Mike Henry, Co-Founder and CEO of Mythic

In 2022 the industry will see a big uptick in processing AI workloads at the edge, moving away from cloud processing. New advancements in AI computing technologies, such as analog compute-in-memory, are driving this shift by enabling extremely powerful processing at the edge while maintaining low power consumption – all in a compact processor. Industrial automation is one sector where a significant amount of processing is already being done at the edge, and this will only continue into 2022 as factories increasingly rely on robots with machine vision to boost productivity and increase safety. While autonomous drones are another popular use case for edge-AI, a lot of people might be surprised to hear that in 2022 we’ll start to see drones being used to detect potential wildfire outbreaks. Finally, the automotive industry is another segment that will continue to see an increase in edge AI processing, whether it’s for assisted driving features in consumer vehicle applications or safety monitoring applications for commercial applications.

By Rich Goldman, Director of Marketing, Ansys

What novel thing did Apple, Tesla, Microsoft, Google & Amazon all do in 2021? They all designed bespoke silicon, specific to their application to give them each a big competitive advantage. As an added bonus, bespoke silicon reduced the dependency on standard silicon making these companies less vulnerable to the great semiconductor shortage of 2021.

Competitors have noticed, and they are ramping up to make bespoke silicon the driving trend of 2022. But bespoke silicon isn’t as accessible as ASIC was back in the day. Whereas ASIC democratized chip design and enabled many a startup, bespoke silicon is driven by innovative systems companies with specific applications. These systems companies are bringing their systems expertise to IC design. Bespoke chips are much larger, encompassing many more functions, and are driving the second big trend of 2022, 3D-IC.

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2022 Outlook: Chip shortage continues and drives opportunities to tier 2 fabs

It won’t come as a surprise when I predict that the current chip shortage will continue to affect the industry throughout 2022. The shortage is there and it’s real. Most foundries are at or near maximum capacity and since consumer or OEM demand is not backing off, the supply shortage is set to continue throughout 2022, at least.

This won’t just affect when you get to upgrade your smartphones and tablets – the chip shortage is having a significant impact on the automotive market and that also is set to continue as the industry’s ‘chip needs’ expands.

Automotive systems may have accounted for a small percentage of chips manufactured by the tier 1 manufacturers (3-4% at TSMC for example, compared to close to 50% for consumer electronics) but the fact is the car industry’s needs are growing exponentially and inexorably.

The trends in vehicle electronics and systems – including the shift to electric vehicles in a race to meet global emissions targets – plus the move to a future of connected and autonomous vehicles (CAVs) – all lead to an increased demand for sensors. Today, an ‘average’ car might have 100 sensors, that number is set to rocket as vehicles become more automated and as functional safety requirements in CAVs necessitate increased volumes of sensors.

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The View Towards ’22

Based upon the events of the last two years, two adages can readily apply: “the only certainty is uncertainty” and “beyond this place there be dragons.” Looking towards 2022, predicting what the future holds for product development in general and EDA technology specifically requires some critical thinking. Add the current chip shortage to the mix and the picture becomes more complex.

Current and next-generation high frequency/high data rate products have very little latitude in terms of “wiggle room” using traditional materials and components. Very small structures such as microvias and solder joints, not addressed during design, can become single points of failure that can mean the difference between a working product or a failed one. The EDA toolsets used to design these features must have a high degree of granularity and accuracy and be able to simulate and predict product manufacturability, operability and reliability. The ability to mitigate these factors will also help satisfy customer needs, maintain competitive advantages and maximize product revenues.

Most importantly, the foregoing challenges create a mandate for rethinking traditional design approaches. For EDA toolsets, lessons borrowed from other industries such as AI and machine learning will play an expanding role. For product designers, the ability to simulate and predict downstream product development processes may well determine the success or failure of current and future products.

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5 Key AI Predictions and Trends to Keep on Your Radar in 2022

By Stelios Diamantidis, Sr. Director, Synopsys AI Solutions, Office of the COO

From innovations in edge AI and computer vision to data modernization and specialized AI chips – with AI even designing some of those chips – there is no question that AI advancement has hit an all-time high in the past year. The global market value for AI chipsets is anticipated to grow to more than $70 billion by 2026, up $62 billion since 2019. This massive surge can be attributed to the swell of IoT devices with machine-learning capabilities and the evolution of smart cities.

As 2022 begins, so does a new era of technological innovation. With ongoing obstacles such as the global chip shortage, COVID-19 and supply chain challenges, the appetite for smart everything has put AI on all the big players’ wish lists.

Let’s dive into five key predictions on what we anticipate will usher in the next wave of AI development this year.

1. The Impact of AI in Chip Design Will Continue to Grow

With more workloads requiring advanced levels of AI processing to power intelligent functions, the need for dedicated chips that are energy-efficient and perform computations at higher speeds will make robust AI chip designs paramount. A new breed of design tools that learn from iterations and leverage data in chip design environments offer a leap forward in productivity and cost efficiency. The AI disruption will open new opportunities not only for the semiconductor leaders but also for companies that typically had smaller teams or more limited financial resources and weren’t previously seen as powerhouses of chip design to deliver exciting silicon solutions ― leveling the playing field, in a sense, and creating a perfect symmetry of companies leveraging AI in chip design across the global economy.

Designing the AI hardware of the future will require a revolution in chip design technology. In 2021, companies that dared to invest in the data center market witnessed significant gains and demonstrated impressive technical capabilities that increased the demand for dedicated AI chips, raising AI funds at an unprecedented pace. With GPUs continuing to be the dominant architecture for training in the data center market, we expect this growth to continue and see hyperscalers opting for next-generation AI-assisted design systems to massively scale exploration design workflows while automating less consequential decisions. Companies will start pivoting to the cloud for their chip design needs ― a victory for additional capacity, faster turnaround times, and high-quality application-optimized design.

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In 2021, we witnessed an increase in the number of road fatalities in the US. Vehicles are getting safer, embedding more safety sensors, and yet, more people are losing their dear ones on the roads. In order to increase road safety, as many vehicles should be equipped with V2X, as early as possible.

Indeed, V2X deployment is continuing to move forward toward mass deployment. In 2021, V2X was added to the production programs of most OEMs, and the rest will soon follow.

Before Autotalks, Onn developed VLSI and communication systems and handled standardization and market development. Onn was working for an elite R&D unit in IDF, Texas Instruments, and Passave (acquired by PMC-Sierra).

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Due to the importance to outperform in the electronic industry more companies are improving their leverage on the material management, Smart factory and Industry 4.0 are basic elements in order to achieve such objectives, based on this demand VCcount launches the XRHCount Inline. As it is fully integrated into the manufacturing processes, the system is fully automatic and can count small components on various types of packages around the clock within ten seconds per cycle.

The XRHCount Inline impresses due to the embedded high degree of automation. Loading and unloading is carried out by a conveyor belt, and the reel ID is automatically read and recorded by a scanner.

Based on the concept of autonomous operation, and taking into account that all manual processes were eliminated, it runs without an operator – eliminating labour in the process.
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“…and then you add as much memory as you can afford”, I heard the clerk tell the woman next to me. I was at a computer store looking for Christmas presents when I overheard a conversation between a customer discussing her soon to be laptop. I think this clerk gives advice that we have heard for a while, but going forward, it is going to be even more relevant and important.

Today, we take the digital equipment on our desk, pocket, arm or in the cloud for granted, it is there, all the time, connected, providing all the services we need and entertainment in the very best definition available.

So, why did this woman hesitate, to max out the memory? Cost, most certainly. We all know that memory is expensive. But, how come we only use a fraction of it… it so turns out that research has found out that up to 70% of the main memory content is redundant. Wouldn’t it make sense to find a way to put that redundant space to work?

Klas Moreau
CEO
ZeroPoint Technologies

Klas is a determined and results focused industry leader, with 25 years of progressive leadership experience in global enterprise environments. Optimistic and enthusiastic about what technology can achieve, he has gravitated to technology-centered companies. That interest has taken him to industries ranging from Telecom and Datacom to Computer games over to AI and cutting edge Integrated Circuit product innovations.

 

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