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Weird Incidents Reveal L5 Challenges


A series of surprising, counterintuitive, and sometimes bizarre incidents reveal the challenges of achieving full Level 5 autonomy in self-driving vehicles, which are an increasingly common site in major cities. While it’s easy to dismiss such anecdotes as humorous glitches compared with the sobering accounts of autonomous tech-related injuries and fatalities, industry executives say these oc... » read more

Beyond Autonomous Cars


As the automotive industry takes a more measured approach to self-driving cars and long-haul trucks for safety and security reasons, there is a renewed focus on other types of vehicles utilizing autonomous technology. The list is long and growing. It now includes autonomous trains, helicopters, tractors, ships, submarines, drones, delivery robots, motorcycles, scooters, and bikes, all of whi... » read more

Rethinking Machine Learning For Power


The power consumed by machine learning is exploding, and while advances are being made in reducing the power consumed by them, model sizes and training sets are increasing even faster. Even with the introduction of fabrication technology advances, specialized architectures, and the application of optimization techniques, the trend is disturbing. Couple that with the explosion in edge devices... » read more

Driver Monitoring Raises Complexity, Adds Privacy Concerns


While you watch the road, your car may be watching you back. The automotive industry’s transition toward self-driving technology means cars increasingly are equipped with features that measure driver alertness and engagement, among many other data points. Executives say such features save lives and spur innovation, while simultaneously raising significant technical, legal, and ethical questio... » read more

AI Power Consumption Exploding


Machine learning is on track to consume all the energy being supplied, a model that is costly, inefficient, and unsustainable. To a large extent, this is because the field is new, exciting, and rapidly growing. It is being designed to break new ground in terms of accuracy or capability. Today, that means bigger models and larger training sets, which require exponential increases in processin... » read more

Where Are The Autonomous Cars?


Are we there yet? Governments, consumers, and engineers alike want to know how close the automotive world is to producing a fully autonomous Level 5 vehicle. While some experts say such vehicles could hit the road in the next few years, they're a shrinking minority. Most forecasts say a truly self-driving car is at least a decade away — and maybe much longer, because it requires disruptive... » read more

Audio, Visual Advances Intensify IC Design Tradeoffs


A spike in the number of audio and visual sensors is greatly increasing design complexity in chips and systems, forcing engineers to make tradeoffs that can affect performance, power, and cost. Collectively, these sensors generate so much data that designers must consider where to process different data, how to prioritize it, and how to optimize it for specific applications. The tradeoffs in... » read more

How To Optimize A Processor


Optimizing any system is a multi-layered problem, but when it involves a processor there are at least three levels to consider. Architects must be capable of thinking across these boundaries because the role of each of the layers must be both understood and balanced. The first level of potential optimization is at the system level. For example, how does data come in and out of the processing... » read more

Choosing Which Tasks To Optimize In Chips


The optimization of one or more tasks is an important aspect of every SoC created, but with so many options now on the table it is often unclear which is best. Just a few years ago, most people were happy to buy processors from the likes of Intel, AMD and Nvidia, and IP cores from Arm. Some even wanted the extensibility that came from IP cores like Tensilica and ARC. Then, in 2018, John Henn... » read more

Expedera: Custom Deep Learning Accelerators Through Soft-IP


Internet of Things (IoT) and Artificial Intelligence (AI) have caused a massive increase in data generation — and along with it, a need to process data faster and more efficiently. Dubbed a “tsunami of data,” data centers are expected to consume about one-fifth of worldwide energy before 2030. This data explosion is driving a wave of startups looking to gain a foothold in custom accele... » read more

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