The ability to run large language models (LLMs), such as Deepseek, directly on mobile devices is reshaping the AI landscape. By allowing local inference, you can minimize reliance on cloud ...

Tiiny AI has demonstrated a 120-billion-parameter large language model running fully offline on a 14-year-old consumer PC.

The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...

What if your local desktop could rival the power of a supercomputer? As AI continues its meteoric rise, the ability to run complex models locally—on setups ranging from modest 2GB systems to ...

Despite its status as the largest company in the world with a market cap of around $4.5 trillion, analysts think Nvidia could ...

Since 2018, the consortium MLCommons has been running a sort of Olympics for AI training. The competition, called MLPerf, consists of a set of tasks for training specific AI models, on predefined ...

As large language models (LLMs) continue their rapid evolution and domination of the generative AI landscape, a quieter evolution is unfolding at the edge of two emerging domains: quantum computing ...

The AI landscape is taking a dramatic turn, as small language and multimodal models are approaching the capabilities of larger, cloud-based systems. This acceleration reflects a broader shift toward ...