8CIOReview | | DECEMBER 2020IN MY OPINIONWith recent, rapid advancements in computer vision technologies and the increasing presence of these technologies in everyday life, it's unsurprising that the computer vision domain is top-of-mind both for investors looking to deploy capital in a growing space as well as for startup founders looking to advance the space through entrepreneurship. The computer vision space's growth has been of particular interest for Amino Capital: as a data-focus venture firm with many successful portfolio companies in the computer vision space like Orbeus (acquired by Amazon), Grokstyle (acquired by Facebook), Daedalean.ai, AIFI.io, Voyage.auto, BrainKey, and Wyze, Amino seeks to identify new, innovative technologies in the space and help them grow by leveraging the firm's expertise and resources.Additionally, Amino's team of technologists are doubly interested in the computer vision space's growth because of their expertise: partner Dr. Huican Zhu, for instance, is a pioneer of computer vision as the inventor of Google Image Search. I recently sat down for a conversation with Zhu to learn more about his thoughts on the growth of computer vision over the years, emerging applications in the space, and his advice for potential startup founders in computer vision.This interview has been lightly edited for clarity.YOU INVENTED GOOGLE IMAGE SEARCH IN 2000. COULD YOU TALK ABOUT THE GAP YOU SAW IN GOOGLE'S FUNCTIONALITY AT THE TIME, HOW GOOGLE IMAGE SEARCH DEALT WITH THAT, AS WELL AS ABOUT THE EVOLUTION OF GOOGLE SEARCH OVER TIME?When I started Google Image Search, and when we launched the product, the product was very straightforward compared to what you see today. Back then, Google had only web searches, which was text-based. You could only search for HTML pages as well as for some text. There was no image search, so I made Image Search.But, our image search engine at the time was also text-only in the sense that you could only type in something, like "cat" or some celebrity's name, and you would get a list of images related to your queries. You'd get images of cats back, you'd get pictures of Jennifer Lopez and other pictures. So, the image that returns from search comes to you because, somehow, the images are on webpages that happened to mention the keywords you searched. So, the first iteration of Google Image Search was keyword-based.Today, Google Image Search definitely evolved a lot, especially with advancements in AI, deep learning, and neural networks. Google Image Search today can do so many things: for example, similar image search and reverse image search. It's not completely related to Google Image Search, but Google Goggles can even do OCR (Optical Character Recognition) for you. If you give it an image, it can get all the text for you in that image. For example, if you take a picture of a restaurant, it can give you the restaurant's name and the opening time.It can do all kinds of other image classification. It can recognize objects for you: if you give it an image, it can tell you 20/20 VISION: DR. HUICAN ZHU ON THE FUTURE OF COMPUTER VISIONBy Patricia Tang, Sue Xu, Managing Partner, Amino Capital
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