While previous embedding models were largely restricted to text, this new model natively integrates text, images, video, audio, and documents into a single numerical space — reducing latency by as muc ...

Abstract: Aero-engine fault diagnosis faces challenges such as low accuracy and weak physical interpretability. Additionally, early anomalies are difficult to identify due to complex thermodynamic ...

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

Red Hat, the world’s leading provider of open source solutions, today announced Red Hat AI Enterprise, an integrated AI platform for deploying and managing AI models, agents and ...

As India pivots from software services to AI token "factories" with tax breaks for global firms, questions arise over jobs, ...

He is talking about security and privacy. But he might just as easily be describing the quiet conviction — held now by a ...

Adding big blocks of SRAM to collections of AI tensor engines, or better still, a waferscale collection of such engines, turbocharges AI inference, as has been shown time and again by AI upstarts ...

Much of the conversation around AI today is focused on building cloud capacity and massive data centers to run models. Companies like Apple and Qualcomm are in the early stages of making on-device AI ...

Cloudflare has released the Agents SDK v0.5.0 to address the limitations of stateless serverless functions in AI development. In standard serverless architectures, every LLM call requires rebuilding ...

In the world of Large Language Models (LLMs), speed is the only feature that matters once accuracy is solved. For a human, waiting 1 second for a search result is fine. For an AI agent performing 10 ...