LLMs, plus broadly sourced yet expertly curated training sources, plus clever harnesses, plus RAS, etc. do an ever better job of synthesizing their training set into useful responses. For some use cases like coding, that's very useful now and likely to get at least somewhat better before reaching limitations based on the training set.
That's not going to reach AGI, mainly because today's recipe for AI products isn't built to be AGI. Some people believe it will reach AGI because the performance and applicability of LLMs was emergent. There's a case to be made that AGI could be similarly emergent. After all, what we intuitively call our consciousness emerged from a network of neurons.
I don't buy it, mainly because the network of neurons and how they interact in our wet slow electrochemical brains, while being in theory mathematically equivalent to a software neural network, isn't sufficiently well understood to tell us how close the software neural network is to being practically equivalent. The odds of consciousness emerging from the same neural network that gave us LLMs without some sort of theoretical breakthrough seems very small.
That's not going to reach AGI, mainly because today's recipe for AI products isn't built to be AGI. Some people believe it will reach AGI because the performance and applicability of LLMs was emergent. There's a case to be made that AGI could be similarly emergent. After all, what we intuitively call our consciousness emerged from a network of neurons.
I don't buy it, mainly because the network of neurons and how they interact in our wet slow electrochemical brains, while being in theory mathematically equivalent to a software neural network, isn't sufficiently well understood to tell us how close the software neural network is to being practically equivalent. The odds of consciousness emerging from the same neural network that gave us LLMs without some sort of theoretical breakthrough seems very small.