Excellent article by @ramez exploring how close current AI systems are to triggering an intelligence explosion. Many pieces on recursive self-improvement assume the AI starts out at least as good as a human on all relevant aspects of AI R&D. Then they can draw extensively on the data about human-driven R&D. They combine this with a small amount of AI-specific data to reach conclusions about whether this would explode. In contrast, Ramez is starting with the data on current AI systems and how they scale to see how close they are to explosive RSI. He generates his conclusions via frameworks and data that are widely supported by those who think an intelligence explosion is likely, so I'd strongly encourage people who are bullish about this to engage with his work. By drawing out the key pieces of evidence against explosive growth, he is also highlighting important parameters for people to track to see if the situation changes. I agree with a lot of his analysis and his conclusion that it doesn't look like their current returns from self-improvement are enough to drive explosive growth in their capabilities. This doesn't mean it won't happen or that it is a responsible thing for people to pursue. It is a bit like saying in 1939 that current techniques for nuclear chain reactions don't seem to be scaling towards a point of criticality (r > 1). That is useful information, though it doesn't mean we should be sanguine about further research on achieving critical chain reactions. https://t.co/KbR4EE4QDe