It seems some companies adopting GenAI at this stage are doing so, at least in part, because they want to believe (that they can replace workers), rather than out of any sober analysis of what it can actually do. Maybe there's an element of FOMO too, and companies wanting to use GenAI because they hear everyone talking about it.
No doubt LLMs will continue to improve, but what remains to be seen is if there will be a direct path from LLMs to AGI (which is where the real value gets unlocked), or if we'll just continue to see quantitative improvement in benchmark scores, hallucination reduction, etc, but not much qualitative change in the types of task they are capable of.
I do think that AGI is inevitable, maybe not even that far off (but certainly not next 5 years, probably not next 10 years *), but there's a lot missing from LLMs to get there, and it seems that at least one critical piece, online learning, may require a different approach.
* Note that it's already been 7 years since the transformer paper came out, and all we've really seen since then is a bunch of engineering work in making them more efficient and how best to train them. We haven't yet seen any advances in "cognitive architecture", or even any widespread recognition that there is a need to do so. If all people are doing for the foreseeable future is building pre-trained LLMs, then that is all we will get.
It seems some companies adopting GenAI at this stage are doing so, at least in part, because they want to believe (that they can replace workers), rather than out of any sober analysis of what it can actually do. Maybe there's an element of FOMO too, and companies wanting to use GenAI because they hear everyone talking about it.
No doubt LLMs will continue to improve, but what remains to be seen is if there will be a direct path from LLMs to AGI (which is where the real value gets unlocked), or if we'll just continue to see quantitative improvement in benchmark scores, hallucination reduction, etc, but not much qualitative change in the types of task they are capable of.
I do think that AGI is inevitable, maybe not even that far off (but certainly not next 5 years, probably not next 10 years *), but there's a lot missing from LLMs to get there, and it seems that at least one critical piece, online learning, may require a different approach.
* Note that it's already been 7 years since the transformer paper came out, and all we've really seen since then is a bunch of engineering work in making them more efficient and how best to train them. We haven't yet seen any advances in "cognitive architecture", or even any widespread recognition that there is a need to do so. If all people are doing for the foreseeable future is building pre-trained LLMs, then that is all we will get.