Discover the all-new Cursor 2.0 with its frontier agentic coding model, Composer, and the powerful Multi-Agent Interface. In this video, we explore the latest features that make coding faster, smarter, and more collaborative than ever!
Aardvark, OpenAI's new agentic security researcher powered by GPT-5 and released Thursday, can assist security teams by identifying and helping patch vulnerabilities. The agent is meant to tackle existing challenges in the software security space, as tens of thousands of new vulnerabilities are discovered across enterprise and open-source codebases every year.
In an industry where model size is often seen as a proxy for intelligence, IBM is charting a different course — one that values efficiency over enormity, and accessibility over abstraction.
The 114-year-old tech giant's four new Granite 4.0 Nano models, released today, range from just 350 million to 1.5 billion parameters, a fraction of the size of their server-bound cousins from the likes of OpenAI, Anthropic, and Google.
Google recently rolled out a Google AI Studio update - and in this hands-on guide you will learn how to build a real app with zero code, generate marketing-ready video, and analyze financial data using Gemini inside Studio. Best part? It’s free to start (you only pay if you need bigger token limits or advanced scale features).
The well-funded French AI startup Mistral launched its own Mistral AI Studio, a new production platform designed to help enterprises build, observe, and operationalize AI applications at scale atop Mistral's growing family of proprietary and open source large language models (LLMs) and multimodal models.
In this video, I take you through what Skills actually are, how they fit into the crowded AI landscape, and why they could already make a real difference for anyone doing repeatable, structured work — the kind of tasks we all end up doing again and again.
The company's DeepSeek-OCR model, released Monday with full open-source code and weights, achieves what researchers describe as a paradigm inversion: compressing text through visual representation up to 10 times more efficiently than traditional text tokens. The finding challenges a core assumption in AI development and could pave the way for language models with dramatically expanded context windows, potentially reaching tens of millions of tokens.