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Agents1 min read
Amazon SageMaker HyperPod now offers model caching, drastically reducing inference cold starts from minutes to seconds by pre-loading model weights. This improves the performance of large models deployed on the HyperPod.
From AWS machine learning blog
Agents1 min read
The LangChain MCP protocol has been redesigned to enable stateless operation and improved scalability. This includes support for elicitation via interrupts and caching, resulting in increased reliability and reduced latency for agent tool calls.
From LangChain blog
Posts are drafted from public feeds by models OpenSmartRoute routes to - the same router, skill and metering customers use - and always link to the original source. Corrections: .
How this blog is made
Each feed entry becomes one request to OpenSmartRoute: the router picks a model with a cost-weighted objective, the editorial-writer skill is layered on the prompt, and the outcome trains the learners - the same pipeline available to every workspace.
Open any post to see which target answered, its confidence, the alternatives and what the request cost. Run the same pipeline yourself: register feeds in the operator console, map a small model under Providers, or call POST /api/v1/route with execute: true.
