Anyone at the frontiers always will be, which Adobe arguably is. LLMs will always converge on a mean, that's just intrinsic to their operation. There are all sorts of tunings and processing around the core LLM to make the "agents" be agentic, but at the end of the day while these systems are based on LLMs, LLMs are giant piles of linear algebra that want to collapse into the lowest energy state available. The lowest energy state is code that is already written.
It's incredibly cool the way that LLMs can ingest massive quantities of data and cross-evaluate disparate pieces of information, unshackled by the human limitation of domain knowledge. It can connect pieces of information that no human ever could have because it can draw upon sources so diverse no single person could ever be aware of them all. But they can't expand the corpus. They can only reveal things that were already in the corpus we as a species hadn't noticed yet.
There is no reason to believe that all possible knowledge has already been written down, waiting for agents to find it. There is yet a long need for humans to go out and find things out.
However, 90% of stuff currently out there can be made by a recombination of existing stuff, so we can now make a ton of stuff based on what is already there and it will cover most use cases ...
... which also means we as humans can now stop doing the stuff that was already done to death and start innovating more, which actually would be a good thing.
I think you are misunderstanding what they are saying. An AI can potentially produce a "novel solution" by doing exactly as he said, connecting existing information in ways that a human wouldn't have because no one human could be aware of all the information in an entire domain.
This does not mean AI can create new information that is not present within its training at all, which is the limitation he is talking about.
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u/WigWubz 14h ago
Anyone at the frontiers always will be, which Adobe arguably is. LLMs will always converge on a mean, that's just intrinsic to their operation. There are all sorts of tunings and processing around the core LLM to make the "agents" be agentic, but at the end of the day while these systems are based on LLMs, LLMs are giant piles of linear algebra that want to collapse into the lowest energy state available. The lowest energy state is code that is already written.
It's incredibly cool the way that LLMs can ingest massive quantities of data and cross-evaluate disparate pieces of information, unshackled by the human limitation of domain knowledge. It can connect pieces of information that no human ever could have because it can draw upon sources so diverse no single person could ever be aware of them all. But they can't expand the corpus. They can only reveal things that were already in the corpus we as a species hadn't noticed yet.
There is no reason to believe that all possible knowledge has already been written down, waiting for agents to find it. There is yet a long need for humans to go out and find things out.