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.

Small Language Models (SLMs) bring AI inference to the edge without overwhelming the resource-constrained devices. In this article, author Suruchi Shah dives into how SLMs can be used in edge ...

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.

A chip is changing how AI runs at the edge with high performance and low power while removing the need for cloud. Could this ...

Additionally, BrainChip is working on quantizing the model to 4 bits, so that it will efficiently run on edge device hardware.

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

These models offer superior performance and versatility, enabling a wide range of applications from natural language processing to image generation. Deploying GenAI on edge devices can unlock new ...

Geniatech's M.2 AI accelerator module, powered by Kinara's Ara-2 NPU, delivers 40 TOPS INT8 compute performance at low power ...

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.

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

Meta Platforms Inc. is striving to make its popular open-source large language models more accessible with the release of “quantized” versions of the Llama 3.2 1B and Llama 3B models, designed ...