Neural Networks and Deep Learning by deeplearning.ai

But Seattle-based startup Algorithmia is aiming to make deep-learning algorithms from the foremost researchers accessible to anyone wanting to harness the technology. Algorithmia today is adding 15 deep-learning algorithms to its marketplace of roughly 2,000 callable APIs of all kinds, said Diego Oppenheimer, Algorithmia's founder and CEO. Algorithms are sets of rules or procedures used to solve a computing problem. Companies building apps might use the deep-learning algorithms to identify faces in a crowd, detect nudity or gore in images, colorize images, or recognize stress in a human voice. The company has also added access to the specialized computing needed to run the sophisticated algorithms.

When I arrived at a Stanford University auditorium Tuesday night for what I thought would be a pretty nerdy panel on deep learning, a fast-growing branch of artificial intelligence, I figured I must be in the wrong place--maybe a different event for all the new Stanford students and their parents visiting the campus. Despite the highly technical nature of deep learning, some 600 people had shown up for the sold-out AI event, presented by VLAB, a Stanford-based chapter of the MIT Enterprise Forum. The turnout was a stark sign of the rising popularity of deep learning, an approach to AI that tries to mimic the activity of the brain in so-called neural networks. In just the last couple of years, deep learning software from giants like, Facebook, and China's Baidu as well as a raft of startups, has led to big advances in image and speech recognition, medical diagnostics, stock trading, and more. "There's quite a bit of excitement in this area," panel moderator Steve Jurvetson, a partner with the venture firm DFJ, said with uncustomary understatement.

ARTIFICIAL INTELLIGENCE CAN do remarkable things, like recognize faces on social networks, instantly translate speech from one language to another, and identify commands barked into a smartphone. But it also can do stupid things, like label an African-American couple "gorillas." The artificial intelligence underpinning Google Photos did just that last year. The platform uses deep neural networks to identify images in your photo collection. These networks of hardware and software, modeled after the network of neurons in your brain, learn to recognize objects, animals, and faces by analyzing many millions of pre-labeled photos.