Google DeepMind’s most advanced forecasting model
Weather predictions need to capture the full range of possibilities — including worst case scenarios, which are the most important to plan for. WeatherNext 2 can predict hundreds of possible…
Weather predictions need to capture the full range of possibilities — including worst case scenarios, which are the most important to plan for. WeatherNext 2 can predict hundreds of possible…
For most large enterprises, AI transformation is a story of silos — business units running competing experiments, data sitting in disconnected systems, and outcomes staying out of reach. Cushman &…
Mira Murati’s Thinking Machines Lab Inc. today launched its first foundation model with the release of Inkling, making its full open weights available to developers so they can fine-tune it…
Retrieval is critical in multi-step agentic workflows where poor retrieval can cause agents to fetch irrelevant context, re-query, waste token budget, and carry noise into later reasoning steps. Today, we…
Capcom’s RE ENGINE team set out to bring path tracing into two shipping titles at once, Resident Evil Requiem and PRAGMATA, each with a different visual identity. Over two years,…
Dive Brief: DePuy Synthes, Johnson & Johnson’s orthopedics subsidiary, has acquired Expanding Innovations, a company that makes expandable spine implant technology. The companies did not disclose the terms of the…
July 16, 2026 — The mission of Thinking Machines Lab is to build AI that extends human will and judgment. The company has developed a platform that lets anyone customize models,…
Roboflow’s Workflows integration with Auto Label isn’t just for bounding boxes. In this article, we build a multi-model consensus pipeline that produces pixel-perfect segmentation masks using SAM 3 prompted directly…
Kimi is launching K3, a multimodal model with 2.8 trillion parameters and a context window of one million tokens. In the company’s own benchmarks, it performs on par with leading…
Knowledge bases that ground agents and generative AI applications over your enterprise data are hard to build at scale. Teams typically stitch together connectors, parsers, vector stores, knowledge graphs, and…