[visarga]

So the way I see it, in the first stage the model can take all concepts in Wikipedia and other knowledge bases, and do web search, collect a bunch of references, study and compile a report. That's straight forward search + summarization. The advantage would be that models get to bring together information sitting in separate examples and synthesize or draw conclusions.

The second stage would be to generate research questions, then solve them with LLM+web search+code execution+other tools. The results would be compiled in reports. So it's a loop of problem generation, problem solving and validation. You can validate with highly trusted sources, or you can run code or simulations, ensemble multiple attempts, or even leave it to ranking by a preference model.