Putting Their Foot Down: GOAT Uses AI to Stomp Out Fake Air Jordan and Adidas Yeezy Sneakers

The sneaker startup, which boasts more than 750,000 shoe listings, authenticates high-end kicks with image recognition AI.
by Scott Martin

Sneaker aficionados invest hundreds of dollars into rare Nike Air Jordans and the hottest Kanye West Adidas Yeezys. But scoring an authentic pair amid a crush of counterfeits is no slam dunk.

Culver City, Calif., startup GOAT (a nod to the sports shorthand for “greatest of all time”) operates the world’s largest sneaker marketplace that uses AI to stomp out fakes. The company offers a seal of authenticity for shoes approved for sale on its site.

Counterfeit sneakers are rampant online for some of the most sought after basketball brands.

“Yeezys and Jordans are now the most faked shoes in the world, and over 10 percent of all sneakers sold online are fake,” said Michael Hall, director of data at GOAT.

A pair of sought-after Kanye West Adidas Yeezys or Nike Air Jordans can easily set you back more than $300.

Pop culture interest in iconic shoes developed for sports stars and celebrity rappers is fueling instant sellouts in new releases. Meanwhile, there’s a heated aftermarket for the most popular footwear fashions as well as scarce vintage and retro models.

As a result, sneaker fans and novices alike are turning to a new wave of shoe sellers, such as GOAT, to ensure they’re getting getting an authentic pair of the most sought-after shoes.

GOAT pioneered the ship-to-verify model in the sneaker industry. This means that sellers can list any shoes on GOAT’s marketplace, but shoes that sell are first sent to the company for authentication by its image detection AI. If the shoes are found to be replicas or not as described, they don’t ship and buyers are given a refund.

Founded in 2015, GOAT’s business is booming. The startup, which has expanded to more than 500 employees, attracts more than 10 million users and has the largest catalog of sneakers in the world at 35,000 skus. This year, the company merged with Flight Club, a sneaker consignment store with locations in Los Angeles,New York City and Miami.

GOAT’s popular app and website — some users have sold more than $10 million in sneakers — has secured nearly $100 million in venture capital funding. The company is a member of NVIDIA’s Inception program, which offers technical guidance to promising AI startups.

AI to Kick Out Counterfeits

When you’re offering 35,000 unique styles, tracking down counterfeit sneakers is no small challenge. GOAT has teams of sneaker experts trained in the art of spotting replicas without AI. “They can spot a fake in like 10 seconds,” said Emmanuelle Fuentes, lead data scientist at GOAT.

Image recognition assists GOAT’s teams of authenticators and quality assurance representatives to ID and authenticate shoes in the warehouse. And the more GOAT’s experts provide helpful metadata to train the AI as they work, the better it helps all those vetting sneakers.

There’s a long list of data signals that are fed into a cloud instance of GPUs for the identification process and for training the network. GOAT’s convolutional neural networks are trained for anomaly and fraud detection.

GOAT, which has multiple neural networks dedicated to brands of sneakers, provides proprietary tools to help its authenticators upload data to train its identification networks.

GPUs Slam Dunk

Tracking and sharing expertise on so many models of high-end sneakers requires logging a ton of photos of authentic sneakers to help assist team members in handling shoes sent in for verification.

“The resolution that we are capturing things at and the scale that we are capturing the images — it’s a high-resolution, massive computational challenge requiring GPUs,” said Fuentes.

GOAT turned to NVIDIA TITAN Xp GPUs and NVIDIA Tesla GPUs on P2 instances of AWS running the cuDNN-accelerated PyTorch deep learning framework to initially train their neural networks on 75,000 images of authentic sneakers.

The company relies on the power of GPUs for identification of all of its sneaker models, Hall added. “For some of the most-coveted sneakers, there are more inauthentic pairs than real ones out there. Previously there wasn’t a way for sneakerheads to purchase with confidence,” he said.