AI at the Edge? It’s Complicated
True AI at the edge, meaning running neural networks on the smart device itself, is a thorny set of problems.
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…
Specification Challenge a Critical Step Toward Greater AI Safety
A report addresses specification as a way to avoid unintended behavior in machine learning systems.
India Launches Center of Excellence of IoT and AI
The Center of Excellence on IoT and AI at the Andhra University Campus, Visakhapatnam, aims at promoting innovation in emerging…
NVIDIA and Mavenir Tap L&T Technology to Accelerate Adoption of AI-on-5G Platform
LTTS will support Mavenir with customization, integration, and deployment of AI applications for deployment on NVIDIA's AI-on-5G Platform.
Lattice Acquires Mirametrix
The acquisition expands Lattice's software portfolio with complementary AI and computer vision capabilities.
IIT Delhi to Launch M.Tech in ‘MINDS’
M.Tech in MINDS is planned as an industry-sponsored program.
New BISTelligence Spin-Off Focuses on Manufacturing AI Solutions
BISTelligence has created Aidentyx to expand its innovative new asset performance management solutions for industrial manufacturing.
Optimizing Connected ML Algorithms
Where to place your machine learning code—in the cloud, on an edge device, or on-premise—always involves tradeoffs. Here are some…
Creating a Level Playing Field for Competing Neuromorphic Systems
Why objective benchmarks conducted by third parties may not yet be the answer.