> But that leaves large and important areas that GPTs are entirely unfit for: Real-time problem solving in dynamic environments, understanding and reacting to current events or spatial reasoning and coordination in the physical world.<p>It is important to recognize the limitations of these deep neural networks and especially GPTs which both have been hyped to the point where most see it as the solution to everything; since many deep-learning supporters continue to compare it to the human brain, despite the severely limited explainability in these models to the point where not even researchers know what it is doing.<p>It's one of the reasons why there's very low trust in deep neural networks in general. Humans can be held to account for their actions but with almost all these neural network systems cannot be held to account when something goes wrong and accept the output as the answer whilst 'it is thinking' or 'reasoning'.<p>> The mechanism behind real world complex systems requires both simple rulesets and a communicative fabric that allows for real time feedback loops. For flocks of starlings this can be as easy as keeping eye contact with the next bird. For Termites, it is pheromone trails. For societies, it is language, reputation and status. For capital markets, it is money. And for the internet, its the physical wiring and network architecture that makes it all possible.<p>As long as this solution provides transparency and explainable results rather than giving an answer from a black box system then I'm looking forward to this approach.