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Pakko De La Torre // Creative Director

What's Your NFT Really Worth? This Man Is Using AI to Find Out

What’s Your NFT Really Worth? This Man Is Using AI to Find Out

The sentiment – that technology can inform and even outperform human capabilities – is at the heart of Yakovenko’s life work, and has taken him around the world for poker tournaments, chess competitions and now, non-fungible tokens (NFTs).

His latest mission is to tame the Wild West of blue-chip NFT prices with an artificial-intelligence startup he founded called DeepValueNFT, which uses a pricing algorithm to assess the market value of high-priced digital collectibles like CryptoPunks and Bored Apes. (Both are collections of 10,000 computer-generated profile pictures, each with their own sets of traits and rarities.)

While NFTs from these collections have fetched millions of dollars in individual sales on NFT marketplaces (the cheapest price for a CryptoPunk with the “alien” trait is listed at over $12 million), buyers remain on their own in determining a fair price for their treasures. Even with the NFT market cooling off in recent months as part of a broader crypto downturn, Yakovenko sees this as a problem worth solving.

At 16, he became a full-time student at the university, taking graduate-level math courses and discovering the game of poker in the dorm rooms, later becoming a regular at higher-stakes games at an off-campus fraternity.

Yakovenko’s poker career began to blossom years later in New York City, where he lived during and after graduate school at Columbia University’s school of engineering and applied science, taking a full-time job at Google as an engineer on the company’s search engine team in 2006.

Yakovenko’s poker career eventually took him to more esteemed settings like the World Series of Poker, but his most interesting games came in the underground contexts, including a stint at an infamous table run by Molly Bloom (whose story was turned into the film “Molly’s Game”) that regularly hosted high-profile celebrities, most notably Tobey Maguire.

The findings of his studies, the most consequential being that it was beneficial for pitchers to throw harder (a seemingly obvious observation that was still contested at the time), led to ongoing consulting gigs with Driveline through the years, contributing in small part to the early days of a larger analytical revolution that has since changed the game of baseball significantly.

He recalled a moment during Tech Week Miami where he would pull up the sale bot while riding in Ubers, asking people how much they thought each Punk was worth, trying to make sense of the discrepancies between “floor” Punks with common traits and rarer editions.

After playing around with the model for a few months in his spare time, he founded DeepValueNFT, a company that offered just that service. The model’s current specialty is CryptoPunk prices, but Yakovenko and his team members plan to roll out a Bored Ape Yacht Club price predictor in the coming weeks. The company just raised a $4 million funding round announced on Thursday.

Users of the website can search for any individual NFT in the available collections, see their valuation history alongside its bids, offers and sales. The company also has a Twitter bot that sends out alerts for notable listings alongside real-time price estimates.

The model’s strength is that it looks at data beyond just sale prices, which on their own are a poor measure of an NFT’s value. More important than sales are the prices for active bids and listings, Yakovenko says. While a sale price determines how much a buyer was willing to pay for an NFT, listings that go untouched are equally telling for how much they aren’t willing to pay.

Yakovenko’s journey into NFTs is in many ways emblematic of the industry’s eclectic nature. NFTs, now just a few years old, aren’t a subject you study in school, and their attraction has taken most market participants by surprise. The type of people NFTs attract, too, have some commonalities – they’re comfortable with taking risks, albeit calculated ones.

This content was originally published here.