Several small-cap companies announced developments that could reshape their long-term business models, while others ...

Canada’s largest AI facility will burn natural gas to power its 1 GW campus while claiming 100% clean energy through ...

Raj Ummadisetty and Ken Kurzweil share Netflix's architectural pivot to CloudStream, a repeatable capture, conversion, and ...

Learn how to secure Model Context Protocol (MCP) against emerging threats. Discover architectural strategies for future-proof, agentic AI security.

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Every day, analysts at major financial institutions spend hours on a deceptively simple task: figuring out whether “Deutsche Bank AG”, “DB” and “Deutsche Bank Aktiengesellschaft” all refer to the same ...

Spend enough time in the self-hosting and smart home hobby, and even the most ardent smart home enthusiast eventually reaches a moment where the excitement of adding new gadgets gives way to the ...

To answer this, first of all, let’s establish, in information retrieval, that an entity is a uniquely identifiable “thing” that exists independently of the words used to describe it. Entity ...

shows the logo of Microsoft displayed on the facade of the company France headquarters in Issy-les-Moulineaux, on the outskirts of Paris, on April 24, 2026. Martin LELIEVRE/Getty Images Microsoft ...

Teaching a large language model something new after it’s been trained is, to put it charitably, a pain. You either retrain the whole thing (expensive), stuff documents into its context window (limited ...

Enterprise teams increasingly rely on AI systems for analytics, but enterprise data workflows are often fragmented across storage systems and tools. Before analysis can begin, teams often need to ...

Large language models become static after pretraining. Their knowledge does not update as the world changes. Retraining a full LLM is too expensive at modern scales. Fine-tuning risks degrading ...