Figure AI Helix 2.5 Enters 30 Homes Cold: Index Pretraining Yields Sixfold Leap
AI-summarised brief · reviewed before publication
On September 17, 2026, Figure AI announced that its Helix 2.5 neural network successfully completed 56% of 420 household tasks in 30 Bay Area homes it had never seen before, using a single pretrained checkpoint from the Index dataset. The same architecture trained from random weights achieved only 9%. The experiment involved three tasks—living‑room tidying, towel folding, and bed making—without any data collection or fine‑tuning on the new environments. The results demonstrate a sixfold improvement attributable solely to Index pretraining, not hardware or model size.
💡 Why It Matters
- · The finding shows that large‑scale human‑behavior data can unlock reliable zero‑shot performance in real homes, potentially accelerating the deployment of autonomous domestic robots.