Anthropic's 2021 research roadmap surfaces: RL and tool use bets were years early
SonglinYang4 · x · 2026-10-14
- Due to copyright litigation, Anthropic's internal 2021 research roadmap has been made public, and Elie Bakouch notes the company was remarkably early on RL and tool use.
- The roadmap already outlined goals that later became industry mainstream: training generally helpful LLMs with human feedback, alignment scaling laws, and using RL to explore how large models learn to use tools as a path toward AGI.
- The pre-training section mentions "periodic batched backprop" and "skeletokenization", which the community links to papers like FearNet (ICLR 2018), a brain-inspired incremental learning model.
- The leaked document includes internal comments from Dario Amodei, Sam McCandlish, and Chris Olah discussing very large contexts, data quality, and safe deployment of code-executing tools.
Related event: Copyright Lawsuit Exposes Anthropic's 2021 Research Roadmap(4 posts)→
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