New RL harness work says math training can improve essay writing too
iamrobotbear · x · 2026-07-21
- The post argues that RLMs became exciting because they turned a hard non-coding problem—long-context reasoning—into a coding-like problem by using a harness to explore context.
- It then highlights new work by Alex Zhang and collaborators: training RL on verifiable tasks such as math can improve both the verifiable task and a structurally similar non-verifiable task like essay writing.
- The key claim is that a well-designed harness can induce generalization by composing task trajectories into shared structures, so the model does not need extra built-in generalization to transfer abilities.
- The quoted paper language suggests a theory where harnesses create equivalence classes over trajectories, letting the same underlying trajectory solve tasks that look different on the surface.
Related event: Research Suggests RLM Generalization is Driven by External Harness(10 posts)→
More from AGI Musings
- 'AGI is here' vs reality: AI labs still ship some of the jankiest desktop apps ever — MilesCranmer · 2026-09-11
- Misquoted: Anthropic Staff Warned of Double-Digit Extinction Risk by 2030, Not Dismissed It — davidmanheim · 2026-09-11
- Economist Ben Moll: You Can Model Anthropic's 15% AI GDP Growth, But It Won't Happen — sebkrier · 2026-09-11
- Cohere Labs launches interactive tool mapping which tasks of 178 occupations AI can automate — Cohere_Labs · 2026-09-11
- AI researcher on SkyNews flags concerns over inequality, power and criminal misuse — schwarzjn_ · 2026-09-11
- VC compares AI doom rhetoric to pandemic-era fear messaging — StewartalsopIII · 2026-09-11