Special Report

Winners And Losers At The Edge
No company owns this market yet — and won’t for a very long time.

Top Stories

Are Better Machine Training Approaches Ahead?
Why unsupervised, reinforcement and Hebbian approaches are good for some things, but not others.

Variables Complicate Safety-Critical Device Verification
Experts at the Table: What’s the best way to approach designs like AI chips for automotive that can stand the test of time?

Blogs

Mentor’s Jacob Wiltgen advocates for an automated, systematic approach to identifying design susceptibility to single event upset (SEU) through structural and static analysis, Mitigating The Effects Of Radiation On Advanced Automotive ICs.

Synopsys’s Ron DiGiuseppe sees a growing number of sensors and data processing requirements having a big impact on automotive Ethernet network and gateway function, in Automotive Gateway IP Enabling Scalable Automotive Platforms.

Arteris IP’s Kurt Shuler observes that with electronics now accounting for 40% or more of a vehicle’s cost, Tier-1s and OEMs are paying much closer attention to the ownership of automotive SoC architectures, in An Automotive Value Chain In Flux.

Rambus’ Maxim Demchenko explains how to keep the benefits of Ethernet’s flexibility while protecting data in motion, in The Evolution Of Ethernet To 800G And MACsec Encryption.

Maxim Integrated’s John Christopher Rice digs into how to evaluate the magnitude of parasitic resonances and electromagnetic interference in a switch-mode power supply, in Understand MOSFET Switch Behavior Via An LED Driver Simulation.

Tortuga Logic’s Jason Oberg outlines how to determine the return on investment for security practices, in Reducing Hardware Security Risk.

Cadence’s Paul McLellan takes a look at Cornami, a new startup promising a revolutionary way of working with encrypted data, in New Design For Trusted Data.