Addicted to A.I.
Mr. Ton-That, 31, grew up a long way from Silicon Valley. In his native Australia, he was raised on tales of his royal ancestors in Vietnam. In 2007, he dropped out of college and moved to San Francisco. The iPhone had just arrived, and his goal was to get in early on what he expected would be a vibrant market for social media apps. But his early ventures never gained real traction.
In 2009, Mr. Ton-That created a site that let people share links to videos with all the contacts in their instant messengers. Mr. Ton-That shut it down after it was branded a “phishing scam.” In 2015, he spun up Trump Hair, which added Mr. Trump’s distinctive coif to people in a photo, and a photo-sharing program. Both fizzled.
Dispirited, Mr. Ton-That moved to New York in 2016. Tall and slender, with long black hair, he considered a modeling career, he said, but after one shoot he returned to trying to figure out the next big thing in tech. He started reading academic papers on artificial intelligence, image recognition and machine learning.
Mr. Schwartz and Mr. Ton-That met in 2016 at a book event at the Manhattan Institute, a conservative think tank. Mr. Schwartz, now 61, had amassed an impressive Rolodex working for Mr. Giuliani in the 1990s and serving as the editorial page editor of The New York Daily News in the early 2000s. The two soon decided to go into the facial recognition business together: Mr. Ton-That would build the app, and Mr. Schwartz would use his contacts to drum up commercial interest.
Police departments have had access to facial recognition tools for almost 20 years, but they have historically been limited to searching government-provided images, such as mug shots and driver’s license photos. In recent years, facial recognition algorithms have improved in accuracy, and companies like Amazon offer products that can create a facial recognition program for any database of images.
Mr. Ton-That wanted to go way beyond that. He began in 2016 by recruiting a couple of engineers. One helped design a program that can automatically collect images of people’s faces from across the internet, such as employment sites, news sites, educational sites, and social networks including Facebook, YouTube, Twitter, Instagram and even Venmo. Representatives of those companies said their policies prohibit such scraping, and Twitter said it explicitly banned use of its data for facial recognition.