Google released DiffusionGemma, a 26-billion-parameter model that generates text not token by token but through diffusion, similar to how image AI turns noise into a picture. According to Nvidia, it hits about 1,000 tokens per second on a single H100 GPU, roughly four times faster than comparable autoregressive models. The speed comes at a cost, though. Output quality is lower, so Google is positioning it as an experimental tool for developers for now.<br /> The article Google's new open model DiffusionGemma generates text from noise instead of word by word appeared first on The Decoder. [...]
GenAI image generators like Stable Diffusion do not draw a picture pixel by pixel from left to right. They start with noise and iteratively refine the entire image in parallel until it converges, in a [...]
Rarely does a set of open-fit earbuds actually impress me. I tend to find them underwhelming because overall sound quality is subpar compared to the more “traditional” in-ear models. Any promise o [...]
It's not just Google's Gemini 3, Nano Banana Pro, and Anthropic's Claude Opus 4.5 we have to be thankful for this year around the Thanksgiving holiday here in the U.S.No, today the Germ [...]
The two big stories of AI in 2026 so far have been the incredible rise in usage and praise for Anthropic's Claude Code and a similar huge boost in user adoption for Google's Gemini 3 AI mode [...]