>To be fair, I'm not even sure if Numenta's networks could perform competently at any classic benchmarks (I'm guessing that if they could, it would take some wo

>To be fair, I'm not even sure if Numenta's networks could perform competently at any classic benchmarks (I'm guessing that if they could, it would take some work to get them to do so), and I have no idea what new problems it could work on. But they really do need to reframe the conversation and emphasize that sort of innovation if they want to be taken more seriously - focusing on neuroscience underpinnings is not a great move if they're not engaged in research that can actually win over neuroscientists, and just pointing out that they're focusing on those things is not a way to win over industry ML folks if they don't have any results to point at. It was definitely a jab, but I've also got some sympathy for their project. I genuinely agree that, well, theoretical and computational neuroscience need to become more genuinely computational! We're seeing an emerging computational paradigm for neuroscience that isn't just about jamming "network architectures" or "neural circuits" together and hoping something works; it supposedly has strong mathematical principles. Ok, so where's the code? Sincere question. Some papers do simulations in Matlab, R, or Python that's just not shared. This includes even papers that purport to be applying these neuroscience-derived principles to robotics problems. Computational cognitive science does a bunch better: their custom-built Matlab gets shared! If we really believe our theories, we should put them to the computational test. If we put them to the test and they don't work well, we should either revise the theories, or revise the benchmarks. Maybe ImageNet classification scores are a bad idea for how to measure precise, accurate sensorimotor inference! New benchmarks for measuring the performance of "real" cognitive systems are a great idea! Let's do it! But that requires that we do the slow work of trying to merge theoretical/computational neurosci, cognitive science, and ML/AI back together, at least in some subfields. This is challenging, because nobody's gonna give us our own journal for it until a few prestigious people advocate for one.