Rather than generating text word by word, Google's experimental open-source model drafts entire passages simultaneously using diffusion, resulting in up to 4x faster inference.

It began with video games, a paintball experiment and a bold bet that few understood. Today, Nvidia has become a company every tech giant depends on to build the future of artificial intelligence.

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.

DSpark can make decoding faster, but acceptance quality still determines how much speed the system actually realizes.

NVIDIA diffusion language model Nemotron TwoTower achieves 2.42x LLM inference throughput without a full retraining run, ...

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...

Lotte Biologics has teamed up with US biotech firm Asimov to unveil a next-generation contract development organization (CDO) ...

Core banking modernization succeeds through phased, API-driven transformation—not risky “rip-and-replace” projects—reducing ...

LLVM powers the core development tools, operating systems, and most applications at Apple Computer, where it long ago ...

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ('WiMi' or the 'Company'), a leading global Hologram Augmented Reality ('AR') Technology provider, has announced its research into the Synergic Quantum ...

Workers are outsourcing their thinking to AI. Researchers warn the cognitive atrophy is real and most employers aren't ...