In healthcare settings where patients use LLMs as a medical assistant, LLM performance differs between evaluation and deployment. (a) Bean et al. (2025) find a 61 percentage point difference between evaluation and deployment. (b) We argue this gap arises not from poorly designed benchmarks, but from implicit assumptions embedded in evaluation protocols that fail to…
Turn every AI agent change into a measured experiment you compare before and after to detect regressions and measure performance. The scariest AI failures are the silent ones. You ship a change to your agent on a branch — a new feature, a prompt fix, a quick refactor. No errors. No complaints. Everything looks fine….
Agentic systems turn model reasoning into action through multi-step workflows that combine inference, tool use, code execution, retrieval, orchestration, and result handling. As these systems scale across the AI factory, performance depends not only on GPU acceleration, but also on the CPU work that happens between model steps. Across the creation and deployment of an…
Today, we’re excited to announce a deep-link integration between Hugging Face and Amazon SageMaker AI. Developers can now go from model discovery to hands-on experimentation in SageMaker Studio with a single selection. Whether you fine-tune a foundation model (FM) from Amazon SageMaker JumpStart or deploy it to an Amazon SageMaker Inference endpoint, you can now…
Featured projects Training state-of-the-art large language models (LLMs) with billions of parameters requires distributed training across hundreds or thousands of GPUs. At this scale, hardware failures are not exceptional events—they are expected. A single GPU memory error, network partition, or node crash can bring down an entire training run that has been progressing for days…
August 19, 2025 — Posted by the TensorFlow teamTensorFlow 2.20 has been released! For ongoing updates related to the multi-backend Keras, please note that all news and releases, starting with Keras 3.0, are now published directly on keras.io. You can find a complete list of all changes in the full release notes on GitHub.tf.lite is…
💡 Modular’s AI-Native Platform to Advance Qualcomm’s Evolution as a Developer-First, AI Solutions Company Delivering Generative and Agentic AI from Edge to Cloud ➡️ Creation of an Industry-Friendly Open Software Ecosystem to Scale AI Across Diverse Compute Environments Highlights: Combines an AI-native software platform, and the world-class team behind it, with Qualcomm Technologies silicon leadership…
Your Unity Catalog (UC) managed tables now get better on their own. Automatic (Auto) Upgrades is the first capability of its kind in any lakehouse. It automatically verifies your clients are compatible, then applies best-practice features like Row Tracking the moment your tables are ready, with no manual effort required. Open table formats are innovating…