Blog Review: July 25

Mentor’s Daniel Clarke takes a look at some of the challenges to effective sensor fusion in automotive and why it’s important to develop different sensing methodologies for particular driving tasks and levels of automation.

Cadence’s Meera Collier explains the evolution in wireless networks that’s brought us to 5G and why it will be such a big deal for a massively connected world.

Synopsys’ Eric Huang looks at what the wide adoption of USB Type-C in Android phones and PC laptops means for docking and peripheral compatibility.

Arm’s Nathan Chong dives into challenges that arise with transactions and weak memory in concurrent programs and why formal semantics and automated reasoning are powerful tools in identifying potential issues.

SEMI’s Christian G. Dieseldorff notes that 200mm fabs worldwide are gearing up to add more than 600,000 wafers per month from 2017 through 2022, with plans for new 200mm fabs in the works.

National Instruments’ James Kimery argues that there’s still a lot of work to be done for 5G, but for progress to be made, wireless researchers need to expand their focus to new application spaces.

ANSYS’ Wim Slagter examines the benefits and tradeoffs when it comes to cloud versus on-premise computing and offers several questions to consider when choosing between them.

A staff writer for Rambus notes that mobile payments are taking off in China, with 77% of all Chinese people using such services and 14% refusing to accept cash entirely, putting the country just ahead of India’s 76% adoption rate.

Nvidia’s Tony Kontzer explains how to teach a deep learning algorithm how to solve a Rubik’s Cube, and how that could translate to AI solving more complicated mathematical problems.

And don’t miss the blogs from last week’s Manufacturing & Process Technology newsletter:

Editor In Chief Ed Sperling looks at why the next steps in scaling will break the old rules.

Executive Editor Mark LaPedus talks with Leti’s CEO about a new Soitec deal and R&D trends.

Applied Materials’ Jonathan Bakke explains why future performance, power, area and cost improvements require materials engineered at the atomic scale.

GlobalFoundries’ Gary Dagastine contends that decentralized in-car network architectures lack the ability to react in real-time to the vast amount of data required by machine learning.

SEMI’s Scott Stevens finds an upbeat outlook across the industry.

Coventor’s Sofiane Guissi considers electrostatic control, planar process technology and superior RF and analog performance in FD-SOI.