But their ability to distill complex multi-dimensional systems into something more compact and easier to work with also makes them a promising avenue for compressing large AI models. Multiverse has ...

When bringing the latest AI models to edge devices, it’s tempting to focus only on how efficiently they can perform basic calculations—specifically, “multiply-accumulate” operations, or MACs.

Llama 3.2 brings powerful generative AI capabilities to mobile devices and edge systems by introducing highly optimized, lightweight models ...

Edge computing and AI are revolutionizing utility operations by enabling real-time, autonomous decision-making at the grid ...

These ready-to-use tools are making AI faster, cheaper and more scalable. The rise of AI model zoos—curated collections of pre-built, optimized models—is the key to this transformation.

Across the tech ecosystem, organizations are coalescing around a shared vision: The smarter future of AI lies at the edge.

By distilling DeepSeek-R1 into smaller versions, developers can leverage state-of-the-art AI performance on edge devices without requiring expensive hardware or cloud connectivity. Why this matters ...

This approach allows for flexible architectures where edge devices handle routine tasks, while more complex queries are routed to more powerful models in the cloud.

Accenture has invested, through Accenture Ventures, in CLIKA, a high-performance AI compression platform company.

Mitsubishi Electric Corporation (TOKYO: 6503) announced today that it has developed a language model tailored for manufacturing processes operating on edge d ...