AI on the Edge

Sponsored by Texas Instruments: Embedded processors capable of running AI algorithms coupled with “low-code” software-development tools lead to edge AI applications that can boost...

Standalone AI on the edge is possible with Useful Sensors’ modules.

The new processor family from Texas Instruments can handle vision and AI processing for up to 12 cameras.

Embedded smart-camera platforms with easy-to-use edge learning provide a unique solution for apps that are too difficult for conventional rule-based machine vision but don’t justify...

Configurable high-bandwidth RISC-V cores with vector units can be made to directly address challenging applications like machine learning, AI, and other cutting-edge spaces.

Explainable AI (XAI) can improve safety, security, and the overall user experience in IoT applications.

Elma’s JetSys-5330 is built around NVIDIA’s Jetson AGX Orin.

Femtosense's SPU-001 coprocessor delivers low-power AI audio processing.

A novel edge AI video analytics platform built by Elma Electronic, Hailo, and Isarsoft challenges how business intelligence is addressed in the transportation industry.

The Cadence Tensilica AI Platform delivers scalable and energy-efficient on-device to edge AI processing.

Highlights of DFI's exhibition include high-performance industrial motherboards featuring AMD's 1.8-in. Ryzen, Intel's newest Raptor Lake-S and Alder Lake series processors, and...

Artificial intelligence and more specifically, machine learning, with human augmentation requires a thorough strategy to achieve a breakthrough.

The machine-learning support from Synaptics' Katana SoC can visually detect actions like falling.

Artificial intelligence is furthering its way into everyday lives, but the focus has predominantly been on the “big machines,” such as self-driving cars. Perhaps it’s now time...

NXP's Robert Oshana discusses issues regarding machine learning at the edge.

Today's advanced products, from consumer wearables to smart EVs, are starting to leverage the power of AI to increase performance and functionality. However, those solutions require...

Some results of our recent machine-learning survey were expected, but others raised eyebrows.

Edge AI tools continue to improve and become more powerful, leading the way to a new era of intelligent video analytics with rapidly expanding capabilities and possible uses.

Our panel addressing the use of artificial intelligence in the field includes experts from NVIDIA, Lattice Semiconductor, and NXP.

With all the buzz surrounding edge computing these days, perhaps you're thinking it’s time to invest in intelligent edge technologies for your IoT network. What are the key factors...

The Jetson family of modules can find homes in a wide variety of systems, bringing low-power machine learning to embedded applications.

AI at the edge is growing rapidly. Don’t let these misguided notions get in your way.

Renesas’ DRP is designed to handle chores ranging from machine learning to stream processing.

Inference arrives at the edge: The eIQ machine-learning framework and development tools facilitate the transfer of AI from the cloud to devices on the edge.

Sponsored by Digi-Key and NXP Semiconductors: Designs evolve over time, but instead of jumping to a new platform and ecosystem to meet new requirements, learn one at the start...