You should make manifold markets for all these statements and put them in the comments.
You should make manifold markets for all these statements and put them in the comments.
Thanks - I only read this linkpost and Haydn's comment quoting your summary, not the linked post as a whole, but this seems to me like probably useful work.
One nitpick:
It seems likely to me that the US is currently much more likely to create transformative AI before China, especially under short(ish) timelines (next 5-15 years) - 70%.
I feel like it'd be more useful/clearer to say "It seems x% likely that the US will create transformative AI before China, and y% likely if TAI is developed in short(ish) timelines (next 5-15 years)". Because:
Yeah, fair point. When I wrote this, I roughly followed this process:
I think it would’ve been more informative if I wrote the bullet points with an explicit aim to add probabilities to them, rather than writing them and thinking after “ah yeah, I should more clearly express my certainty with these”.
A second or third place China that lags the US and allies could still be important. Since AI progress has recently moved at a break-neck pace, being second place might only mean being a year or two behind — though I suspect this gap will increase as the technology matures - 65%.
This is three different claims. Which one are you 65% confident in?
I think I was just reading all of those claims together and trying to subjectively guess how likely I find them all to be. So to split them up, in order of each claim: 90%, 90%, 80%.
I recently published a blog post where I tried to assess China's importance as a global actor on the path transformative AI. This was a relatively shallow dive, but I hope it will still be able to spark an interesting conversation on this topic, and/or inspire others to research this topic further.
The post is quite long (0ver 6,000 words), so I'll copy and paste my bottom line takes, and (roughly) how confident I am in them after brief reflection:
This was a really interesting and useful read! Posting the summary from the end of the post, as I found it helpful:
Kaiming He was at MSR in China when he invented ResNets in 2015. Residual connections are part of transformers, and probably the 2nd most important architectural breakthrough in modern Deep Learning.