Improving Medical Image Processing With AI


Machine learning is being integrated with medical image processing, one of the most useful technologies for medical diagnosis and surgery, greatly expanding the amount of useful information that can be gleaned from scan or MRI. For the most part, ML is being used to augment manual processes that medical personnel use today. While the goal is to automate many of these functions, it's not clea... » read more

Easier And Faster Ways To Train AI


Training an AI model takes an extraordinary amount of effort and data. Leveraging existing training can save time and money, accelerating the release of new products that use the model. But there are a few ways this can be done, most notably through transfer and incremental learning, and each of them has its applications and tradeoffs. Transfer learning and incremental learning both take pre... » read more

Week In Review: Design, Low Power


Tools Cadence's digital and custom/analog flows were certified for TSMC's N3 and N4 process technologies. Updates for the digital flow includes efficient processing of large libraries, additional accuracy during library cell characterization and static timing analysis, and support for accurate leakage calculation required in N3 and static power calculation for new N3 cells. Synopsys' digita... » read more

Rising Fortunes For ICs In Health Care


Semiconductors are increasingly finding their way into a variety of medical devices, after years of slow growth and largely consumer electronics types of applications. Nearly every major chipmaker has a toehold in health care these days, and many are starting to look beyond wearable such as the Apple Watch to devices that can be relied on for accuracy and reliability. Unlike in the past, the... » read more

Competing Auto Sensor Fusion Approaches


As today’s internal-combustion engines are replaced by electric/electronic vehicles, mechanical-system sensors will be supplanted by numerous electronic sensors both for efficient operation and for achieving various levels of autonomy. Some of these new sensors will operate alone, but many prominent ones will need their outputs combined — or “fused” — with the outputs of other sensor... » read more

Make Your SoC Upgradable Like A Tesla


I’ve always been a fan of Tesla. Not for the quick acceleration, nice lines, great handling or leading the world away from the using the internal combustion engine. I’m a big fan because they plan products not just for use today, but for the future. In the not too distant past, in order to get the latest automotive technology, you’d have to buy a new car. With Tesla, you don’t have to. ... » read more

Security Risks Grow With 5G


5G mobile phones can download a movie in seconds rather than minutes, but whether that can be done securely remains to be seen. What is clear from technology providers, though, is they are taking security very seriously with this new wireless technology. More data is in motion, and the value of that data is growing as users rely on mobile devices for everything from banking to automotive saf... » read more

Overview Of Medical Chip Challenges


Medical devices are adopting, and increasingly adapting, a variety of semiconductor technologies to provide new functions and capabilities in smaller form factors. In doing so, they are leveraging increasing processing capabilities, lower power, and new types of sensors to propel health care forward. Many different chip types have been used in medical devices for years, many of them develope... » read more

Long-Haul Trucking With Fewer Drivers


The trucking industry is betting heavily on increasing levels of autonomy and electrification to reduce the cost of moving goods and to overcome persistent problems. The economics of autonomous driving are compelling, not least of which is an almost perpetual shortage of qualified drivers. But there also are a number of technical hurdles to making this work. On top of the challenges facing t... » read more

Tradeoffs Between Edge Vs. Cloud


Increasing amounts of processing are being done on the edge, but how the balance will change between what's computed in the cloud versus the edge remains unclear. The answer may depend as much on the value of data and other commercial reasons as on technical limitations. The pendulum has been swinging between doing all processing in the cloud to doing increasing amounts of processing at the ... » read more

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