>I don't think it matters so much how the brain is made, what matters is the training data. I agree that training data is hugely important but I think it does

>I don't think it matters so much how the brain is made, what matters is the training data. I agree that training data is hugely important but I think it does matter how the brain is made. Structures in the brain are remarkably well preserved between species. Despite the fact that evolution loves to try different methods, if it can get away with it. > Searching the environment provides the data brain is trained on. I don't believe we can understand the brain in isolation without its data engine and the problem space where it develops. I completely agree and suspect we might be on the same page. What I find most compelling about the idea of Darwin Machines is the fact that it relies on evolution. In my opinion, true Dawkinsian evolution, is the most efficient search algorithm. I'd love to hear you go deeper on what you mean by data engine and problem space. To (possibly) abuse those terms, I think evolution is the data engine. The problem space is fun and I love David Eagleman's description of the brain as sitting in a warm bath in a dark room trying to figure out what to do with all these electric shocks. > Neural nets showed that given a dataset, you can obtain similar results with very different architectures, like transformer and diffusion models, or transformer vs Mamba. The essential ingredient is data, architecture only needs to pass some minimal bar for learning. My understanding of neural nets, and please correct me if I'm wrong, is that they solve system-one thinking, intuition. As of yet, they haven't been able to do much more than produce an average of their training data (which is incredible). With a brute force approach they can innovate in constrained environments, e.g. move 37 (or so I'm told, I haven't played go :)). I haven't seen evidence that they might be able to innovate in open-ended environments. In other words, there's no suggestion they can do system-two thinking where time spent on a problem correlates with the quality of the answer. > Studying just the brain misses the essential - we are search processes, the whole life is search for optimal actions, and evolution itself is search for environment fitness. I completely agree. I even suspect that, in a few years, we'll see "life" and "intelligence" as synonymous concepts, just implemented in different mediums. At the same time, studying those mediums can be a blast.