AGI timelines are very bimodal. It's either by 2030 or bust. AI progress over the last decade has been driven by scaling training compute of frontier systems (3.55x a year, 160x over 4 years). This simply cannot continue beyond this decade, whether you look at chips, power, even fraction of raw GDP used on training. After 2030, AI progress has to mostly come from algorithmic progress. But even there the low hanging fruit will be plucked (at least under the deep learning paradigm). So the yearly probability of AGI craters. And we're plausibly looking at 2040+ timelines. I discuss this dynamic with @_sholtodouglas and @TrentonBricken: