This is a cool finding; I did not know it was still an active area of study with all the work on ML and LLMs these days. I have done some amateur exploration of the space and the result does not surprise me: https://github.com/ehbar/evol
Tierra[0], written by Tom Ray[1], immediately comes to mind. I was captivated when I read about it, as a teenager, in Steven Levy's "Artificial Life"[2]. Having played Core War[3], the description of Tierra in Levy's book inspired me to play around with making a virtual machine in Turbo Pascal and trying my hand at making a pale and naive clone. It was a lot of fun, and arguably has influenced a lot of my thinking about the origin of biological life.
> We show that when random, non self-replicating programs are placed in an environment lacking any explicit fitness landscape, self-replicators tend to arise. We demonstrate how this occurs due to random interactions and self-modification, and can happen with and without background random mutations. We also show how increasingly complex dynamics continue to emerge following the rise of self-replicators.
I've long felt that Artificial Life or an approach rooted in that is the best way to get a novel and interesting machine intelligence. The breakthrough with more conventional methods was surprising, but it still seems like it might hit a ceiling (or may have already?).
The major thing that's always stumped me is how to design a universal fitness function that can take you from soup to a brain. IRL there is "the environment" which contains resources that need to be consumed to survive, and the majority of evolution (senses, bodyforms, metabolic pathways, etc) is based on navigating this environment and extracting energy. Can we say that life or intelligence is a meaningful concept without this universal background reference plane and survival game?
One of the things I think is limiting about conventional systems is what I call the "brain-in-a-vat" problem. They don't "exist" in any meaningful sense, they don't "experience" anything, they don't have any "reason" or "motivation" to do or develop anything.
I think of something more like a video game. The world of World of Warcraft or Call of Duty is a mathematical construct that doesn't truly reflect how our world works, but, through a window we can interpret it in a way that we understand and relate to. Some kind of video game environment with more relaxed and "open-ended" parameters and a simulated survival mechanism would be an interesting experiment.
The abstract mentions metabolic constraints. Can you share more of your thoughts or conceptual approach to this?
The projects being worked on by the Paradigms of Intelligence team at Google are so fascinating. The book "What is Intelligence?" by the founder is brilliant and mind-opening. While reading the posted article and related topics, I rediscovered a rich collection of papers on Differentiable Self-organizing Systems.
I'd read through the whole site and all the papers there when they were published, and the questions they raise are, to me, some of the most interesting intellectual themes. Then I realized you're an author on most of the articles, as well as Michael Levin, whose research I've been deeply curious about, listening to his talks, reading his papers. It makes sense that there's a common thread and convergence, but also a pleasant surprise.
Just wanted to express my appreciation for the work you and your cohorts are doing, how it's pushing the boundary and depth of our collective understanding. I don't have a question per se, but I feel that this area of inquiry seems both underappreciated by the general public and at the same time fairly open to those outside of academia - what might be called experimental mathematics and exploratory computer science. Maybe there's room for "popular-science" type authors, to explain how cool (ha) these ideas are, to translate the technical material to more digestible language for a wider audience.
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[ 3.5 ms ] story [ 50.7 ms ] thread[0] https://tomray.me/tierra/whatis.html
[1] https://en.wikipedia.org/wiki/Thomas_S._Ray
[2] https://www.stevenlevy.com/artificial-life
[3] https://en.wikipedia.org/wiki/Core_War
Evolution also eventually gets frustrated and creates the brain, capable of in context learning.
Maybe we should take some notes from these massively parallel, shallow, and highly recurrent constructions.
https://arxiv.org/abs/2406.19108
> We show that when random, non self-replicating programs are placed in an environment lacking any explicit fitness landscape, self-replicators tend to arise. We demonstrate how this occurs due to random interactions and self-modification, and can happen with and without background random mutations. We also show how increasingly complex dynamics continue to emerge following the rise of self-replicators.
The major thing that's always stumped me is how to design a universal fitness function that can take you from soup to a brain. IRL there is "the environment" which contains resources that need to be consumed to survive, and the majority of evolution (senses, bodyforms, metabolic pathways, etc) is based on navigating this environment and extracting energy. Can we say that life or intelligence is a meaningful concept without this universal background reference plane and survival game?
One of the things I think is limiting about conventional systems is what I call the "brain-in-a-vat" problem. They don't "exist" in any meaningful sense, they don't "experience" anything, they don't have any "reason" or "motivation" to do or develop anything.
I think of something more like a video game. The world of World of Warcraft or Call of Duty is a mathematical construct that doesn't truly reflect how our world works, but, through a window we can interpret it in a way that we understand and relate to. Some kind of video game environment with more relaxed and "open-ended" parameters and a simulated survival mechanism would be an interesting experiment.
The abstract mentions metabolic constraints. Can you share more of your thoughts or conceptual approach to this?
https://distill.pub/2020/selforg/
I'd read through the whole site and all the papers there when they were published, and the questions they raise are, to me, some of the most interesting intellectual themes. Then I realized you're an author on most of the articles, as well as Michael Levin, whose research I've been deeply curious about, listening to his talks, reading his papers. It makes sense that there's a common thread and convergence, but also a pleasant surprise.
Just wanted to express my appreciation for the work you and your cohorts are doing, how it's pushing the boundary and depth of our collective understanding. I don't have a question per se, but I feel that this area of inquiry seems both underappreciated by the general public and at the same time fairly open to those outside of academia - what might be called experimental mathematics and exploratory computer science. Maybe there's room for "popular-science" type authors, to explain how cool (ha) these ideas are, to translate the technical material to more digestible language for a wider audience.