I agree, I think we are in the latter phase already. LLMs were a huge leap in machine learning, but everything after has been steps on top + scale.
I think we would need another leap to actually meet the markets expectations on AI. The market is expecting AGI, but I think we are probably just going to do incremental improvements for language and multi modal models from here, and not meet those expectations.
I think the market is relying on something that doesn't currently exist to become true, and that is a bit irrational.
Transformers aren't it, though. We need a new fundamental architecture and, just like every step forward in AI that came before, when that happens is a completely random event. Some researcher needs to wake up with a brilliant idea.
The explosion of compute and investment could mean that we have more researchers available for that event to happen, but at the same time transformers are sucking up all the air in the room.
Several people hinted at the limits this technology was about to face, including training data and compute. It was obvious it had serious limits.
Despite the warnings, companies insisted on marketing superintelligence nonsense and magic automatic developers. They convinced the market with disingenous demonstrations, which, again, were called out as bullshit by many people. They are still doing it. It's the same thing.
I think we would need another leap to actually meet the markets expectations on AI. The market is expecting AGI, but I think we are probably just going to do incremental improvements for language and multi modal models from here, and not meet those expectations.
I think the market is relying on something that doesn't currently exist to become true, and that is a bit irrational.