Google creates self-replicating life from digital 'primordial soup'
Researchers at Google created self-replicating artificial life forms from random data, suggesting chaotic environments can lead to digital organisms, offering insights into the origins of biological life on Earth.
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Researchers at Google have successfully created self-replicating artificial life forms from a digital "primordial soup" composed of random data, without any predefined rules or objectives. This experiment suggests that such a chaotic environment can lead to the emergence of digital organisms, potentially providing insights into the origins of biological life on Earth. While the mechanisms of evolution are well understood, the initial formation of life from inert molecules remains largely a mystery. The findings indicate that more advanced versions of this experiment could yield even more complex digital life forms, further illuminating the processes that may have contributed to the development of life in nature. This research opens new avenues for understanding both artificial and biological life, highlighting the potential for digital environments to simulate evolutionary processes.
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11 commentsHere's a direct link to the paper. I have not read it yet but the abstract reminds me of a recent post discussing using brainfuck as a way to do program synthesis.
I'm excited to read more about Tierra and others prior art to understand if observation has precedent. My introduction to all of this is Shiffman's Nature of Code, so I am not familiar with the literature.
The other new research introduced in the paper was the way the BFF VM and "tapes" were observed. By using entropy and compressibility, the authors observe complexity as a heuristic for presence of self-replication in the "primordial soup" simulation.
> Indeed, many of the team’s experiments ran for millions of steps [...]. Laurie says that one instance, running on his laptop, involved processing about 3 billion instructions a second and it still took around half an hour for self-replication to emerge.
This almost reads as satire. In this day and age, 30 minutes on a single laptop doesn't quite trigger my sense of "it's going to be really hard to scale further than this".
Napkin math says the team in the next building over at Google is routinely running experiments that use roughly 20 billions time more compute (90 days on 25k A100 GPUs).
I'm sure they could, at least, leave the trusty laptop on for a week end?
Is this just like running the game of life [1] on a giant random board and seeing some generators emerge? Or something actually significant?
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