5 ms·

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.

by eyvindn 2mo ago

chychiu 2mo ago
Super cool work! What's next? Do you think with longer memory limits more interesting programs might emerge? Or is it substrate dependent?
- eyvindn 2mo ago
  there are many bottlenecks in the substrate - memory limits being one of them. other things like the A-B concatenation inherited from the bff paper also severely limit the possible dynamics. understanding and avoiding these bottlenecks are some of our next steps!
jrowen 2mo ago
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?
- eyvindn 2mo ago
  this is my personal take; 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?)
  - jrowen 2mo ago
    Yes, that's the other thing -- starting from a soup, it takes a very long time to know if the parameters that have been chosen are conducive to evolving something we would consider intelligent. The gif in vicgalle's github is largely inscrutable (even if you understand what it represents in aggregate), and I imagine one would be staring at something like that for quite some time. Obviously, you have to "cheat" biology somewhere, we don't have hundreds of millions of years. Neural networks cheat by essentially throwing out the whole evolutionary process and environment that led to the brain, attempting to make a model that works like the brain. IMO that is too much cheating. Starting with a substrate of random bits of assembly code strikes me as a little too low-level (which is not to dismiss this research at all, I think it's valuable, I'm just spitballing big-picture ideas). Have you considered starting with something like the Unreal or Unity engine, or even Minecraft? You would lose the elegant and unopinionated search space of all programs, and you would have to engineer a more structured system (kind of like Spore but more simulation than game), but I feel like you might be able to get some more readily relatable behaviors sooner?
    - jrowen 2mo ago
      And maybe that just isn't really your area of work, I get that it would be a totally different project (like saying to a C++ guy "have you tried JavaScript?"), but that's why I think it's interesting to ask, because it really is a question of understanding this entire integrated "stack" of biology and what parts of it are vital.
lioeters 2mo ago
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. https://distill.pub/2020/selforg/ 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.

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.

by eyvindn 2mo ago

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.

chychiu 2mo ago

Super cool work! What's next? Do you think with longer memory limits more interesting programs might emerge? Or is it substrate dependent?

eyvindn 2mo ago
there are many bottlenecks in the substrate - memory limits being one of them. other things like the A-B concatenation inherited from the bff paper also severely limit the possible dynamics. understanding and avoiding these bottlenecks are some of our next steps!

jrowen 2mo ago

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?

eyvindn 2mo ago
this is my personal take; 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?)
- jrowen 2mo ago
  Yes, that's the other thing -- starting from a soup, it takes a very long time to know if the parameters that have been chosen are conducive to evolving something we would consider intelligent. The gif in vicgalle's github is largely inscrutable (even if you understand what it represents in aggregate), and I imagine one would be staring at something like that for quite some time. Obviously, you have to "cheat" biology somewhere, we don't have hundreds of millions of years. Neural networks cheat by essentially throwing out the whole evolutionary process and environment that led to the brain, attempting to make a model that works like the brain. IMO that is too much cheating. Starting with a substrate of random bits of assembly code strikes me as a little too low-level (which is not to dismiss this research at all, I think it's valuable, I'm just spitballing big-picture ideas). Have you considered starting with something like the Unreal or Unity engine, or even Minecraft? You would lose the elegant and unopinionated search space of all programs, and you would have to engineer a more structured system (kind of like Spore but more simulation than game), but I feel like you might be able to get some more readily relatable behaviors sooner?
  - jrowen 2mo ago
    And maybe that just isn't really your area of work, I get that it would be a totally different project (like saying to a C++ guy "have you tried JavaScript?"), but that's why I think it's interesting to ask, because it really is a question of understanding this entire integrated "stack" of biology and what parts of it are vital.

lioeters 2mo ago

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. https://distill.pub/2020/selforg/ 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.