Week in Review: IoT, Security, Auto


Internet of Things Second-tier cities in the U.S. that can’t attract projects like the Amazon HQ2 are welcoming the testing of autonomous vehicles, smart city technology, and advanced surveillance techniques, this analysis notes. What do they get in return? Much of the time, little or nothing. And bad things can happen. People have been throwing objects at Waymo vehicles in Chandler, Ariz., ... » read more

Power/Performance Bits: Mar. 19


Explainable AI Researchers from Technische Universität Berlin (TU Berlin), Fraunhofer Heinrich Hertz Institute (HHI), and Singapore University of Technology and Design (SUTD) propose a pair of algorithms to help determine how AI systems reach their conclusions. Explainable AI is an important step towards practical applications, argued Klaus-Robert Müller, Professor for Machine Learning at... » read more

The Growing Challenge Of Thermal Guard-Banding


Guard-banding for heat is becoming more difficult as chips are used across a variety of new and existing applications, forcing chipmakers to architect their way through increasingly complex interactions. Chips are designed to operate at certain temperatures, and it is common practice to develop designs with some margin to ensure correct functionality and performance throughout the operat... » read more

Week in Review: IoT, Security, Auto


Internet of Things Apple purchased a portfolio of eight granted and pending patents that belonged to Lighthouse AI, a smart home security camera startup that ceased operations near the end of 2018. The portfolio was acquired at about the same time, according to the U.S. Patent & Trademark Office; financial terms weren’t revealed. Also not disclosed, as usual, is what Apple will do with t... » read more

Using Less Power At The Same Node


Going to the next node has been the most effective way to reduce power, but that is no longer true or desirable for a growing percentage of the semiconductor industry. So the big question now is how to reduce power while maintaining the same node size. After understanding how the power is used, both chip designers and fabs have techniques available to reduce power consumption. Fabs are makin... » read more

Memory Tradeoffs Intensify in AI, Automotive Applications


The push to do more processing at the edge is putting a strain on memory design, use models and configurations, leading to some complex tradeoffs in designs across a variety of markets. The problem is these architectures are evolving alongside these new markets, and it isn't always clear how data will move across these chips, between devices, and between systems. Chip architectures are becom... » read more

Using Analog For AI


If the only tool you have is a hammer, everything looks like a nail. But development of artificial intelligence (AI) applications and the compute platforms for them may be overlooking an alternative technology—analog. The semiconductor industry has a firm understanding of digital electronics and has been very successful making it scale. It is predictable, has good yield, and while every de... » read more

Finding Defects In Chips With Machine Learning


Chipmakers are using more and different traditional tool types than ever to find killer defects in advanced chips, but they are also turning to complementary solutions like advanced forms of machine learning to help solve the problem. A subset of artificial intelligence (AI), machine learning has been used in computing and other fields for decades. In fact, early forms of machine learning ha... » read more

Domain Expertise Becoming Essential For Analytics


Sensors are being added into everything, from end devices to the equipment used to make those sensors, but the data being generated has limited or no value unless it's accompanied by domain expertise. There are two main problems. One is how and where to process the vast amount of data being generated. Chip and system architectures are being revamped to pre-process more of that data closer to... » read more

Designing An AI SoC


Susheel Tadikonda, vice president of networking and storage at Synopsys, looks at how to achieve economies of scale in AI chips and where the common elements are across all the different architectures. https://youtu.be/fm0kxnj3DuM » read more

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