Crossposted from my Substack. @titotal recently posted an in-depth critique of AI 2027. I'm a fan of his work, and this post was, as expected, phenomenal*. Much of the critique targets the unjustified weirdness of the superexponential time horizon growth curve that underpins the AI 2027 forecast. During my own...
Cross-posted from my Substack. Introduction AI 2027’s recent publication made waves—if you’re reading this, you probably saw the whole saga unfold: cheers, jeers, NYT writeup, the works. To briefly recap: the authors predict that by March 2027, a superhuman coder is created, speeding up AI R&D fivefold. By the end...
Crossposted from my Substack.
@titotal recently posted an in-depth critique of AI 2027. I'm a fan of his work, and this post was, as expected, phenomenal*.
Much of the critique targets the unjustified weirdness of the superexponential time horizon growth curve that underpins the AI 2027 forecast. During my own quick excursion into the Timelines simulation code, I set the probability of superexponential growth to ~0 because, yeah, it seemed pretty sus. But I didn’t catch (or write about) the full extent of its weirdness, nor did I identify a bunch of other issues titotal outlines in detail. For example:
Cross-posted from my Substack.
AI 2027’s recent publication made waves—if you’re reading this, you probably saw the whole saga unfold: cheers, jeers, NYT writeup, the works. To briefly recap: the authors predict that by March 2027, a superhuman coder is created, speeding up AI R&D fivefold. By the end of the year, full-blown artificial superintelligence arrives. It sparks unprecedented scientific and economic progress—alongside mass unemployment, an arms race with China, and, worst case, human extinction via bioweapon.
There’s much to say about the assumptions built into their timelines, but here, I want to hone in on one key piece: the long-form data bottleneck.
I argue that the AI 2027 authors overlook the availability (or lack... (read 3673 more words →)
