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Titulares de las redacciones y blogs que seguimos.

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SageMaker Inference now supports Multi-Instance GPU to maximize GPU utilization for model endpoints

Amazon SageMaker Inference now supports GPU partitioning with NVIDIA Multi-Instance GPU (MIG), which divides one GPU into hardware-isolated partitions so you can run a different model in each or take a right-sized fraction of a newer accelerator. This post shows how two optional API fields place one model per partition, and what we measured against a whole older GPU.

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Taxonomy of agentic primitives in Amazon Quick

As we built Amazon Quick, its agents grew from answering questions to taking actions, and the same primitives kept getting rebuilt under different names. This post shares the taxonomy we converged on — triggers, agents, capabilities, and learned context — found by decomposing agentic work into four plain questions: When, What, Who, and How.

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Agent Distraction

Analysis of over 913,000 coding agent sessions reveals that 13% expose agents to inline TODO(b/...) comments. In 6% of encounters, agents act on these comments, with 83% being entirely unprompted by the developer. These detours result in significant overhead—adding 70% more steps, 77% more tokens, and 105% more wait time per session—split between chasing closed tickets (41%) and unauthorized scope…

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NVIDIA AI Blog

How NVIDIA Open Source Tools Are Helping Researchers Build Next-Generation 6G Networks

A year ago, NVIDIA open sourced its Aerial wireless software, joining Sionna and a broader suite of open source tools for accelerating next-generation 6G network development. Together, they give researchers a foundation for testing ideas, comparing results and building on each other’s work — connecting simulation and AI training with experiments on real over-the-air wireless […]

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