A photo shared on X by Alexandr Wang, Meta’s chief AI officer and Scale AI co-founder, has drawn attention to an unusually concentrated network of former quantitative-trading interns who have gone on to lead major companies across artificial intelligence, software development and crypto markets.
The image showed Wang with Scott Wu, co-founder and chief executive of AI coding company Cognition, and Jeff Yan, founder of decentralized derivatives platform Hyperliquid. Wang’s caption referred to their time at Hudson River Trading, the quantitative trading firm where the three were members of its first internship cohort roughly a decade ago.
Their careers have since diverged into distinct corners of technology, but the shared HRT background connects founders behind some of the sector’s most closely watched private companies. Wang entered Meta through its $14.3 billion purchase of a 49% stake in Scale AI in June 2025; Wu’s Cognition reported a $48 billion valuation after its latest financing; and Yan built Hyperliquid as a self-funded crypto trading venue following the collapse of FTX.
From quantitative trading interns to startup founders
Hudson River Trading has long recruited heavily from elite mathematics, computer-science and programming-competition circles. Its early internship group appears to have become an unusually productive founder network rather than simply a pipeline into proprietary trading.
Wang, who was born in Los Alamos, New Mexico, in 1997, left the Massachusetts Institute of Technology in 2015 before co-founding Scale AI. The company built data-labeling systems used in training artificial intelligence models, including tools for computer vision and audio transcription. Scale AI was valued at $7.3 billion in 2021, when Wang’s reported 15% stake put his estimated wealth above $1 billion.
Meta’s 2025 transaction gave the social-media company a substantial minority holding in Scale AI and brought Wang into Meta to lead its Superintelligence Labs. The arrangement placed a founder with experience building AI-data infrastructure at the center of Meta’s effort to develop frontier models, while Scale AI continued as a separate company.
Wu, also born in 1997, came from a more visibly competitive-programming background. He won three gold medals at the International Olympiad in Informatics, or IOI, and took first place in 2014 with a perfect score. While at Harvard, he was part of a team that won gold at the 2016 International Collegiate Programming Contest and ranked third overall.
After working on the social-networking startup Lunchclub, Wu co-founded Cognition in 2023 with Steven Hao and Walden Yan. Cognition introduced Devin in 2024, presenting the product as an autonomous AI software engineer capable of writing, debugging and deploying code.
Cognition said in September that it had raised more than $2 billion in a Series E round led by Andreessen Horowitz and Accel, valuing the company at $48 billion after the financing. That valuation reflects the intense competition around AI systems designed to automate parts of software engineering, a market where companies are selling the prospect of reducing the time required to turn product ideas into functioning code.
Hyperliquid took a different route
Yan’s path followed the same early quantitative-training environment but led toward decentralized financial infrastructure. Two years older than Wang and Wu, Yan studied at Harvard on a full scholarship and participated in HRT’s first winter internship program, a three-week course with 10 places. According to the account of that program, Yan and Wu finished first and second in the contests held during the internship.
Yan began Chameleon Trading in late 2019 with $10,000 in starting capital. Following the 2022 FTX collapse, he and his team began developing Hyperliquid, a crypto derivatives platform built on its own Layer 1 blockchain rather than deployed on a general-purpose network.
That design gave Hyperliquid more direct control over transaction processing and trading functions. A derivatives exchange needs to handle rapid order placement, cancellation, matching and liquidations, which can be difficult and costly on chains designed primarily for broader application use. Building an in-house chain gives the platform greater room to optimize for those operations, while also placing the technical and operational burden on a relatively small team.
The supplied account said Hyperliquid was developed without outside venture funding and operated with more than 10 people. It also said the platform’s team generated more than $900 million in profit during 2025. The figures were not accompanied by audited financial statements in the material provided, though the platform’s growth has made it a prominent example of a crypto project seeking to combine exchange-style performance with on-chain settlement.
Hyperliquid’s HYPE token distribution also became a major event for early users. Token airdrops can transfer ownership to traders and other participants instead of concentrating it solely among outside funders, though the eventual value of those allocations depends on market prices and token-unlock structures.
A network extending beyond three founders
The same HRT and programming-competition circle includes Jesse Zhang, founder and chief executive of AI customer-service company Decagon. Zhang was also part of the 10-person HRT intern group and was born in 1997. Decagon announced a $250 million Series D financing in January at a $4.5 billion valuation.
Aravind Srinivas’s Perplexity is linked to the wider competitive-programming network through co-founder and chief strategy officer Denis Yarats, described in the source material as a Harvard alumnus and three-time IOI gold medalist who won first place in 2012 with a perfect score. Reports in August said Nvidia was considering an investment in Perplexity at a valuation of about $30 billion, though no transaction was confirmed in the material provided.
Cognition also reflects the overlap between this network and Scale AI. Hao, Cognition’s co-founder and chief technology officer, is an MIT mathematics graduate and IOI gold medalist who previously worked with Wang at Scale AI before joining Wu to build Cognition.
The photo therefore captures more than a reunion of former interns. It traces a founder network shaped by algorithmic trading, Olympiad-style problem solving and elite computer-science training, now spread across AI infrastructure, autonomous coding tools and crypto-market architecture. Those fields demand different products and business models, but each rewards the ability to turn difficult technical systems into fast, scalable software.
From HRT interns to crypto leaders—explore how derivatives work and shape markets in this in-depth guide today.
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