Uber is using Amazon’s custom chips to speed up computing and train artificial intelligence models, the cloud giant said on Tuesday, as the ride-hailing firm seeks advanced hardware to handle growing digital workloads.
The deal expands the companies’ existing cloud partnership by enabling Uber to use Amazon Web Services’ (AWS) Graviton chips and Trainium processors to power its apps.
What Uber Is Using
| Chip | Purpose |
|---|---|
| AWS Graviton | Supports smoother rides and deliveries |
| Trainium | Trains AI models that power Uber’s apps |
Key Applications
Uber is working to optimize its digital interface, accelerate ride-matching, and personalize user experiences to attract users and gain a competitive edge.
The custom chips will help Uber:
- Speed up computing for digital workloads
- Train AI models more efficiently
- Improve ride and delivery coordination
- Enhance personalization for users
The Bigger Picture
| Company | Strategy |
|---|---|
| Uber | Seeking advanced hardware to handle growing digital workloads and gain competitive edge |
| Amazon | Investing heavily in custom chips to attract enterprise customers and capitalize on booming demand for AI model training and inference |
Amazon, meanwhile, is investing heavily in growing the appeal of its custom chips and attracting enterprise customers to capitalize on booming demand for AI model training and inference.
Expanded Partnership
The deal expands the companies’ existing cloud partnership, building on their long-standing relationship. By leveraging AWS’s custom silicon, Uber aims to improve operational efficiency and user experience across its global platform.
