Dyna Robotics' DYNA-2 world-action model scales on 1M hours of human video
On 2026-08-10 Dyna Robotics unveiled DYNA-2, a world-action model pretrained on over 1 million hours of egocentric human video; it reports a smooth human-to-robot scaling law (on-robot score 20% to 53% across 14 tasks from 1k to 1M hours) and an 87% zero-shot pass rate at a customer site vs 46% for DYNA-1.
Key facts
- Pretraining: 1M+ hours of egocentric human video (~170 years of waking experience)
- Architecture: video-diffusion world-action model jointly denoising future video and action chunks
- Customer deployment: 87% quality pass rate zero-shot vs 46% for DYNA-1; 1.55x more successes
- One-step distilled video generation, 90x faster than teacher; bottle-cap opening from 10 min of robot data
What happened
Dyna, whose DYNA-1 already runs in production in hotels, restaurants and laundromats, showed that robot performance improves predictably with more human video, with no plateau up to 1M hours. Dyna calls it the first scaling law across the embodiment gap.
Why it matters
Human video is far cheaper to collect than robot teleoperation. Together with Figure's Helix 2.5 and Generalist GEN-1, DYNA-2 suggests 2026 is the year robot learning found a scalable data source. Claims are company-reported.
Changelog
- 2026-09-29: created
Models
- DYNA-2 (World-Action Model) Dyna Robotics · current
Related events
- Figure Helix 2.5: humanoids do chores zero-shot in 30 never-seen homes ★★★★★
- Generalist GEN-1 claims 99% success on simple robot tasks, trained on 500k+ hours of human wearable data ★★★★
Sources (3)
- officialDyna: DYNA-2 — A 1-Million-Hour Scaling Law for World-Action Models
- officialPR Newswire: Dyna Robotics unveils DYNA-2
- pressMarkTechPost: Dyna Robotics introduces Dyna-2
id: 2026-08-10-dyna-robotics-dyna-2 · updated 2026-09-29 · open in the interactive timeline