How do we reduce latency in our AI stack?

How It Works:

Apply model optimizations (quantization, distillation), deploy closer to users (edge or regional zones), and use async pipelines and GPU caching.

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Key Benefits:

• Faster time-to-insight: Improves real-time analytics.
• Scalability: Handles peak loads without lag.
• Cost savings: Efficient resource use reduces spend.

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Real-World Use Cases:

• AR/VR apps: Low-latency tracking for seamless experiences.
• Live sports analytics: Instant highlight generation.