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Hosting NVIDIA speech NIM models on Amazon SageMaker AI: Parakeet ASR

This post was written with NVIDIA and the authors would like to thank Adi Margolin, Eliuth Triana, and Maryam Motamedi for their collaboration. Organizations today face the challenge of processing large volumes of audio data–from customer calls and meeting recordings to podcasts and voice messages–to unlock valuable insights. Automatic Speech Recognition (ASR) is a critical …

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The Blueprint: How Giles AI transforms medical research with conversational AI

Welcome to The Blueprint, a new feature where we highlight how Google Cloud customers are tackling unique and common challenges across industries using the latest AI and cloud technologies. We hope to inspire others looking to innovate in their work.  The challenge:  Giles AI is a London-based startup that helps healthcare and life sciences organizations …

IBM’s open source Granite 4.0 Nano AI models are small enough to run locally directly in your browser

In an industry where model size is often seen as a proxy for intelligence, IBM is charting a different course — one that values efficiency over enormity, and accessibility over abstraction. The 114-year-old tech giant’s four new Granite 4.0 Nano models, released today, range from just 350 million to 1.5 billion parameters, a fraction of …

Breakthrough optical processor lets AI compute at the speed of light

Researchers at Tsinghua University developed the Optical Feature Extraction Engine (OFE2), an optical engine that processes data at 12.5 GHz using light rather than electricity. Its integrated diffraction and data preparation modules enable unprecedented speed and efficiency for AI tasks. Demonstrations in imaging and trading showed improved accuracy, lower latency, and reduced power demand. This …

AI use makes us overestimate our cognitive performance, study reveals

When it comes to estimating how good we are at something, research consistently shows that we tend to rate ourselves as slightly better than average. This tendency is stronger in people who perform low on cognitive tests. It’s known as the Dunning-Kruger Effect (DKE): The worse people are at something, the more they tend to …

Evaluating Evaluation Metrics — The Mirage of Hallucination Detection

Hallucinations pose a significant obstacle to the reliability and widespread adoption of language models, yet their accurate measurement remains a persistent challenge. While many task- and domain-specific metrics have been proposed to assess faithfulness and factuality concerns, the robustness and generalization of these metrics are still untested. In this paper, we conduct a large-scale empirical …

Announcing new capabilities in Vertex AI Training for large-scale training

Building and scaling generative AI models demands enormous resources, but this process can get tedious. Developers wrestle with managing job queues, provisioning clusters, and resolving dependencies just to ensure consistent results. This infrastructure overhead, along with the difficulty of discovering the optimal training recipe and navigating the endless maze of hyperparameter and model architecture choices, …

MiniMax-M2 is the new king of open source LLMs (especially for agentic tool calling)

Watch out, DeepSeek and Qwen! There’s a new king of open source large language models (LLMs), especially when it comes to something enterprises are increasingly valuing: agentic tool use — that is, the ability to go off and use other software capabilities like web search or bespoke applications — without much human guidance. That model …