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Earlier quoted context omitted.
If evolution had access to TSMC's process technology, do you think it wouldn't leverage it? The signals in my AMD CPU propagate ~1,000,000x faster than the ones in my brain.
^ yes. this is what we hope.
Interesting. But, evolution is way too unconstrained to provide us a path to "agi". It would require too much compute. 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.
If evolution had access to TSMC's process technology, do you think it wouldn't leverage it? The signals in my AMD CPU propagate ~1,000,000x faster than the ones in my brain.
An independent reproduction of the main result: https://github.com/vicgalle/coevolution-soup
authors here - happy to answer any questions! we’re excited for this line of work and see this as the first step on a longer journey.
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?
authors here - happy to answer any questions! we’re excited for this line of work and see this as the first step on a longer journey.
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.
An independent reproduction of the main result: https://github.com/vicgalle/coevolution-soup
This is every cool research. Do you have any idea why the authors chose Z80 as the program language? I have seen other studies in the same spirit that use simpler toy languages like Brainfuck ( https://arxiv.org/abs/2406.19108 ) and I wonder if you could get higher execution speed if you didn't have to execute so much emulator code. The programs/genomes are extremely tiny. I would be very interested to see what kind…
second question is a good question :)
authors here - happy to answer any questions! we’re excited for this line of work and see this as the first step on a longer journey.
Super cool work! What's next? Do you think with longer memory limits more interesting programs might emerge? Or is it substrate dependent?
authors here - happy to answer any questions! we’re excited for this line of work and see this as the first step on a longer journey.
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 envir…
I agree, for the same reasons you mentioned, resource constraints will need to be baked in (they are already, to some extent, if you consider the constrained resource to be z80-CPU-seconds the program has access to). something more akin to energy in our real world, which can be manipulated, aggregated, shared, pooled, stolen, etc feels more natural, however.
imo meaningful intelligence could conceivably developed in a soup (even in-silico), unclear on what timeline, but grounding it with human and/or real-world data is necessary to make it useful to us (bio-compatible, if you will?)