How do we optimize inference costs and performance?
Efficient inference makes AI practical at scale.
How It Works:
Apply techniques like model pruning, quantization, and serverless GPU bursts; use load balancers and caching layers to manage traffic.
Key Benefits:
- Lower bills: Slash compute spend up to 10?.
- Reduced latency: Speed up response times for users.
- Maintain accuracy: Minimal impact when done properly.
Real-World Use Cases:
- Voice assistants: Fast response under heavy load.
- Recommendation engines: Real-time personalization at scale.
FAQs
What's model quantization?
Can pruning harm accuracy?
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