Quality Issues Widen


As the amount of semiconductor content in cars, medical and industrial applications increases, so does the concern about how long these devices will function properly—and what exactly that means. Quality is frequently a fuzzy concept. In mobile phones, problems have ranged from bad antenna placement, which resulted in batteries draining too quickly, to features that take too long to load. ... » read more

A Brief History of Test


The history of semiconductor test systems is the subject of this blog post. We’ll turn to printed circuit board testing at another time. Boston-based Teradyne sold its D133 diode tester to Raytheon in 1961. Five years later, it introduced the J259 integrated circuit tester, which had a minicomputer to run the test programs. For many, this marks the beginning of automatic (or automated) tes... » read more

The Week In Review: Manufacturing


SPIE news At this week’s SPIE Advanced Lithography conference, the industry paid close attention to the progress of extreme ultraviolet (EUV) lithography. Here’s the general report card: EUV is making noticeable progress, but there are still some challenges ahead, such as the power source, resists and pellicles. Several issues need to be resolved before chipmakers can put EUV into mass... » read more

Big Data On Wheels


By Jeff Dorsch & Ed Sperling All kinds of chips are going into driver-assisted and autonomous cars. On one side are arrays of sensors, which are generating huge amounts of data about everything from lane position and proximity to other cars to unexpected objects in the road. On the other side are the chips required to process that data at blazing speed. As the market for PCs and mobil... » read more

What Does An AI Chip Look Like?


Depending upon your point of reference, artificial intelligence will be the next big thing or it will play a major role in all of the next big things. This explains the frenzy of activity in this sector over the past 18 months. Big companies are paying billions of dollars to acquire startup companies, and even more for R&D. In addition, governments around the globe are pouring additional... » read more

The Week In Review: Manufacturing


Chipmakers Recently, Intel announced plans to invest more than $7 billion to complete its previously-announced fab in Chandler, Ariz. Targeted for 7nm processes, Fab 42 will be completed in 3 to 4 years. As reported, the fab announcement was made by U.S. President Donald Trump and Intel CEO Brian Krzanich at the White House. There is more to the story. Typically, Intel has two fabs for a gi... » read more

AI Storm Brewing


AI is coming. Now what? The answer isn't clear, because after decades of research and development, AI is finally starting to become a force to reckon with. The proof is in the M&A activity underway right now. Big companies are willing to pay huge sums to get out in front of this shift. Here is a list of just some of the AI acquisitions announced or completed over the past few years: ... » read more

Custom Hardware Thriving


In the early days of the IoT, predictions about the commoditization of hardware and the end of customized hardware were everywhere. Several years later, those predictions are being proven wrong. Off-the-shelf components have not replaced customized hardware, and software has not dictated all designs. In fact, in many cases the exact opposite has happened. And where software does play an elev... » read more

What Does AI Really Mean?


Seth Neiman, chairman of eSilicon, founder of Brocade Communications, and a board member and investor in a number of startups, sat down with Semiconductor Engineering to talk about advances in AI, what's changing, and how it ultimately could change our lives. What follows are excerpts of that conversation. SE: How far has AI progressed? Neiman: We’ve been working with AI since the mid 1... » read more

Blog Review: Feb. 22


Mentor's Brian Derrick digs into the state of the electric vehicle industry and whether established OEMs will be able to make the changes required to meet new consumer demands. Cadence's Paul McLellan listens in on how to greatly improve the efficiency of machine learning, without using custom hardware, in a talk by Stanford's Kunle Olukotun. Synopsys' Robert Vamosi warns not to overlook ... » read more

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