170 commits spread across 10 repos, mostly autoresearch variants. No releases, no merged PRs, no fires to report.
Five open issues outline the next frontier: licensing questions, pluggable optimization tracks, and a pivot toward data-centric research.
@karpathy has filed five substantial issues against autoresearch this week, none yet merged. The most ambitious: Auto-Research Tracks, which proposes pluggable idle optimization across harness, skills, memory, and model selection. A separate pitch for data-centric autoresearch suggests the project may be at an inflection point. Pending work also includes a JudgeModel layer for snapshot-diff scoring and a call to expand the harness generator into the pattern/memory/security design space. Licensing remains an open question.
The CPU-bound variant of autoresearch picked up 17 commits this week but remains undocumented in the public record.
@karpathy's CPU adaptation saw steady churn. No releases, no PRs, no issues filed. The work is opaque from the outside.
The social simulation fork of autoresearch registered 17 commits but no user-facing activity.
@karpathy committed to the prompt-only social simulation built from autoresearch, but nothing shipped or broke this week.
GPU-specific kernel work accumulated 17 commits with no visible release or PR activity.
@karpathy is preparing infrastructure for the RTX 5090. The commits landed but stayed under wraps. Likely not production-ready yet.
Continual learning setup for RTX 5070 saw 17 commits this week with no releases or issues filed.
@karpathy's RTX 5070 training pipeline accumulated work in silence. No public signals yet on what the commits contain or when they ship.
| autoresearch |
|
48,246 |
| TrainRTX5070 |
|
1 |
Your GitHub week, turned into something worth reading.
Generate your dispatch →