Week In Review: Design, Low Power


Memory CEA-Leti demonstrated 16-kbit ferroelectric random-access memory (FeRAM) arrays at the 130nm node. It utilizes back-end-of-line (BEOL) integration of TiN/HfO2:Si/TiN ferroelectric capacitors as small as 0.16 µm² and solder reflow compatibility for the first time for this type of memory. The researchers anticipate it will be useful for embedded applications such at IoT and wearable dev... » read more

Week In Review: Auto, Security, Pervasive Computing


Automotive Features of Toyota’s key fobs for entering vehicles get turned off when drivers do not start paying a subscription fee when the complementary subscriptions end, says an article in Ars Technica. SiLC Technologies announced its compact Eyeonic Vision Sensor, a FMCW lidar sensor, is now commercially available. The sensor has a silicon photonic chip that keeps a lidar’s size down... » read more

Revving Up SiC And GaN


Silicon carbide (SiC) and gallium nitride (GaN) are becoming more popular for power electronics, particularly in automotive applications, driving down costs as volumes scale up and increasing the demand for better tools to design, verify, and test these wide-bandgap devices. Both SiC and GaN are proving essential in areas such as battery management in electric vehicles. They can handle much ... » read more

Week In Review: Design, Low Power


Intel intends to take Mobileye public in mid-2022 on a US market through an IPO of newly issued stock. The subsidiary, which Intel acquired in 2017, develops SoCs for ADAS and autonomous driving solutions. Mobileye has achieved record revenue year-over-year with 2021 gains expected to be more than 40 percent higher than 2020, highlighting the powerful benefits to both companies of our ongoing p... » read more

Week In Review: Auto, Security, Pervasive Computing


Pervasive computing An outage in network equipment at the US-EAST-1 Region of Amazon Web Services this week reminded customers of the downside to having every appliance run via a data center. Users accessing apps tied to AWS on the East coast found services did not work, including Alexa, Ring, smart appliances, some Amazon warehouses and packaging delivery, web APIs such as Slack, and some str... » read more

Big Changes Ahead For Inside Auto Cabins


The space we occupy inside our vehicles is poised to change from mere enclosure to participant in the driving experience. Whether for safety or for comfort, a wide range of sensors are likely to appear that will monitor the “contents” of the vehicle. The overall approach is referred to as an in-cabin monitoring system (ICMS), but the specific applications vary widely. “In-cabin sensing... » read more

Week In Review: Manufacturing, Test


Packaging and test Taiwan’s ASE--the world’s largest OSAT--has announced the proposed sale and disposal of equity interests in its subsidiaries, GAPT Holding and ASE (Kun Shan), to Wise Road Capital, a private equity firm based in China. The deal has a value of $1.46 billion. The announcement is related to four ASE assembly and test facilities in China, including Shanghai, Suzhou, Kunsh... » read more

Week In Review: Auto, Security, Pervasive Computing


Automotive The U.S. Federal Trade Commission (FTC) sued Nvidia to block the company’s $40 billion acquisition of Arm. The FTC said in a press statement that “the proposed vertical deal would give one of the largest chip companies control over the computing technology and designs that rival firms rely on to develop their own competing chips. … the combined firm would have the means and in... » read more

Why It’s So Difficult — And Costly — To Secure Chips


Rising concerns about the security of chips used in everything from cars to data centers are driving up the cost and complexity of electronic systems in a variety of ways, some obvious and others less so. Until very recently, semiconductor security was viewed more as a theoretical threat than a real one. Governments certainly worried about adversaries taking control of secure systems through... » read more

Will Markets For ML Models Materialize?


Developers are spending increasing amounts of time and effort in creating machine-learning (ML) models for use in a wide variety of applications. While this will continue as the market matures, at some point some of these efforts might be seen as reinventing models over and over. Will developers of successful models ever have a marketplace in which they can sell those models as IP to other d... » read more

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