Under the lens…and under many other things: Ambarella

You’ll notice that while I do style myself as an expert on some things, I never claim that I know everything…because I obviously don’t.

This became clear to me when I was watching the Paravision Converge 2021 video and noticed its emphasis on optimizing Paravision’s recognition algorithms for Ambarella.

Ambarella-related announcements from https://www.paravision.ai/converge2021/.

I had never heard of Ambarella.

I should have heard of it.

Even in my own little corner of the technology world, Ambarella has made an impact:

We power a majority of the world’s police body cams.

We were the first to enable HD and UHD security with low power; we revolutionized image processing for low-light and high-contrast scenes; and we are an industry leader in next-generation AI video security solutions.

Video has been a key component of face detection, person detection, and face recognition for years. (Not really of iris recognition…yet.) In certain use cases, it’s extremely desirable to move the processing out from a centralized server system to edge devices such as body cams, smart city cameras, and road safety cameras, and Ambarella (and its software partners) optimize this processing.

In addition to professional (and consumer) security, Ambarella is also a player in automotive solutions including autonomous vehicles, non-security consumer applications, and a variety of IoT/industrial/robotics applications.

All of these markets are supported via Ambarella’s specialized chip architecture:

Our CVflow® chip architecture is based on a deep understanding of core computer vision algorithms. Unlike general-purpose CPUs and GPUs, CVflow includes a dedicated vision processing engine programmed with a high-level algorithm description, allowing our architecture to scale performance to trillions of operations per second with extremely low power consumption.

I’ve always been of the opinion that technology is moving away from specialized hardware to COTS hardware. For example, the fingerprint processing and matching that used to require high-end UNIX computers with custom processor boards in the 1990s can now be accomplished on consumer-grade smartphones.

However, the reason that these consumer-grade devices can now perform these operations is because specialized technologies have been miniaturized and optimized for incorporation into the consumer grade devices, such as Yi home video cameras.

Ambarella itself is US-based (in Santa Clara, California), was founded in 2004, is traded on NASDAQ, and is a $200+ million/year company (although revenues and profits have declined over the last few years). While much smaller than more famous semiconductor companies, Ambarella obviously fills a critical niche for (among others) professional security product firms.

So if you, like me, had never heard of Ambarella…now you have.


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