The market for computer vision companies is warm and getting warmer.
On Monday, March 13th, Intel Corp. announced its intention to acquire Israeli driverless car technology firm Mobileye for around $15.3 billion in an all-cash deal. It serves as Intel’s latest strategic investment into self-driving car technology, as well as one of the largest acquisitions of computer vision technology ever.
The Mobileye acquisition is also the third notable M&A event in the computer vision field in the last month. On February 19, the Times of Israel reported that Apple bought Tel Aviv-based facial recognition startup Realface for around $2 million. On February 20th, TechCrunch confirmed that Magic Leap, the augmented reality startup with around $1.4 billion in venture financing, has acquired the 3D division of Dacuda, a computer vision startup based out of Zurich.
Since 2011, US-based privately-held computer vision companies have raised over $780 million in financing from investors. In terms of the number of deals, the pace at which investors have deployed capital has slightly leveled off, but the amount of capital invested has only increased.
So far in 2017, Crunchbase has recorded 8 investment deals struck with computer vision companies totaling over $20.7 million dollars. If the 2016 investment market for equity computer vision companies is any indication, 2017 ought to be a fairly lively year.
And it’s not just investment that’s taken off. There have been a number of notable M&A events that have proved fairly lucrative for investors in computer vision companies. Here’s just a sampling from 2016:
- Intel acquired Movidius for $400 million.
- Twitter, ahem, ponied up $150 million for Magic Pony Technology.
- Snap Inc acquired Obvious Engineering for $47 million.
- Google bought Eyefluence for $21.6 million.
- Salesforce acquired Metamind for $32.8 million (over a 4x multiple on invested capital).
And these are just some of the greatest hits.
It’s no small wonder that computer vision is such a hot field right now. Computer vision sits at the intersection of a number of emerging and rapidly evolving technologies: ever smaller, sharper, and cheaper cameras; flexible, extensible machine learning platforms; and more efficient hardware running said machine learning algorithms. It has the chance of serving industries ranging from the security and defense sector to orbital satellite monitoring, drones, self-driving cars and, yes, even entertainment and smartphone manufacturers.
Frequent blogger and dyed-in-the-wool NYC startup investor Mark Suster indicated back in 2016 that computer vision “has become a major theme” for his investment activity. Why? He suggests that it marks a turning point in the way we interact with computers. Rather than text input through a keyboard, he believes that the future will be one where computers will take in and interpret the world through a wide variety of cameras and sensors.
For now, it seems like voice is the human-computer interaction medium du jour, thanks in no small part to the blow-out success of Amazon’s Alexa. But a future in which the smiling, if scrutinizing eyes – er, cameras and sensors – of various gizmos gaze constantly, incessantly upon us is just around the corner. Give it a couple of years. We, like computers, will wait to see.
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