Retrieval-augmented generation enhances the performance of AI agents by expanding their recall. It can do this in three ...

A mathematical problem that had remained unsolved for more than 10 years in the physics of complex systems has finally been ...

Taika Waititi’s Sony Pictures adaptation of Ishiguro’s novel hits theaters October 23, 2026, and every technology the book imagined is real. Vision Transformers process images as Klara does — in ...

What happens when we die? It's one of the single greatest questions in the history of humankind, silently driving science and ...

Industry discussions about what’s holding back AI often focus on security, graphics processing unit availability and other ...

With a 23% holdings overlap as of April 2026, WTAI and WQTM offer complementary exposure to the shared pursuit of greater ...

LFM2.5-230M proves that while 3-billion-parameter models like VibeThinker are solving advanced calculus, a ...

OpenAI’s first custom AI chip Jalapeño was unveiled today in partnership with Broadcom, claiming roughly 50% lower inference ...

Deploying DFlash block diffusion on NVIDIA hardware accelerates autoregressive LLMs during latency-sensitive inference.

Google's open-source diffusion language model generates 256 tokens in parallel and self-corrects, hitting 4x speed on one GPU at a cost to quality.

Google has released DiffusionGemma, an experimental language model that generates text using a diffusion-based method, producing blocks of 256 tokens at once rather than generating text word by word.

Another day, another AI model from Google. This time, Google DeepMind has released a new member of the Gemma 4 open model family, but it’s fundamentally different from the rest of the lineup.