I think it’s a bit overzealous to say LLMs are the wrong approach. It is possible the math behind them would be useless to a true AI, but as far as I can tell, the only definitive statement we can make right now is that they can’t be the whole approach. Still, you’re absolutely right that there is a huge set of operations we haven’t figured out yet if we want a genuine AI.
My understanding of consciousness is that it isn’t one single sequence of operations, but a set of simultaneous ones. There’s a ton of stuff all happening at once for each of our senses. Take sight, for example. Just to see things, we need to measure light intensity, color definition, and spacial relationships, and then mix that all together in a meaningful way. Then we have to balance each of our senses, decide which one to focus on in the moment, or even to focus on several at once. And that hasn’t even touched on thoughts, emotions, social relationships, unconscious bodily functions, or the systems in place that let us switch things back and forth between conscious and unconscious, like breathing, or blinking, or walking, and so on. There are hundreds, maybe thousands of operations happening in our brains simultaneously at any given moment.
So, without a doubt, LLMs aren’t the most energy efficient way to do pattern recognition. But I find it hard to believe that a strong system for pattern recognition would be fully unusable in a greater system. If/when we figure the rest out, I’m sure an LLM could be used as a piece of a much greater puzzle… if we wanted to burn all that energy.
They do simultaneous workloads but each load is essentially performing the same function. A person, on the other hand, is a huge variety of differing functions all working in tandem; a set of vastly different operations that are all inextricably linked together to form who we are. No single form of generative algorithm is anything more than a tiny fraction of what we think of as a conscious being. They might perform the one operation they’re meant for on a much greater scale than we do, but we are nowhere near linking all those pieces together in a meaningful, cohesive stream.
Edit, think of the algorithms like adding more cores to a CPU. Sure, you can process workloads simultaneously, but each workload is interchangeable and can be arbitrarily assigned to each core or thread. Not so with people. Every single operation is assigned to a specialized part of the brain that only does that one specific type of operation. And you can’t just swap out the RAM or GPU; every piece is wired specifically to interact with only the other pieces they were grown together with.