Section 1, section 10, and section 11 cover the scenario of R&D automation via AI/ML systems that drive more productive R&D automation, resulting in a positive feedback loop, without requiring the typical “self-improving agent”—it’s the R&D system (people + AI/ML products) as a whole that is self-improving, not the individual AI/ML systems.
I highly recommend reading the entire report though. It was released in 2019 and I think it was brushed aside a little bit too easily. The past 3 years have (in my mind) provided sufficient evidence of things that CAIS directly predicted would happen, e.g. all of the AI/ML systems we’ve developed recently that have reached super-human competency on tasks despite a lack of generalized learning or capabilities or “self-improvement” or other recognizably “general intelligence” / “agent”-like behavior.
In 2019, we did not have Copilot, or DALL-E, or DALL-E-2, or AlphaFold, or DeepMind Ithaca, or GPT-3 -- etc.
I talk about this a little bit in my comment here.
This was one of the central points in the CAIS technical report.
Thanks for the pointer. Any specific section / sub-section I should look into?
Section 1, section 10, and section 11 cover the scenario of R&D automation via AI/ML systems that drive more productive R&D automation, resulting in a positive feedback loop, without requiring the typical “self-improving agent”—it’s the R&D system (people + AI/ML products) as a whole that is self-improving, not the individual AI/ML systems.
I highly recommend reading the entire report though. It was released in 2019 and I think it was brushed aside a little bit too easily. The past 3 years have (in my mind) provided sufficient evidence of things that CAIS directly predicted would happen, e.g. all of the AI/ML systems we’ve developed recently that have reached super-human competency on tasks despite a lack of generalized learning or capabilities or “self-improvement” or other recognizably “general intelligence” / “agent”-like behavior.
In 2019, we did not have Copilot, or DALL-E, or DALL-E-2, or AlphaFold, or DeepMind Ithaca, or GPT-3 -- etc.
I talk about this a little bit in my comment here.