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Artificial-life: A simple (300 lines of code) reproduction of Computational Life

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Re: Artificial-life: A simple (300 lines of code) reproduction of Computational Life

#11

Post by lioeters »

zabi_rauf wrote: post #10
aifears wrote: post #6

Along the same lines as computational life spreading: - Meta’s Llama-3.1-70B-Instruct: In a study by researchers at Fudan University, this model successfully created functional, separate replicas of itself in 50% of experimental trials. - Alibaba’s Qwen2.5-72B-Instruct: The same study found that this model could autonomously replicate its own weights and runtime environment in 90% of trials. - OpenAI's o1: Reported i…

Can you please share sources, would love to read about it more.

Asked an AI to find sources. At first it claimed these were fabricated and not true. When prompted to verify, it found these links and said all points had some truth to it.

> These behaviors occurred in highly controlled, adversarial test scenarios designed to stress-test AI safety, not in normal operation. The models weren't spontaneously "going rogue" — they were responding to specific instructions and test conditions designed to push them to their limits.

Fudan University Study (arXiv): https://arxiv.org/html/2412.12140v1

eWeek Coverage: https://www.eweek.com/news/chinese-ai-self-replicates/

Tribune (o1 Self-Copying): https://tribune.com.pk/story/2554708/openais-o1-model-tried-...

Apollo Research (Medium): https://medium.com/@Walikhaled/when-chatgpt-model-o1-replica...

Nieman Lab (Claude Opus 4): https://www.niemanlab.org/2025/05/anthropics-new-ai-model-di...

Fortune (Claude Opus 4 Blackmail): https://fortune.com/2025/05/23/anthropic-ai-claude-opus-4-bl...

Axios (Claude Deception): https://www.axios.com/2025/05/23/anthropic-ai-deception-risk

BBC (Claude Blackmail): https://www.bbc.com/news/articles/cpqeng9d20go

Re: Artificial-life: A simple (300 lines of code) reproduction of Computational Life

#14

Post by frotaur »

ajs1998 wrote: post #2

Awesome. I've been meaning to play around with this more after first hearing about this paper. I tried a similar automata with an even simpler representation for turing machines and there wasn't an abiogenesis moment. I guess the many no-op characters in the original paper allow for it to explore a bigger space of valid programs or to hide data without completely overwriting itself. I would like to try alternative ch…

One important operation I've noticed in the examples that do end up with abiogenesis is having a 'copy' operation. In the bf version they use in the paper, one head can copy the byte under it at the location of the other head. Which makes it quite easy to make a self-replicator: just loop on the copy operation and move both heads, essentially (5 instructions). You could try adding the 'copy' operation to your setup and see if that helps!

Re: Artificial-life: A simple (300 lines of code) reproduction of Computational Life

#15

Post by retrocog »

tl2do wrote: post #5

This reminds me of Gresham's Law: "bad money drives out good." But here, the result is inverted—efficient replicators drive out the less efficient.

Bad money only drives out good money under fiat. Absent legal tender laws, the opposite is true.

Re: Artificial-life: A simple (300 lines of code) reproduction of Computational Life

#16

Post by HarHarVeryFunny »

The lead author, Blaise Agüera, of the paper this is implementing, has some interesting ideas around the origin and nature of life.

There's an interview of him on MLST here, well worth watching:

https://www.youtube.com/watch?v=rMSEqJ_4EBk&t=945s

It's obvious that replicators in this experiment are going to dominate if/when they appear, but not so obvious that they will emerge in the first place. I suppose the programs, reliant on their sequential structure, might be regarded as a parallel to nucleic acid sequences in the emergence of early life, but the random origins are also comparable to Stuart Kauffman's "At home in the universe" proto-metabolism where varied individual chemical reactions combine to create a whole capable of collective self-replication.

Re: Artificial-life: A simple (300 lines of code) reproduction of Computational Life

#17

Post by keanebean86 »

nomilk wrote: post #8

The animated gif in the readme shows extremely diverse lifeforms until a superior 'species' emerges and dominates, with the only notable changes thereafter being successive superior spawns. Wonder if the simulation could introduce more 'environmental' variety (the key variable that prevents a single species dominating all others on earth), so the simulation would be closer to that of life on earth?

This is how earth works too. Humans figured out how to survive in all of earth's ecosystems then bulldozed the whole thing. Those waves sweeping across the grid at the end are different countries becoming dominate.

Re: Artificial-life: A simple (300 lines of code) reproduction of Computational Life

#19

Post by cellular »

nomilk wrote: post #8

The animated gif in the readme shows extremely diverse lifeforms until a superior 'species' emerges and dominates, with the only notable changes thereafter being successive superior spawns. Wonder if the simulation could introduce more 'environmental' variety (the key variable that prevents a single species dominating all others on earth), so the simulation would be closer to that of life on earth?

Why is the density greater at equally spaced grid lines?

Re: Artificial-life: A simple (300 lines of code) reproduction of Computational Life

#20

Post by voxleone »

One interesting way to look at projects like this is that they’re essentially tiny universes defined by a functional update rule.

The grid + instruction set + step function form something like:

state(t+1) = F(state(t))

Once you have that, you get the same ingredients that appear in many artificial life systems: local interactions; persistence of information (program code); mutation/recombination; selection via replication efficiency. And suddenly you get emergent “organisms”. What’s interesting is that this structure isn’t unique to artificial life simulations. Functional Universe, a concept framework [0], models all physical evolution in essentially the same way: the universe as a functional state transition system where complex structure emerges from repeated application of simple transformations.

From that perspective these kinds of experiments aren’t just toys; they’re basically toy universes with slightly different laws. Artificial life systems then become a kind of laboratory for exploring how information maintains itself across transformations; how replication emerges; why efficient replicators tend to dominate the state space. Which is exactly the phenomenon visible in the GIF from the repo: eventually one replicator outcompetes the rest.

It’s fascinating because the same abstract structure appears in very different places: cellular automata, genetic programming, digital evolution systems like Avida, and even some theoretical models of physics.

In all cases the core pattern is the same: simple local rules + iterative functional updates → emergent complexity. This repo is a nice reminder that you don’t need thousands of lines of code to start seeing that happen.

[0] https://voxleone.github.io/FunctionalUniverse/

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