Why TinyML Is Such A Big Deal


While machine-learning (ML) development activity most visibly focuses on high-power solutions in the cloud or medium-powered solutions at the edge, there is another collection of activity aimed at implementing machine learning on severely resource-constrained systems. Known as TinyML, it’s both a concept and an organization — and it has acquired significant momentum over the last year or... » read more

Always On, Always At Risk


Always-on devices are everywhere, and each of them is a potential target for hackers. While many people associate always-on devices with smart speakers such as an Amazon Alexa or Google Home, or a connected security camera, that's only one component in a system. There's a broader infrastructure behind those devices. So even if you power down a digital assistant/smart speaker, everything it's... » read more

Implementing Improved Security And Connectivity For The Smart Home


The smart home continues to evolve in available functions and complexity as several different connectivity protocols from numerous suppliers target a variety of products for use in smart homes. However, many consumers (71% according to incontrol) acknowledge fear of their personal information being stolen while using smart home products. At the same time, ease of use for user-installed products... » read more

Designing Chips In A ‘Lawless’ Industry


The guideposts for designing chips are disappearing or becoming less relevant. While engineers today have many more options for customizing a design, they have little direction about what works best for specific applications or what the return on investment will be for those efforts. For chip architects, this is proving to be an embarrassment of riches. However, that design freedom comes wit... » read more

Challenges For New AI Processor Architectures


Investment money is flooding into the development of new AI processors for the data center, but the problems here are unique, the results are unpredictable, and the competition has deep pockets and very sticky products. The biggest issue may be insufficient data about the end market. When designing a new AI processor, every design team has to answer one fundamental question — how much flex... » read more

Manufacturing Bits: July 27


Merchant quantum processors Startup QuantWare has launched the world’s first merchant and off-the-shelf superconducting processor for quantum computers. QuantWare’s quantum processor unit (QPU), called Soprano, is a 5-qubit device. The QPU can be customized for various applications. The device is ideal for research institutions and university labs. Quantum computing is a hot topic. A... » read more

The Great Quantum Computing Race


Quantum computing is heating up, as a growing number of entities race to benchmark, stabilize, and ultimately commercialize this technology. As of July 2021, a group from China appears to have taken the lead in terms of raw performance, but Google, IBM, Intel and other quantum computer developers aren’t far behind. All of that could change overnight, though. At this point, it's too early t... » read more

Behind The Intel-GlobalFoundries Rumor


A Wall Street Journal report that Intel is looking to buy GlobalFoundries has sparked discussions across the industry. But what exactly this would mean, and why now versus a couple years ago, needs some context. There are layers upon layers of irony behind this would-be deal, and it dates back decades to some rather famous encounters. Consider former AMD CEO Jerry Sanders' 1991 comment that ... » read more

Rocky Road To Designing Chips In The Cloud


EDA is moving to the cloud in fits and starts as tool vendors sort out complex financial models and tradeoffs while recognizing a potentially big new opportunity to provide unlimited processing capacity using a pay-as-you-go approach. By all accounts, a tremendous amount of tire-kicking is happening now as EDA vendors and users delve into the how and why of moving to the cloud for chip desig... » read more

Shifting Toward Data-Driven Chip Architectures


An explosion in data is forcing chipmakers to rethink where to process data, which are the best types of processors and memories for different types of data, and how to structure, partition and prioritize the movement of raw and processed data. New chips from systems companies such as Google, Facebook, Alibaba, and IBM all incorporate this approach. So do those developed by vendors like Appl... » read more

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