NEWS IN BRIEF: AI/ML FRESH UPDATES

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Streamline Onboarding with AI-Powered Agents

Amazon Quick is a managed service that helps HR departments create onboarding agents to streamline new-hire processes and improve productivity. Components like knowledge bases, actions, and spaces enable organizations to automate tasks and provide consistent answers, saving time and enhancing the onboarding experience.

Customizing AI in Amazon SageMaker: Accelerate Agentic Tool Calling

AI agents utilize agentic tool calling for production tasks, but often fail due to hallucinations and bad parameters. Amazon SageMaker AI offers Serverless model customization with RLVR to improve tool calling accuracy by 57%, handling infrastructure and complexity. SageMaker AI supports model families like Amazon Nova and techniques such as RLVR, enabling models to generate candidate responses...

AI Institute in UK Faces Major Overhaul

The Alan Turing Institute urged to enhance strategy and value for money by main funder after legal duties reminder by watchdog. Significant changes required following whistleblower complaint, as reported by The Guardian.

Fueling the Future: The Nuclear Renaissance

Dean Price, an MIT nuclear engineer, aims to advance nuclear technology for carbon-free energy generation in the US by designing new reactors. His research focuses on multiphysics modeling to understand how neutrons and thermal processes interact in nuclear reactors.

AI Love Gone Wrong

AI skeptic Rhik Samadder lets AI take the lead on a date in week five of his diary. Is AI the missing ingredient in his search for love?

Opting Out: The Case Against Auto-Stopping in SGD Training

Summary: Auto-stopping in stochastic gradient descent training can be challenging due to setting stopping tolerance and consecutive-no-improve constants, impacting model accuracy and overfitting risk. Specifying the right stopping tolerance in SGD depends on data scaling, affecting model prediction accuracy and potential overfitting.

Accelerating Gemma 4: NVIDIA's Local Agentic AI Journey

Google's Gemma 4 family introduces compact models optimized for NVIDIA GPUs, supporting a wide range of tasks. These models enable efficient local execution for on-device AI, from edge devices to high-performance GPUs, revolutionizing everyday devices.