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lucas atkins

T2 · manager / operator

Lucas Atkins is CTO and head of research at RCAI, an AI research company focused on pre-training open-weight models for developers and enterprises. He previously worked on post-training of open-source models like Mistral and Qwen.

1 call·1 name·0% bull·last heard 2 months ago·SemiAnalysis
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$RCAIRCAI

RCAI CTO explains pivot to pre-training for developer sovereignty

RCAI moved into pre-training to control the full stack for developers, avoiding reliance on Chinese base models and Western labs whose revenue doesn't depend on open-weight model quality.

SemiAnalysis2026-07episode →

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  • Open Source AI1
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$RCAI
RCAI
HIGHlucas atkins·SemiAnalysis·2 months ago·Training a 400B Model on 2,048 Blackwell GPUs for $20M | Researcher Conversations at GTC
RCAI CTO explains pivot to pre-training for developer sovereignty
RCAI moved into pre-training to control the full stack for developers, avoiding reliance on Chinese base models and Western labs whose revenue doesn't depend on open-weight model quality.
"for us when we were largely doing just post training on top of other open models. So Alama Mistrol back in the day and then later on Quen was a very popular one cuz we were trying…"
1:52
8
Open Source AItailwind
Open weights critical for enterprise sovereignty and safety research
Enterprises need full control over model pipeline to avoid vendor lock-in and margin pressure; open weights enable transparent safety research beyond the few hundred researchers at frontier labs.
7
AI Economics & Business Modelstailwind
Open model labs should undercut frontier labs on cost/speed for 80% of tasks
Open-weight labs shouldn't chase frontier benchmarks like theorem proving; instead they should optimize for reliability, speed, and cost on economically viable tasks, requiring far less compute than frontier labs.
6
AI Talent & Labor Markettailwind
Small open labs attract talent by offering full-stack ownership and visibility
Researchers prefer small open-weight labs where they own the entire training pipeline and see their work published, unlike at large frontier labs where work is siloed and only visible via API symptoms.
6
AI Hardware & Chip Architecturemixed
B300 GPU adoption limited by immature kernel ecosystem despite availability
RCAI chose B300s for speed but faced lack of optimized kernels and at-scale benchmarks; relied on DeepSeek's Hopper-era sparse kernels as performance reference, highlighting software maturity gap for new hardware.