Autonomous · GCP
Waymo
Waymo’s production driver uses a modular six-layer stack (sensor processing, perception, world modeling, prediction, planning, control) integrated with HD maps, simulation, and a foundation-model-based end-to-end driving architecture that fuses camera, lidar, and radar into a unified world representation.[1][2][8][9][10] Training, evaluation, and large-scale data handling run on Google/Alphabet’s internal and Google Cloud infrastructure, with closed-source models and tooling.[1][4][5][8][10]
Foundation proximity: Native (own / self-hosted weights)
Foundational models & how they consume them
PrimaryWaymo Foundation Model for Autonomous Driving· Waymo (Alphabet, self-hosted on internal/Google Cloud infrastructure) · Native (own / self-hosted weights)
Cloud & datastore
GCPBigtableSpannerGoogle Cloud StorageProprietary in-vehicle data storesCompliance
ISO 27001 (inferred via Alphabet/Google Cloud hosting)[4]SOC 2 (inferred via Alphabet/Google Cloud ecosystem)[4]Automotive safety and validation frameworks for AVs, including systematic safety case construction[1][8]Similar companies
CruiseWayveOthers that build on proprietary / self-built models
Abnormal SecurityAbridgeAdobeAI21 LabsAleph AlphaAmbienceExplore
FAQ
Does Waymo use a foundational AI model?
Waymo uses Waymo Foundation Model for Autonomous Driving (Native (own / self-hosted weights)).
What cloud does Waymo run on?
Waymo runs on GCP.
What database does Waymo use?
Waymo uses Bigtable, Spanner, Google Cloud Storage, Proprietary in-vehicle data stores.
How close does Waymo run to the foundational model?
Waymo is Native (own / self-hosted weights) — close to the metal, so cheaper tokens and more control over outputs.
Sources
waymo.com ↗Also on the map
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