A knowledge graph represents real-world entities and the relationships between them in a connected structure. Nodes may describe people, products, places, documents, or concepts, while edges state how those entities relate. Because relationships are explicit, systems can traverse the graph to answer questions, combine records from different sources, support recommendations, or add context to AI responses. Knowledge graphs often rely on schemas, identifiers, and rules that keep meaning consistent across data. They still require ongoing maintenance: duplicate entities, missing links, outdated facts, and uncertain sources can reduce reliability. When connected to generative AI, access controls and provenance help users distinguish verified graph data from generated interpretation.
A study by the University of Maryland and Microsoft found that Polish outperforms English and other major languages in long-context AI prompts, surprising researchers.
Neobank Revolut has acquired Berlin-based AI travel agent start-up Swifty, integrating its conversational booking technology into Revolut’s loyalty and lifestyle platform for over 65 million users.
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.