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Case Study: Woven by Toyota drives 10x experiment velocity with Weights & Biases

Woven by Toyota Case StudySourced & dated by Case Study Desk
Key facts · TL;DR
Company
Woven by Toyota
Industry
Autonomous Vehicles
Challenge
Scaling ML for safe autonomous driving
Headline result
10x experiment velocity

Key results

10x
Experiment velocity
Via experiment tracking

The challenge

Woven by Toyota builds machine learning for safe autonomous driving and needed to increase the speed and scale of its experimentation to keep pace with development, applying kaizen (continuous improvement) principles.

The solution

Woven by Toyota used Weights & Biases experiment tracking to log, share, and trace results across the team, enabling faster collaboration with traceability.

Experiment tracking has given us 10x velocity and enabled us to share results with each other much faster, with tractability and traceability.

EC
Evan Cushing
Machine Learning Engineer, Woven by Toyota

The results, in context

Woven by Toyota reported that experiment tracking gave the team 10x velocity and enabled faster sharing of results with tractability and traceability.

Products used

Weights & Biases W&B Experiment Tracking