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Will AI R&D Automation Cause a Software Intelligence Explosion?

forethought.org · 14,225 words · saved by 9 readers

AI companies are increasingly using AI systems to accelerate AI research and development. Today’s AI systems help researchers write code, analyze research papers, and generate training data. Future systems could be significantly more capable – potentially automating the entire AI development cycle from formulating research questions and designing experiments to implementing, testing, and refining new AI systems. We argue that such systems could trigger a runaway feedback loop in which they quickly develop more advanced AI, which itself speeds up the development of even more advanced AI, resulting in extremely fast AI progress, even without the need for additional computer chips. Empirical evidence on the rate at which AI research efforts improve AI algorithms suggests that this positive feedback loop could overcome diminishing returns to continued AI research efforts. We evaluate two additional bottlenecks to rapid progress: training AI systems from scratch takes months, and improving AI algorithms often requires computationally expensive experiments. However, we find that there are possible workarounds that could enable a runaway feedback loop nonetheless.

Will AI R&D Automation Cause a Software Intelligence Explosion? Daniel Eth Tom Davidson Authors Citations Cite Citations PDF Contact 26th March 2025 Will AI R&D Automation Cause a Software Intelligence Explosion? Summary Key Points Introduction Where AI progress comes from Improvements in AI software are already driving fast AI progress AI progress will likely speed up as we approach ASARA What happens when we reach ASARA? A toy model to demonstrate the dynamics of a software intelligence explosion Being more mathematically concrete: returns to software R&D In the real world, are returns to so

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