Continuous Learning Experiment Achieves 100% Success from 16 Examples
ihorbeaver · x · 2026-08-02
This tweet shows a full run and a segment of a task, achieving 100% success from 16 examples. The author notes that for continuous learning, the base model needs to be data-efficient and stable, as irrelevant fluctuations can compound over time.
Related event: Embodied AI Achieves 100% Reliable Continuous Learning with 16 Samples(4 posts)→
More from Research
- One ancient fold, many jobs: how the immunoglobulin domain evolved into antibodies, MHC and titin — arjunrajlab · 2026-10-16
- Universal forgery attack breaks Chinese PQC signature Origami using only the public key — matthew_d_green · 2026-10-16
- How do you attribute agent gains: model training or infrastructure? — jrxna · 2026-10-16
- First-ever paper on multi-agent swarm safety lands NeurIPS spotlight — LauraRuis · 2026-10-16
- EDEN: anchored embedding noise boosts RLVR exploration beyond policy rollouts — Daijiao Liu · 2026-10-16
- Autonomous vehicle demo shows car reversing to break narrow-road deadlock, with a robotic arm to shift gears — sanjeevs_iitr · 2026-10-16