2023-05-23 - Infineon Technologies AG

Infineon strengthens embedded AI solutions with Imagimob acquisition

The Imagimob acquisition significantly complements Infineon's AI offerings.

2022-06-16 - Renesas Electronics Corp.

Renesas to acquire Reality AI

Renesas is enhancing its endpoint AI capability with the acquisition of Reality AI.

2022-02-17 - Majeed Ahmad

Audio chip moves machine learning from digital to analog

The machine learning chip processes natively analog data and analyzes it while consuming near-zero power to inference and detect events.

2022-02-09 - Infineon Technologies AG

Infineon and SensiML enable sensor data capture and ML models, announce design challenge

Infineon and SensiML are developing an easy and seamless process to capture data from Infineon XENSIV sensors, train ML models,…

2022-01-06 - Majeed Ahmad

Does analog have a place in the machine learning world?

Aspinity claims its inference-based analog signal processing technology provides a power-efficient solution for battery-operating devices.

2021-12-30 - Brian Dipert

2022 tech themes: A look ahead

Having recently reviewed the past year, our intrepid engineer now tackles forecasting the hot topics of the year ahead.

2021-12-09 - STMicroelectronics

STMicroelectronics enhances tool for ML applications development

NanoEdge AI Studio Version 3 is the first major upgrade of the software tool for machine-learning applications that ST acquired…

2021-08-26 - Majeed Ahmad

The profile of an ML software development toolset

NXP offers a software development environment for building ML applications using NXP microcontrollers and applications processors.

2021-06-28 - Ludovic Larzul, Mipsology

TOPS: The truth behind a deep learning lie

A formula for determining the real-world performance of AI and others chips when running deep learning workloads.

2021-06-23 - Richard Quinnell

A multi-tier approach to machine learning at the edge

A multi-tier approach to machine learning at the edge can help streamline both development and deployment for the AIoT.