Comment by nullbio

> Biology and chemistry are the sciences I know best, so I will use those examples -- every major breakthrough of the last 50 years has involved invention of some fundamental new mode of observation, such as crystallography, NMR, mass spec, electron microscopy, various kinds of light microscopy, DNA sequencing, PCR, etc. Someone invents some innovative technique, and a wave of progress happens. Expert practitioners in in the lab are probably the second rate-limiting step, but the part that LLMs can do -- taking data and turning it into hypotheses -- is the part that carries the least value. Any postdoc has enough ideas to keep a lab going forever.

Technology is not made in a vacuum though, it is a process of incremental advancements, often in parallel, over multiple industries. If LLMs are watching the worlds scientific and hardware progress on all fronts and compute is dedicated to exploring combinations of new ideas and ranking them on estimated practicality toward outstanding problems or current goals that humans have, I see no reason why they won't be able to come up with creative new technology. The issue with cutting edge technology is that it's expensive and time consuming to validate. If AI can develop sufficient simulations, it could be validated digitally.

Surely you don't believe that this isn't around the corner, given the scale we are now seeing? For example dedicating 80,000 agents over 88 hours to write a proof for Navier-Stokes.

Maybe this isn't a wildly creative exercise or you consider math "small" in comparison, but I think it's quite clear to see that this isn't a question of whether it's possible but rather a question of how long it will take to get there.

There's no shortage of talent being dedicated to this pursuit, either. For example: https://finance.yahoo.com/technology/ai/articles/deepmind-ch... - The company aims to accelerate scientific and engineering breakthroughs by building autonomous systems that handle entire research cycles.