artificial life forms in physical or virtual environments.

The potential applications of artificial life are explored in a wide range of fields, from robotics to medicine. This also raises ethical and philosophical questions about our understanding of life and our role as creators of living systems. One thing's for sure, I'm getting addicted to these simulations and I’m looking for more and more realism in them.

So I'm on my PC, watching the little creatures of Lenia doing their own things in front of me, and I’m telling myself: “It's crazy though, they look like real little things we could observe with a microscope. ” Then I step away from my screen and realize that the most fascinating thing about “artificial life” is actually Life itself. And I'm not trying to show off.

But I can honestly say, as it happened to me, that the study of artificial life has made me aware, or rather re-aware, of the beauty and the complexity of the things that we’re made of and surround us. It may seem strange to need to study ersatz life to realize the beauty of life. But that's how the human brain works.

Well, we get used to things. It takes us a few months, a few days, a few hours to take the wonders that surround us for granted, to consider them as banalities. So if we can change our perspective, we shouldn't hesitate to do so.

And that's what I'm suggesting, to join me in the Laniakea supercluster, then in the local group, then in the Milky Way and finally in the solar system, where we find, warmed by a yellow star composed of 75% of hydrogen, a little blue planet which, 3 to 4 billion years ago, saw the birth in its oceans of little creatures that we could have, if we had been present at the time, observed in the same way as we observed the Game of Life, wondering what such little things could do, what they could become with enough space and time. We could have looked at them as we would look at a small simulation, with the same curiosity we've developed for Conway's little creatures. We could have looked at these little pieces of life, letting ourselves get carried away by the possibilities and wondering what they could become.

The advantage for us is that we don't have to wonder.