alt Hacker NewsSkimmed, some notes for a more 'bear' case:
* value seems highly concentrated in a sliver of tasks - the top ten accounting for 32%, suggesting a fat long-tail where it may be less useful/relevant.
* productivity drops to a more modest 1-1.2% productivity gain once you account for humans correcting AI failure. 1% is still plenty good, especially given the historical malaise here of only like 2% growth but it's not like industrial revolution good.
* reliability wall - 70% success rate is still problematic and we're getting down to 50% with just 2+ hours of task duration or about "15 years" of schooling in terms of complexity for API. For web-based multi-turn it's a bit better but I'd imagine that would at least partly due to task-selection bias.
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I've found that architecting around that reliability wall is where the margins fall apart. You end up chaining verification steps and retries to get a usable result, which multiplies inference costs until the business case just doesn't work for a bootstrapped product.
,,1% is still plenty good, especially given the historical malaise here of only like 2% growth but it's not like industrial revolution good.''
You can't compare the speed of AI improvements to the speed of technical improvements during the industrial revolution. ChatGPT is 3 years old.