Researcher Profile
Editor reviewedOpen-source LLMs, training
Co-founder at Conjecture
A useful anchor for the open-model ecosystem because his path runs from EleutherAI’s training efforts into a more explicit alignment and interpretability agenda at Conjecture.
Organizations
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About This Page
This profile is meant to help you get oriented quickly: why this researcher matters, what to read first, and where to explore next.
Last reviewed
March 18, 2026
Official And External Links
The ideas, systems, and research directions that make this person worth knowing.
01
EleutherAI and open-source LLM training
02
GPT-NeoX-era community model building
03
Interpretability and alignment work at Conjecture
04
Open-source LLMs, training
05
GPT-NeoX (GitHub)
06
EleutherAI
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Worth tracking for the open-model side of the field, especially where dataset construction, practical training work, and alignment-flavored thinking meet.
Useful to follow if you care about the practical evaluation layer of open models, especially where benchmark tooling and reproducible comparisons actually shape what the ecosystem measures.
An important open-model researcher for understanding how early public LLM efforts, scaling heuristics, and open data work fed into the broader modern model ecosystem.
Important for the bridge between early open-model scaling work and later frontier closed-model systems, especially around architecture and training-stack choices that ended up mattering at both ends of the field.