Generative AI needs a way to receive feedback. AI learned to play chess by playing a lot, and the feedback was either winning, losing, or drawing.
If generative AI can repeatedly test physics theories faster than humans, then we may witness progress in physics. AI could generate thousands of theories and conduct experiments successfully, possibly leading to new physics models.
However, I am uncertain whether this will be achievable soon, particularly for theories requiring costly experiments.
A benefit could be that humans crave recognition for success, making papers less valuable. AI may be more willing to take risks and document its failures than humans.
Generative AI needs a way to receive feedback. AI learned to play chess by playing a lot, and the feedback was either winning, losing, or drawing.
If generative AI can repeatedly test physics theories faster than humans, then we may witness progress in physics. AI could generate thousands of theories and conduct experiments successfully, possibly leading to new physics models.
However, I am uncertain whether this will be achievable soon, particularly for theories requiring costly experiments.
A benefit could be that humans crave recognition for success, making papers less valuable. AI may be more willing to take risks and document its failures than humans.