Chip Industry Week in Review


The Biden-Harris Administration announced preliminary terms with HP for $50 million in direct funding under the CHIPs and Science Act to support the expansion and modernization of HP’s existing microfluidics and microelectromechanical systems (“MEMS”) facility in Corvallis, Oregon. CHIPS for America launched the CHIPS Metrology Community, a collaborative initiative designed to advance ... » read more

Chip Industry Week In Review


By Jesse Allen, Karen Heyman, and Susan Rambo UMC and Intel will collaborate on the development of a 12nm semiconductor process platform to address high-growth markets, such as mobile, communications infrastructure, and networking. Apple reportedly pushed back the launch date of its long-awaited electric vehicle and scaled back the self-driving features to L2 driver assistance, according ... » read more

Chip Industry Week In Review


By Susan Rambo, Karen Heyman, and Liz Allan The Biden-Harris administration designated 31 Tech Hubs across the U.S. this week, focused on industries including autonomous systems, quantum computing, biotechnology, precision medicine, clean energy advancement, and semiconductor manufacturing. The Department of Commerce (DOC) also launched its second Tech Hubs Notice of Funding Opportunity. ... » read more

Chip Industry Week In Review


By Gregory Haley, Jesse Allen, and Liz Allan TSMC told equipment vendors to delay deliveries of the most advanced tools due to uncertain demand, according to Reuters. The news drove down stock prices of all the major equipment providers. On the other hand, TSMC said advanced packaging shortages will constrain AI chip shipments for the next 18 months, according to NikkeiAsia. The United St... » read more

Week In Review: Auto, Security, Pervasive Computing


Hyundai, Samsung Catalyst Fund, and others invested a combined $100 million in Canada-based Tenstorrent to accelerate the design and development of AI chiplets and machine-learning software and allow the integration of AI into future Hyundai, Kia, and Genesis vehicles, plus other future mobilities such as robotics and advanced air mobility (AAM). The National Highway Traffic Safety Administr... » read more

Week In Review: Auto, Security, Pervasive Computing


The Biden-Harris Administration announced the U.S. Cyber Trust Mark, a cybersecurity certification and labeling program to help consumers choose smart devices less vulnerable to cyberattacks. The Federal Communications Commission (FCC) is applying to register the Cyber Trust Mark with the U.S. Patent and Trademark Office and it would appear on qualifying smart products, including refrigerators,... » read more

Week In Review: Design, Low Power


Keysight Technologies said it intends to acquire ESI Group for €913 million (~$998.6 million). ESI Group provides virtual prototyping solutions for the automotive and aerospace end markets that can create real-time digital twins to simulate a product's behavior during testing and real-life use. MLCommons announced the latest results from two MLPerf benchmark suites. One aims to measure the... » read more

Week In Review: Design, Low Power


MLCommons debuted the latest results for the MLPerf Inference v3.0 and Mobile v3.0 benchmark suites, which measure the performance and power-efficiency of applying a trained machine learning model to new data in data center, edge, and mobile use cases. Overall, MLCommons said the results showed both power efficiency improvements and significant gains in performance in some benchmark tests. Seve... » read more

The Problem With Benchmarks


Benchmarks long have been used to compare products, but what makes a good benchmark and who should be trusted with their creation? The answer to those questions is more difficult than it may appear on the surface, and some benchmarks are being used in surprising ways. Everyone loves a simple, clear benchmark, but that is only possible when the selection criteria are equally simple. Unfortuna... » read more

Standard Benchmarks For AI Innovation


There is no standard measurement for machine learning performance today, meaning there is no single answer for how companies build a processor for ML across all use cases while balancing compute and memory constraints. For the longest time, every group would pick a definition and test to suit their own needs. This lack of common understanding of performance hinders customers' buying decis... » read more