Let us put some context here: With performances like 0.23% for the MNIST dataset or 2.53% for the NORB dataset, some people are already talking about Superhuman Visual Pattern Recognition. In a way the models will continue to improve. At the same time, we continue to see the steamrollers doing their job, where computations become cheaper and cheaper and can be done on the cloud. The time seems to be ripe for AI for images on the cloud.
Tomasz Malisiewicz, the man behind the tombone's computer vision blog, just graduated, founded a company (vision.ai) and is now starting a Kickstarter campaign: VMX: Computer Vision for Everyone
Hi Igor,We finally launched our kickstarter! We are trying to make computer vision, in particular real-time object detection and training, accessible to everyone. It would be awesome to get a short blurb with link to our kickstarter campaign on Nuit Blanche.VMX Project: Computer Vision for EveryoneWebapp for real-time training of visual object detectors and an API for building vision-aware apps.The VMX project was designed to bring cutting-edge computer vision technology to a very broad audience: hobbyists, researchers, artists, students, roboticists, engineers, and entrepreneurs. Not only will we educate you about potential uses of computer vision with our very own open-source vision apps, but the VMX project will give you all the tools you need to bring your own creative computer vision projects to life.Our project video shows off our in-browser prototype in action, describes why we did everything in the browser, shows off some vision-aware apps we built and mentions why we've come to kickstarter.The Kickstarter URL, which contains the video, listing of rewards, etc, is here:or our short versionThanks again,Tomasz