Raw LLM Responses

My impression is that in order to make the next great leaps in capability, there needs to be more fundamental R&D in AI technologies. Unfortunately, the rate of scientific breakthroughs isn't exactly a function of funding. You can throw all the money you want at a top-tier AI research team, but as the saying goes, nine women can't make a baby in one month. That's why they talk about having AI itself design better AI systems (the AI 2027 predictions assume this), but it remains to be seen how far that can take us. Meanwhile, I'm skeptical when it comes to a lot of the benchmarks. Not to say that the results aren't impressive in their own right, but if these major AI companies' models were able to independently accomplish complex, economically valuable work, they wouldn't bother with high school math competitions. Personally, I think AI will have transformative impacts even if the tech stops developing quickly. There are so many opportunities to build AI-enabled systems that play to their strengths, we could keep ourselves busy for the next 10-15 years. We don't need to have AGI/ASI for that to happen.