Debating RSI, the US-China Gap, and Jaggedness with JS Denain of Epoch AI
- ID
- 27264
- Status
- summarized
- Published
- 22 Sep 2026, 9:37 PM
- Fetched
- 22 Sep 2026, 10:33 PM
- Provider
- Interconnects
- Category
- research-analysis
- Original URL
- https://www.interconnects.ai/p/debating-rsi-the-us-china-gap-and
- Source URL
- https://www.interconnects.ai/feed
Summary
- Score
- 6.5
- Created
- 22 Sep 2026, 10:35 PM
- Tags
- Audience
- ai_ml_learnersai_agent_userssaas_founders
What happened
Nathan Lambert interviews JS Denain of Epoch AI's Insights Team about recursive self-improvement (RSI), the US-China AI model gap, whether distillation explains that gap, what Chinese lab job postings reveal, and what a frontier post-training recipe looks like. Both express significant uncertainty about AI's trajectory, with Denain leaning toward faster progress scenarios. Key concrete observation: OpenAI's published data shows increasing Codex spending on AI-assisted model deployment, though it's unclear if this signals imminent self-sustaining acceleration or is a measurement artifact.
Why it matters
For builders shipping AI products, the US-China gap discussion and distillation question directly affect model selection and dependency planning — if Chinese labs are catching up via distillation rather than independent capability, open-weight alternatives may plateau or face export-control disruption. The RSI debate sets realistic expectations for when AI coding agents might meaningfully automate ML engineering work, which informs hiring and tooling investment decisions over the next 12-24 months.
Discussion angle
Whether the evidence for imminent RSI is actually strong — the Codex spending increase could be a measurement artifact rather than proof of self-sustaining AI acceleration, and what that means for how aggressively builders should plan around AI coding agents replacing engineering work.