AI is being rapidly adopted in edge computing. As a result, it is increasingly important to deploy machine learning models on Arm edge devices. Arm-based processors are common in embedded systems ...

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 ...

AWS Lambda provides a simple, scalable, and cost-effective solution for deploying AI models that eliminates the need for expensive licensing and tools. In the rapidly evolving landscape of artificial ...

Large language models (LLMs) such as GPT-4o and other modern state-of-the-art generative models like Anthropic’s Claude, Google's PaLM and Meta's Llama have been dominating the AI field recently.

Smart devices respond to wake words like “Alexa,” “Hey, Siri,” or “OK, Google” using a machine-learning technique called keyword spotting.

Speed embedded development with generative AI. Just as search engines transformed how we access information, AI is now transforming how we build embedded applications. With integrated generative AI in ...

Why it’s important not to over-engineer. Equipped with suitable hardware, IDEs, development tools and kits, frameworks, datasets, and open-source models, engineers can develop ML/AI-enabled, ...