Ryan Greenblatt
speaker
243 appearances
3 recordings
1 series
first heard Jan 2026
last heard 12 Apr
Ryan Greenblatt’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 3 in all, peaking in Apr 2026 with 2.
Appearances
LessWrong (Curated & Popular) · "My picture of the present in AI" by ryan_greenblatt · 9 Apr 2026
podcast
A company revenue is decently high and growing fast, but not high enough that we'd expect this to clearly show up in GDP statistics.
I think the current annualized revenue attributable to general-purpose AI, for example, not including image generation, is perhaps around $100 billion though I haven't thought about this carefully.
The combined annualized revenue of OpenAI and Anthropic is around $55 billion.
I'm uncertain how to convert this revenue into a GDP effect, but I tentatively expect that the GDP effect is a few times bigger than the revenue, perhaps 3x, but maybe only around 65% of this GDP effect is in the US, implying the current fraction of US GDP that is due to AI, and not including investment, is around 0.5%.
If AI revenue doubles or triples by end of year and my multiplier analysis is roughly correct, AI will contribute perhaps roughly 1.0 percentage points of additional US GDP growth that year, perhaps increasing growth by roughly 1 for dash 1-2, again, putting aside investment.
It's plausible that the real effect on the US GDP will be this large, but this won't show up in the numbers because AI productivity increases will be concentrated in improving the quality of goods in sectors where GDP measurements don't do a good job accounting for quality improvements.
AACAPEX is supposed to be around $650 billion this year, though a reasonable fraction of this compute build won't be used for frontier general-purpose AI.
This is around 2% of US GDP.
I don't currently think there are large and widespread labor market effects from AI, though I do think that junior software engineering hiring is significantly reduced and companies are more likely to lay off software engineers.
This may be mostly due to AI-induced uncertainty because hiring is sticky and generally having fewer employees is a bit less risky, I'd guess.
This article was narrated by Type 3 Audio for Less Wrong.
The original text contained five footnotes which were omitted from the narration.
The Inaugural Redwood Research Podcast by Buck and Ryan Greenblatt.
Published on January 4, 2026.
There's a YouTube video here in the text.
Subheading.
Notes on editing the podcast with Claude Code.
Buck wrote this section.
After the recording, we faced a problem.
We had four hours of footage from our three cameras.
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