Who are the architects of AI, and what are the ties that bind them?

The world’s most consequential artificial intelligence research is being conducted by a strikingly small circle of scientists who studied mostly under the same mentors, taught in the same rooms and kept recruiting from each other’s labs.

To understand where AI is going, one needs to understand a simple fact: Virtually every major breakthrough of the past 15 years traces back to five or six key figures and three institutions: Stanford University, Massachusetts Institute of Technology and the University of Toronto.

No surprise then that the AI world is deeply interconnected, with Google DeepMind, OpenAI and Stanford/MIT featuring as the primary hubs for the current generation of AI leaders, with close, often fluid, talent flows. The connections among top AI founders and leaders are built on shared academic backgrounds, research collaborations and moves between major labs.

The PayPal parallels

After eBay acquired PayPal in 2002, a close-knit group of former PayPal founders and employees — that included Peter Thiel, Elon Musk and Reid Hoffman — went on to found or fund many of Silicon Valley’s most influential companies. Their ventures include YouTube, LinkedIn, Tesla, Yelp, SpaceX and Palantir.

OpenAI was founded by Elon Musk, Altman, Ilya Sutskever, Greg Brockman, Wojciech Zaremba and John Schulman. Thiel was the main backer and mentor of Sam Altman, providing the large part of the $5 million that made up Altman’s initial venture fund. When OpenAI launched in 2015, Thiel was one of the founding investors pledging $1 billion.

The most notable startups founded by OpenAI alumni include brother-sister duo Dario Amodei and Daniela Amodei of San Francisco-based Anthropic. The siblings left OpenAI in 2021 to form their own startup that has a focus on AI safety. Anthropic has rapidly grown to become OpenAI’s biggest rival. OpenAI co-founder and chief scientist Ilya Sutskever left OpenAI in May 2024 after he was reportedly part of a failed coup to replace CEO Sam Altman.

Shortly afterward, Sutskever co-founded Safe Superintelligence. Mira Murati, OpenAI’s CTO, left OpenAI last year to found, Thinking Machines Lab, which emerged in February 2025. Aravind Srinivas worked as a research scientist at OpenAI for a year until 2022, when he left the company to co-found AI search engine Perplexity.

Google DeepMind is a major “founder factory” in the AI industry, with over 200 former employees having gone on to establish their own startups, with OpenAI coming in a close second. Its co-founder, Mustafa Suleyman, is now CEO of Microsoft AI.

Intellectual mentorship

The intellectual godfathers of deep learning include Geoffrey Hinton (University of Toronto/Google), LeCun (New York University/ex-Meta) and Yoshua Bengio (Universite de Montreal). They all won the Turing Award in 2018 for conceptual and engineering breakthroughs that made deep neural networks a critical component of computing.

Hinton’s students include Sutskever (OpenAI/Safe Superintelligence) and Alex Krizhevsky (AlexNet). LeCun, Meta’s chief AI scientist until January this year, was in fact a postdoctoral researcher under Hinton.

After the success of AlexNet, Hinton, Sutskever and Krizhevsky formed a company to commercialise their work. In 2013, Google acquired that company for $44 million and hired all three.

Hinton stayed at Google Brain for the next decade while maintaining his faculty position at the University of Toronto. Sutskever worked at Google Brain for a few years before co-founding OpenAI in 2015. Krizhevsky eventually left Google to work at startups before becoming a research advisor at various AI companies.

Now consider Andrew Ng. He founded Google Brain in 2011, the research division that spawned countless AI leaders. He was chief scientist at Baidu, where he built an AI group of 1,300 people. He co-founded Coursera, which has taught millions of people machine learning. He continues to teach at Stanford as an adjunct professor. And, critically, he has been a post-doctoral adviser, collaborator and mentor to many of the field’s rising stars.

In 2012, Sutskever spent time with Ng as a postdoc after completing his PhD at Toronto under Hinton. That brief connection mattered. When Sutskever went on to co-found OpenAI in 2015, he carried the intellectual legacy of both Hinton and Ng. Ng has also taught Sam Altman, the co-founder of OpenAI, at Stanford.

At Stanford, Fei-Fei Li created ImageNet — the massive dataset of 14 million labelled images that made AlexNet possible. Without her dataset, Hinton’s work at Toronto wouldn’t have had the fuel it needed. She was also the PhD advisor of computer vision expert Andrej Karpathy. He interned at Google Brain (2011), Google Research (2013), and DeepMind (2015) — gaining exposure to the world’s three largest AI research operations. When he graduated in 2015, he joined OpenAI as a founding member. He left the company to join Tesla in 2017 to lead its autopilot program. Karpathy is also well-known for his YouTube videos explaining core AI concepts. He left Tesla in 2024 to found Eureka Labs, a startup that is building AI teaching assistants.

The AI funding cycle

AI funding over the past 5 years has seen multi-billion dollar rounds, with a big portion of capital coming from a mix of big tech players, or hyperscalers, and private equity firms. Microsoft is one of the largest backers, with a multi-billion dollar partnership with OpenAI and investments in Anthropic and Anysphere. Chipmaker Nvidia has been a major investor across the downstream AI ecosystem, with equity exposure to Anthropic and Anysphere. Google and Google Ventures have invested in Anthropic and AI21 Labs, while Meta has invested in Scale AI. Amazon has backed Anthropic and has invested in robotics player Figure AI.

Among funds, SoftBank had led a massive $40 billion investment into OpenAI in 2025, even as Andreessen Horowitz has investments in OpenAI and Mistral AI. Y Combinator is another major player in early stage funding of startups. These interlinked funding plans have now catalysed an industry-wide term — circular trading — that is being attributed to the AI bubble. This comes amid a pickup in large partnership announcements across AI model developers, hyperscalers and chip companies.