DEPLOYDatabase

Brain

GEN-1

Generalist AI's second-generation physical foundation model. Demonstrated 99% reliability on diverse tasks, execution up to 3x faster than prior state of the art, complex new physical skill learning, and emergent improvisational intelligence. Trained from scratch — goes beyond VLAs and world models. Supports broad range of end effectors.

Foundation model · Maturity: Pilot · Closed


Machine-readable surfaces

Architecture

Physical foundation model trained from scratch on real-world data at scale

Developed by (1)

Common questions

What is GEN-1?
Generalist AI's second-generation physical foundation model. Demonstrated 99% reliability on diverse tasks, execution up to 3x faster than prior state of the art, complex new physical skill learning, and emergent improvisational intelligence. Trained from scratch — goes beyond VLAs and world models. Supports broad range of end effectors.
Who developed GEN-1?
GEN-1 is credited to Generalist AI on the DEPLOY registry. Each developer attribution is verified via primary sources.
Is GEN-1 open source?
No. GEN-1 is recorded as proprietary on the DEPLOY registry. Model weights and source are not publicly available.
What type of AI is GEN-1?
GEN-1 is a foundation model, built on a Physical foundation model trained from scratch on real-world data at scale architecture on the DEPLOY registry.
What is GEN-1's maturity stage?
GEN-1 is at the pilot stage on the DEPLOY maturity ladder. Pilot stage means at least one named-customer trial deployment is verified.
Which robots run on GEN-1?
No robot models on the DEPLOY registry are recorded as running GEN-1. DEPLOY wires brain-to-model connections only when the wiring is verifiable from primary sources; absence may reflect pre-deployment or unverified manufacturer claims.
Methodology: Unreviewed · no sources on file · last reviewed 2026-08-09

Verification posture

Unreviewed

Low confidence

Review state

Stable

Last reviewed 2026-08-09

Maturity + lifecycle

Maturity stage: pilot

The framework is documented at /methodology. Corrections at /corrections. Reviewer: DEPLOY editorial team.

Methodology surface for GEN-1.

Canonical ID f08551f6-2cd5-436c-b483-87766bf3a316