#inference — AI News & Research · DeepTrendLab

Stochastic KV Routing: Enabling Adaptive Depth-Wise Cache Sharing

Serving transformer language models with high throughput requires caching Key-Values (KVs) to avoid redundant computation during autoregressive generation. The memory footprint of KV caching is significant and heavily impacts serving…

Capacity-aware inference: Automatic instance fallback for SageMaker AI endpoints

Today, Amazon SageMaker AI introduces capacity aware instance pool for new and existing inference endpoints. You define a prioritized list of instance types, and SageMaker AI automatically works through your…

Inference Scaling (Test-Time Compute): Why Reasoning Models Raise Your Compute Bill

Why reasoning models dramatically increase token usage, latency, and infrastructure costs in production systems The post Inference Scaling (Test-Time Compute): Why Reasoning Models Raise Your Compute Bill appeared first on…

Larry’s risky business

If you want to know whether the AI bubble is bursting, there's only one publicly traded company that will tell you: Oracle. That's right, the database company. Oracle has burned…

DeepInfra on Hugging Face Inference Providers 🔥

Rethinking AI TCO: Why Cost per Token Is the Only Metric That Matters

Traditional data centers only stored, retrieved and processed data. In the generative and agentic AI era, these facilities have evolved into AI token factories. With AI inference becoming their primary…

Torch compile caching for inference speed

Cache your compiled models for faster boot and inference times