Named entity recognition, or NER, finds mentions of specific entities in text and assigns them to categories such as people, organizations, locations, products, dates, or monetary values. It turns unstructured language into structured information that can support search, document analysis, customer service, compliance, and knowledge graphs. Systems may use rules, statistical models, neural networks, or language models. The task becomes difficult when names are ambiguous, new entities appear, categories overlap, or a domain uses specialized terminology. Reliable NER requires representative examples, clear label definitions, multilingual testing where relevant, and evaluation of both whether an entity was found and whether its boundaries and category were correct.
Andrew Tulloch, co-founder of the $12 billion AI startup Thinking Machines Lab, has joined Meta after previously rejecting what reports described as a $1.5 billion offer — a figure Meta has since called ‘inaccurate and ridiculous.’
Google has unveiled Gemini Enterprise, a next-generation AI platform designed for business productivity and collaboration, positioning itself directly against Microsoft’s Copilot and OpenAI’s enterprise solutions in the race for workplace AI dominance.
Google Cloud and Figma have launched an expanded partnership to embed Google’s generative AI models – including Gemini 2.5 Flash and Imagen 4 – directly into Figma’s design tools, reducing latency and accelerating creative workflows.
Opera today introduced Neon, an AI-powered browser that can run tasks and navigate pages autonomously — aiming to shift web browsing from passive to “agentic.”
AI search startup Perplexity has reportedly raised $200 million at a $20 billion valuation, just two months after a $100 million round – signaling its rapid rise as a major rival to Google.