Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there ...

Going from a microcontroller blinking an LED, to one that blinks the LED using voice commands based on a data set that you trained on a neural net work is a “now draw the rest of the owl&#822… ...

Arm says it has everybody beat in terms of volumes of AI and machine-learning chips deployed in the widest array of devices. Skip to main content Events Video Special Issues Jobs ...

Thu, Apr 10, 2025 | Updated 08:21 IST Updated 08:21 IST; Toggle navigation. Toggle navigation ...

Albert Zhichun Li, Ph.D., is Chief Security Scientist at Stellar Cyber. He has over 15 years of experience in cybersecurity research. Not long ago, the state of voice recognition was quite ...

While embedded processor vendors usually focus on the deployment side of machine learning (ML) designs, NXP has taken the extra step of offering tools for data preparation and model training. NXP, ...

The 200 MHz S6E2CCA series (Fig. 2) foregoes the 2D graphics engine and bulks up on memory to provide automatic speech recognition (ASR) support. It has a dual bank of 1 Mbyte flash along with 256 ...

Arm’s Project Trillium addresses machine learning (ML) and it includes a number of components, including the new ML processor (Fig. 1). This platform will support the Arm CPU complexes in a ...

Google bets on AI-first as computer vision, voice recognition, machine learning improve The shift may be bigger than mobile computing. Written by Larry Dignan, Contributor May 17, 2017 at 11:00 a ...