Blog Review: Nov. 29


ANSYS' Robert Harwood offers a reminder that autonomous and assisted driving technology are still very much works in progress, and flawed ones at that. It will take an estimated 5 billion to 10 billion road miles to effectively train self-driving algorithms. So far, Google has logged about 3.5 million miles. Along the same lines, Mentor's Paul Johnston takes a look at the electric car market... » read more

System Bits: Nov. 7


Exposing logic errors in deep neural networks In a new approach meant to brings transparency to self-driving cars and other self-taught systems, researchers at Columbia and Lehigh universities have come up with a way to automatically error-check the thousands to millions of neurons in a deep learning neural network. Their tool — DeepXplore — feeds confusing, real-world inputs into the ... » read more

Testing Autonomous Vehicles


After I wrote last month about my concerns about the pending legislation that appears to relax safety regulations for autonomous vehicles being tested on public roads, it seems I am not alone and some safety groups have also expressed concern. Of course, the promise of autonomous driving is exciting and will absolutely save lives — when the technology and infrastructure are ready — there... » read more

Frenzy At 10/7nm


The number of chipmakers rushing to 10/7nm is rising, despite a slowdown in Moore's Law scaling and the increased difficulty and cost of developing chips at the most advanced nodes. How long this trend continues remains to be seen. It's likely that 7/5nm will require new manufacturing equipment, tools, materials and transistor structures. Beyond that, there is no industry-accepted roadmap, m... » read more

System Bits: Aug. 8


Improving robot vision, virtual reality, self-driving cars In order to generate information-rich images and video frames that will enable robots to better navigate the world and understand certain aspects of their environment, such as object distance and surface texture, engineers at Stanford University and the University of California San Diego have developed a camera that generates 4D images... » read more

System Bits: June 27


Entangling photons for bug-proof communication With the increasing processing power of computers, conventional encryption of data is becoming increasingly insecure, reminded Fraunhofer researchers that are proposing one solution is coding with entangled photons. The team is developing a quantum coding source that allows the transport of entangled photons from satellites, expected to be an impo... » read more

Tech Talk: ISO 26262


Arteris' Kurt Shuler discusses what's changing in the automotive standard and how everything is supposed to work in the future. » read more

The Software Side Of Self-Driving


Just as the overall system complexity is causing ripples through the automotive supply chain so too is managing the system complexity, with software in particular. With so much new technology, and so many new ideas to keep track of, it would seem a huge undertaking by the automotive OEMs. In the midst of making decisions about the usual incremental improvements, the system architecture decis... » read more

System Bits: Oct. 4


Light deflection through fog In a development that could lead to computer vision systems that work in fog or drizzle, which have been a major obstacle to self-driving cars, MIT researchers have developed a technique for recovering visual information from light that has scattered because of interactions with the environment — such as passing through human tissue. This technology — called... » read more

System Bits: May 24


Controlling autonomous vehicles in extreme conditions In an approach that could help make self-driving cars of the future safer under hazardous road conditions, a Georgia Institute of Technology research team devised a way to help keep a driverless vehicle under control as it maneuvers at the edge of its handling limits. According to the team comprised of researchers from Georgia Tech’s D... » read more

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