Nearly two years ago, researchers from X, the experimental "moonshot factory" at Alphabet, sat down with the head of a food bank in Arizona to begin to better understand one of the conundrums of hunger in the U.S.: As much as 40% of the food supply is wasted, but millions of Americans don't have enough to eat. "We probably have two to four times as much food as we need in the world, but we're not doing a very good job of distributing it to people who really need it," says Emily Ma, the leader of the X team, called Project Delta, which announced today that two early tools it developed will be moving to Google to be fully built. The X team built a prototype of a new matching platform that could automatically consider ... the shelf life of donated food, how it's packaged, what transportation is available, and where it's needed and wanted. Another tool uses computer vision and machine learning to identify food as it's being thrown out so that a restaurant or supermarket deli can better plan future buying decisions to reduce waste: If you're throwing out a lot of onions every week, the software will alert you so you can stop buying as many. Eventually, similar technology could also be used to identify surplus food available for donations, so that information doesn't have to entered manually. "What we're looking to do is, in the automating of this, actually make food much more accessible to everyone," says Ma. "I believe that in the next 10 to 30 years, it is possible to actually almost perfectly match supply and demand," she says.