More than 30 OpenAI and Google DeepMind employees signed onto a statement supporting Anthropic's lawsuit against the Defense Department after the agency labeled the AI firm a supply-chain risk, ...

StorageChain was incorporated in late 2022 and introduced its decentralized cloud storage product in 2023, followed by the launch of its AI-powered semantic search platform in early 2026.

AI turns power and cooling into one big puzzle, but using a digital twin makes it easy to solve, check and manage everything without the usual guesswork.

Zilliz Cloud BYOC eliminates this compromise by deploying a fully managed vector database directly inside a customer's own cloud account—enabling organizations to move faster on AI initiatives without ...

Researchers have coined a new way to trick artificial intelligence (AI) chatbots into generating malicious outputs. AI security startup NeuralTrust calls it "semantic chaining," and it requires just a ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine the role that semantic leakage ...

Where Microsoft promises enterprises better understanding of their data for workers and autonomous agents alike, analysts fear deployment hurdles and vendor lock-in. With Fabric IQ, Microsoft is ...

Microsoft announced two new Windows 11 recovery features today at the Ignite developer conference, called Cloud Rebuild and Point-in-Time Restore (PITR), that aim to reduce downtime and make it easier ...

You followed the SEO playbook. You carefully selected keywords, analyzed competing content, and published long‑form articles that filled gaps in coverage for dozens of topics. Yet your Google rankings ...

Semantic SEO helps search engines understand context. Learn how to use entities, topics, and intent to build richer content that ranks higher. Semantic SEO aims to describe the relationships between ...

Large-scale 3D point cloud datasets are essential for training deep neural networks but impose heavy computational burdens. We propose a distribution matching-based dataset distillation framework that ...