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Computer Vision as the New Industry Growth Driver? Perspectives from the Embedded Vision Summit Investor Panel

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This article was originally published by Embedded Vision Alliance consultant Dave Tokic. It is reprinted here with Tokic's permission.

It seems to me that hardly a day goes by without some mention of self-driving cars (mostly good, some tragic), drones that follow you to record your ski run, augmented and virtual reality goggles that immerse you in another world, or smart doorbells that recognize who’s at the door. All of these are made possible through the recent impressive innovation in machine vision and deep learning technologies and you can read more about it in my recent post covering the Embedded Vision Summit Business Insights Track that I moderated.

What was a buzz a couple years ago is now a roar. The beat of vision-based acquisitions is increasing and investment dollars are pouring in. But what are those investors looking for?

The 5-person expert panel was moderated by Jeff Bier, Embedded Vision Alliance founder, and included Don Faria (Intel Capital), Jeff Hennig (Bank of America Merrill Lynch), Gabriele Jansen (Vision Ventures), Helge Seetzen (TandemLaunch), and Peter Shannon (Firelake Capital Management).

Here's a video preview (see here for the full video):

The panelists provided their insights on the evolution of vision technology into the mainstream, attributes they look for when evaluating companies, and some of the hot technologies and application spaces.

Out of the discussion, I saw four key themes emerge.

  1. Vision is a hot and growing area of investment. Even though computer vision has been in research and used in certain applications for decades, like industrial inspection or even barcode scanners, recent advancements have enabled the application of vision to many more markets.

    These large opportunities (e.g. reports showing the ADAS market to grow to $100B by 2022, AR / VR market to grow to $150B by 2022, drones market growing to $12B in 2021, etc.) and high profile acquisitions ($2B for Oculus by Facebook, $350M for Apical by ARM, $150M for Magic Pony by Twitter) have created a very friendly VC and internal investment environment, spurring impressive innovation and integration across vision algorithms, machine learning, sensors, and both cloud-based and embedded compute technologies.
     

  2. It’s not only about the technology. Investors are looking more deeply at the startup’s exec team and the business / GTM plan in addition to making sure they have strong technology IP. The right CEO and exec team can make or break a startup. The technical depth, energy, and enthusiasm of a young technologist founder can drive impressive development results and an exciting work environment, but having a seasoned team can focus that energy on developing the right products and ecosystems for the market opportunity, landing the right initial customers that won’t thrash resources, and tightly managing burn rate so the company can get off the ground before the money runs out.

    It was quoted that it takes 5% of the effort to make a really impressive demo and 95% to productize the technology to ship. That requires a strong grasp on where to apply the investment dollars.

    Building on that, the company must have a value proposition and go-to-market (GTM) plan that clearly communicates the business problems they address rather than just crowing about the gee-whiz algorithms or raw performance they provide. The ability to connect with the customer’s business challenges is crucial to getting customers on board and accelerating revenue. Unfortunately, in a lot of startups, marketing and sales is not appreciated as much as the technology itself. I’ve seen many tech startups lack this ability and this point was hit on many times by the panel… e.g. “that’s a great idea and really interesting technology, but I don’t know how you’re going to make money.”
     

  3. Will we see more vision technology “unicorns”? While investment in vision is certainly increasing, the trend is moving from exuberant investment to ones based on a more traditional business rationale. Increased investor caution is generally being driven by unicorn blowback, market uncertainty, and accelerating return on investment. This is driving deeper diligence in both the technology and business fundamentals. Is the startup applying the latest vision technology to create a product or actually inventing that state of the art technology while also creating the product and developing a new market? These have very different investment needs and risks that must be thoughtfully outlined in the business plan to pass VC “sniff tests”. But while there is more scrutiny, there are a lot of investment dollars available.
     
  4. This brave new world is moving faster than regulations and security can keep up. There has been intense discussion and debate on both the safety and security of autonomous vehicles and drones over the past few years and a flurry of initial bills and regulations have already been introduced this year. This process will undoubtedly accelerate as the number of autonomous vehicles and drones increases and unfortunately as more incidents occur while the technologies evolve.

    Similarly, cybersecurity concerns for these cars and other connected IoT devices is growing at a fever pitch, especially as we see more high-profile (though sometimes canned) hacks, with increasing investment in both startups and in established security companies. This was a key topic at the recent RSA Conference 2016, creating both FUD (fear, uncertainty, and doubt) for users and enterprises and growth opportunity for those creating solutions to address the real and perceived risk.

    Here are a few links and recent articles.

As usual, the combination of tremendous innovation, huge potential markets, available investment money, and a healthy dose of excitement means there are great opportunities for a vision startup to get funded.

Do you think so too?  Please share your thoughts…

About the Author

I strongly believe that a huge wave of innovation and growth will come from the convergence of machine learning and machine vision technology deployed to the enterprise and consumers through connected IoT devices and strong ecosystems. I help companies succeed by creating winning products, go-to-market programs, and the targeted ecosystems necessary to accelerate revenue growth. Let me know how I can help you.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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