Archive for June, 2018

TechCrunch’s Startup Battlefield is coming soon to Beirut, São Paolo and Lagos

Everyone knows there are thriving startup communities outside of obvious hubs, like San Francisco, Berlin, Bangalore and Beijing, but they don’t always get the support they deserve. Last year, TechCrunch took a major page from its playbook, the Startup Battlefield competition, and staged the event in Nairobi, Kenya to find the best early stage startup in Sub-Saharan Africa, and also to Sydney, Australia, to find the same for Australia and New Zealand. Both were successes, thanks to talented founders and the hard traveling TechCrunch team. And now we’re pleased to announce that we’re stepping up our commitment to emerging ecosystems. TechCrunch is once again teaming up with Facebook, our partner for last year’s Nairobi event, to bring the Startup Battlefield to three major cities representing regions with vital, emerging startup communities. In Beirut, TechCrunch’s editors will strive to find the best early stage startup in the Middle East and North Africa. In São Paolo, the hunt is for the best in Latin America. And in Lagos, Nigeria, TechCrunch will once again find the top startup in Sub-Saharan Africa. Early stage startups are welcome to apply. We will choose 15 companies in each region to compete, and we will provide travel support for the finalists to reach the host city. The finalists will also receive intensive coaching from TechCrunch’s editors to hone their pitches to a razor’s edge before they take the stage in front of top venture capitalists from the region and around the world. Winners will receive $25,000 plus a trip for two to the next TechCrunch Disrupt event, where they can exhibit free of charge, and, if qualified, have a chance to be selected to participate in the Startup Battlefield competition associated with that Disrupt. In the world of founders, the Startup Battlefield finalists are an elite; the more than 750 Startup Battlefield alums have raised over $8 billion and produced 100+ exits to date. What are the dates? They will be finalized shortly but Beirut is on track for early October, São Paolo for early November, and Lagos in early December.  In the meantime, founders eager start an application for one of these Startup Battlefields may do so  by visiting apply.techcrunch.com . Look for more details next week. Interested in sponsoring one of the events? Email us at [email protected]

Facebook’s new AI research is a real eye-opener

There are plenty of ways to manipulate photos to make you look better, remove red eye or lens flare, and so on. But so far the blink has proven a tenacious opponent of good snapshots. That may change with research from Facebook that replaces closed eyes with open ones in a remarkably convincing manner. It’s far from the only example of intelligent “in-painting,” as the technique is called when a program fills in a space with what it thinks belongs there. Adobe in particular has made good use of it with its “context-aware fill,” allowing users to seamlessly replace undesired features, for example a protruding branch or a cloud, with a pretty good guess at what would be there if it weren’t. But some features are beyond the tools’ capacity to replace, one of which is eyes. Their detailed and highly variable nature make it particularly difficult for a system to change or create them realistically. Facebook, which probably has more pictures of people blinking than any other entity in history, decided to take a crack at this problem. It does so with a Generative Adversarial Network, essentially a machine learning system that tries to fool itself into thinking its creations are real. In a GAN, one part of the system learns to recognize, say, faces, and another part of the system repeatedly creates images that, based on feedback from the recognition part, gradually grow in realism. From left to right: “Exemplar” images, source images, Photoshop’s eye-opening algorithm, and Facebook’s method. In this case the network is trained to both recognize and replicate convincing open eyes. This could be done already, but as you can see in the examples at right, existing methods left something to be desired. They seem to paste in the eyes of the people without much consideration for consistency with the rest of the image. Machines are naive that way: they have no intuitive understanding that opening one’s eyes does not also change the color of the skin around them. (For that matter, they have no intuitive understanding of eyes, color, or anything at all.) What Facebook’s researchers did was to include “exemplar” data showing the target person with their eyes open, from which the GAN learns not just what eyes should go on the person, but how the eyes of this particular person are shaped, colored, and so on. The results are quite realistic: there’s no color mismatch or obvious stitching because the recognition part of the network knows that that’s not how the person looks. In testing, people mistook the fake eyes-opened photos for real ones, or said they couldn’t be sure which was which, more than half the time. And unless I knew a photo was definitely tampered with, I probably wouldn’t notice if I was scrolling past it in my newsfeed. Gandhi looks a little weird, though. It still fails in some situations, creating weird artifacts if a person’s eye is partially covered by a lock of hair, or sometimes failing to […]