Episode 142
Happy holidays! This is one of my favorite episodes of the year — for the third time,
and I did our yearly roundup of all the AI news and advancements you need to know. This includes selections from this year’s State of AI Report, some early takes on o3, a few minutes LARPing as China Guys………If you’ve stuck around and continue to listen, I’m really thankful you’re here. I love hearing from you.
You can find Nathan and
here on Substack and on Twitter, LinkedIn, and his personal site. Check out his writing at press.airstreet.com.Find me on Twitter (or LinkedIn if you want…) for updates on new episodes, and reach me at editor@thegradient.pub for feedback, ideas, guest suggestions.
Outline
(00:00) Intro
(01:00) o3 and model capabilities + “reasoning” capabilities
(05:30) Economics of frontier models
(09:24) Air Street’s year and industry shifts: product-market fit in AI, major developments in science/biology, "vibe shifts" in defense and robotics
(16:00) Investment strategies in generative AI, how to evaluate and invest in AI companies
(19:00) Future of BioML and scientific progress: on AlphaFold 3, evaluation challenges, and the need for cross-disciplinary collaboration
(32:00) The “AGI” question and technology diffusion: Nathan’s take on “AGI” and timelines, technology adoption, the gap between capabilities and real-world impact
(39:00) Differential economic impacts from AI, tech diffusion
(43:00) Market dynamics and competition
(50:00) DeepSeek and global AI innovation
(59:50) A robotics renaissance? robotics coming back into focus + advances in vision-language models and real-world applications
(1:05:00) Compute Infrastructure: NVIDIA’s dominance, GPU availability, the competitive landscape in AI compute
(1:12:00) Industry consolidation: partnerships, acquisitions, regulatory concerns in AI
(1:27:00) Global AI politics and regulation: international AI governance and varying approaches
(1:35:00) The regulatory landscape
(1:43:00) 2025 predictions
(1:48:00) Closing
Links and Resources
From
:There is no scaling wall: in discussion with Eiso Kant (Poolside)
Alchemy doesn’t scale: the economics of general intelligence
Other highlights/resources:
Deepseek: The Quiet Giant Leading China’s AI Race — an interview with DeepSeek CEO Liang Wenfeng via
, translated by , , and othersA great position paper on open-endedness by Minqi Jiang, Tim Rocktäschel, and Ed Grefenstette — Minqi also wrote a blog post on this for us!
for China Guys only: China’s AI Regulations and How They Get Made by Matt Sheehan (+ an interview I did with Matt in 2022!)
The Simple Macroeconomics of AI by Daron Acemoglu + a critique by
(more links in the Report)AI Nationalism by Ian Hogarth (from 2018)
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