The magazine estimates Chen’s net worth at $18 billion, which stems from the value of his firm.
Edwin Chen, CEO and founder of Surge AI. Screenshot from Youtube/20VC with Harry Stebbings
Launched in 2020 by Chen without external funding, Surge now works with more than one million contractors, by his count, supplying high-quality datasets to clients including Google, Anthropic and OpenAI.
Similar to Scale AI, founded by the world’s youngest self-made billionaire Alexandr Wang, Surge has ridden the wave of tech giants and big startups rushing to train artificial intelligence models to quickly become one of the top-earning data-labeling firms worldwide.
What set Surge apart was its focus on markets that others overlooked. While rivals began with simpler labeling tasks such as marking stop signs for self-driving cars, Chen chose to concentrate on more complex and specialized projects instead.
“Early customers were people in either the search space, the organic recommendation space, the content moderation space,” Inc. magazine quoted Chen as saying.
The firm carved out its dominant position through a mix of sharp financial decisions and a platform that matches data-labelers with projects best suited to their expertise.
“We think of ourselves as a research company, but the research we focus on is understanding human data and its applications,” Chen says.
Chen, who studied math, computer science and linguistics at the Massachusetts Institute of Technology (MIT), came up with the idea for the startup during his stints as a machine-learning engineer at Facebook, Dropbox, Google and Twitter, according to The Information.
At Facebook, he was tasked with building recommendation and search algorithms and helping source the data needed to train them. Yet despite the firm’s deep pockets, Chen often ran into challenges.
To train the system to distinguish between businesses, like differentiating a grocery store from a restaurant, for instance, a dataset of 50,000 accurately labeled businesses is needed.
Chen recalled that an outside firm took six months to deliver the dataset.
But when the data finally arrived, it was riddled with mistakes, such as restaurants being labeled as coffee shops and coffee shops as hospitals. The lack of quality training data for AI frustrated Chen.
“Really high-quality data is critical to the future of AI and AGI,” he says.
That belief has shaped Surge’s approach, which charges two to five times more than rivals like Scale but backs it up with a reputation for industry-leading work.
Clients appear to agree. An executive at a major tech firm that has worked with Surge once described it as “boring in the best possible way—they just do a good job.”
Surge is in discussions for its first external fundraising, according to a source cited by Bloomberg.
It reportedly seeks about $1 billion at a valuation of at least $25 billion. Such a deal would rank Surge among the most highly valued startups in the U.S.
Outside of matters related to his business, Chen tends to stay out of the spotlight, with his only trace online a long-dormant Medium blog filled with technical musings.
Even when he appears in interviews with the media, the focus of such discussions mostly revolves around Surge or the future of AI.
When he was honored by Time as one of the 100 most influential people in AI late last month, Chen said he imagines a future where AI could achieve feats as grand as Nobel Prize-winning poetry, solving the Riemann hypothesis, or even uncovering the universe’s deepest secrets—but only if it is trained on data that reflects human knowledge, creativity and values.
“We want AI to not just be this cold robotic thing that solves a bunch of math questions,” he told the magazine, adding that a well-built AI would feel “rich and warm and creative” and capable of interacting in an “inherently human” way.
He also sees the arrival of generally intelligent or even superintelligent systems as an inevitability. “They are going to be our descendants,” he said. “Like humanity’s children.”