Our recent research shows that venture capital (VC) investment in computer vision technology firms has increased four-fold from 2016-2018 exceeding a total of $8 billion USD. We analysed over 1400 deals during this three year period. Our analysis also indicates that Chinese investors investing in Chinese companies are dominating the space accounting for over 56% of overall dollars invested and 8 of the 10 biggest deals.

2018 investments by companies in the People’s Republic of China (PRC) was three times the United States and almost 66% of overall capital invested. It was the reverse in 2016 when United States investors put four times more capital into computer vision than PRC investors. The data also shows that PRC investors pumped 20 times more capital into computer vision in 2018 than they did in 2016. And in 2018, the average deal size in China was nine times that of the US. So this isn’t about spreading more money to more companies but concentrating more investment capital in fewer start-ups. Although our data doesn’t include every single global venture capital investment it captures enough transactions to make this a clear trend.

This is evidence supporting Beijing’s goal of dominating artificial intelligence by 2030. I expect to see significant computer vision technology emerge out of China over the next five years and also anticipate that they will take a dominant position in the computer vision and video analytics global markets.

It seems that PRC recognises the pivotal position computer vision and video analytics plays in AI. Computer vision and video analytics are crucial artificial intelligence capabilities and are fundamental to most leading-edge physical business applications including autonomous vehicles, Internet of Things (IoT) edge computing, physical security, retail footfall and attention analysis, and smart manufacturing automation.

Yes, machines have confused images of blueberry muffins with chihuahuas. But let’s not let that distract us from the remarkable leaps of the past few years.  With advancements in convolutional neural network (CNN) machine learning and machine vision sensor technologies (e.g., liquid lenses), computer vision capabilities are skyrocketing and for some uses have surpassed human vision. Computer vision applications around object recognition in poor visibility, multi-spectral imaging and rapid multi-object tracking have tremendous potential to change our lives and disrupt industries as the world slowly transitions to one where indeed, the walls have eyes.

For most of the data analysis underpinning this post I am borrowing from my very talented computer vision analyst Nick Ingelbrecht. In addition to geography he provides an overall analysis and a look at the data by investment stage and technology sector. His full research paper entitled “Venture Capital Growth Insights: Computer Vision” is available to Gartner clients. Gartner is delivering this type of analysis on VC investments for a range of emerging technologies.

This article is republished from he Gartner blog with permission.

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