Many decisions cannot wait for a round trip to the cloud. Driver monitoring, industrial sensing and adaptive audio all need millisecond response.

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 ...

Here are our picks for the top 10 edge AI chips with a bright future across applications from vision processing to handling multimodal LLMs.

‘Hey Google’ find me a suitable keyword spotting (KWS) model for edge devices. While voice control is essential for modern interfaces like Alexa, Siri, and Hey Google, building KWS models on edge ...

SAN JOSE, Calif.--(BUSINESS WIRE)--Edge Impulse, the leading platform for building, deploying, and scaling edge machine learning models, today announces Microchip Technology’s SAMA7G54 microprocessor ...

Large language models are powerful, but generally they require vast computing resources, which means they typically have to run on stacks of high-end GPUs in data centers. Now, startup Multiverse ...

SAN JOSE, Calif.--(BUSINESS WIRE)--Edge Impulse, the leading platform for building, deploying, and scaling edge machine learning models, has unveiled a suite of new industry first edge AI tools ...

The MarketWatch News Department was not involved in the creation of this content. Collaboration to bring production-ready machine learning models to NXP-based devices in days-- unlocking edge AI for ...

Edge AI is a form of artificial intelligence that in part runs on local hardware rather than in a central data center or on cloud servers. It’s part of the broader paradigm of edge computing, in which ...

Artificial intelligence (AI) and machine learning (ML) have undergone significant transformations over the past decade. The revolution of convolutional neural networks (CNNs) and recurrent neural ...