BATTLING GIANTS

Clarifai’s image-recognition ai can go toe-to-toe with those of google, IBM and Microsoft. now the startup must fight to stay competitive.

Clarifai’s image-recognition AI can go toe-to-toe with those of Google, IBM and Microsoft. Now the startup must fight to stay competitive.

In the summer of 2013, as Matthew Zeiler was close to finishing a PH.D. in artificial intelligence at New York University, he seemed to have every tech giant in the palm of his hand. Zeiler had left an internship with a Google AI group a few weeks earlier when he got a call from an unknown number while he was running along the Hudson River. It was Alan Eustace, then a senior vice president of engineering at Google, who had heard about Zeiler’s AI chops. Eustace wanted Zeiler to join permanently. To entice him, Eustace told him he would make an offer that was among the highest Google had ever made to a new graduate, Zeiler recalls. Zeiler won’t say how much he was offered, and Google declined to comment. But offers for top recruits with specific expertise can add up to several millions of dollars over four years, according to people with knowledge of the matter. Regardless, Google’s offer kicked off a bidding war for Zeiler and his knowhow in deep learning, the vaunted branch of AI that’s driving major breakthroughs in computing.

Within days, Zeiler received a bigger offer from Microsoft, which Google promptly matched. Apple also wanted to chat, and when Zeiler flew out to Silicon Valley, Mark Zuckerberg personally sought to persuade him to join a new AI research group at Facebook. Zeiler respectfully turned them all down, deciding instead to start a company with an audacious goal: to compete with the giants that were courting him. “It was a crazy period,” Zeiler remembers. “I had this low-risk opportunity of joining a tech giant versus doing my own startup.” Zeiler says he knew that some of his algorithms worked better than Google’s on certain AI problems. “I knew I had to follow my gut,” he says.

Four years later, Zeiler’s New York City-based startup, Clarifai, is widely seen as one of the most promising in the crowded, buzzy field of machine learning. Clarifai offers image- and video-recognition tools for developers that rival those from Google, Microsoft and others. Much as Stripe and Twilio make it easy for programmers to tap into payments and communications capabilities, Clarifai gives its customers access to cutting-edge AI techniques that would cost millions to replicate. Companies like Unilever, Buzzfeed, Ubisoft and Staples U.K., as well as makers of medical devices and drones, use Clarifai to automatically analyze millions of images and videos. One of the company’s 100 or so customers, i-nside, makes a smartphone accessory for imaging the inside of an eardrum and diagnosing ear diseases. Revenue, while still small, is expected to reach $10 million as early as next year, according to people close to the company.

That Clarifai has made it this far is, in and of itself, remarkable. In the past few years, AI— in particular a form of it called deep learning or deep neural networks—has emerged as the Next Big Thing in tech. Deep-learning techniques work loosely like the brain, with layers of “neurons” connected with “synapses.” The techniques are leading to substantial breakthroughs in areas like image and speech recognition, which in turn are ushering in advances in everything from medicine to self-driving cars to robotics.

But there’s a problem: Amid the scramble for talent, the richest companies in tech have consumed entire university departments and acquired just about every AI startup they could get their hands on. Google has been the hungriest, with at least 11 Ai-related acquisitions, spend-