Tom Brown, a senior executive at Anthropic, says a candid conversation with friends in 2014 set him on a path that would take him from conventional engineering to the frontlines of the global artificial intelligence race — through OpenAI and ultimately to the founding of one of AI's most closely watched safety-focused companies. Brown shared the account during a fireside chat with US Commerce Secretary Howard Lutnick in Chapel Hill, North Carolina.

The Conversation That Changed Everything

Brown recalled that friends approached him with a proposition that initially struck him as implausible: that machines could reach human-level intelligence within their lifetimes — potentially within the next 50 years. “A few of my friends came to me and they were like, ‘Tom, it seems like we might end up getting human level intelligence from AI within our lifetimes, so in the next 50 years,’” he said.

Despite his scepticism, Brown found the implications impossible to dismiss. “I was like, ‘Wow, that, like, seems kinda crazy, but if it does happen, like, that would be the biggest, most important thing that ever happens to humanity,’” he said. The exchange prompted him to reflect on what fundamentally defines human beings — and why a machine capable of replicating the mind would dwarf even the industrial revolution in consequence.

“The industrial revolution transformed all of society, but really it was, like, the second most important thing about humans is our bodies,” he said. “The main thing is our minds.”

From Engineering to Self-Study in AI

Persuaded by the argument, Brown stepped away from mainstream engineering and began teaching himself about artificial intelligence. “That got me to think, like, okay, maybe I’ll switch from engineering to try to help out learning about AI,” he said. “And so I did. I started doing kind of self study on that.”

OpenAI was founded roughly a year after Brown began his self-directed AI education. Already acquainted with several of the people involved, he reached out to explore whether he could contribute. “I went to see if I could help out in some way,” he said, adding that he joined as one of the first 20 employees to carry out engineering work.

The Scaling Laws Breakthrough That Accelerated Everything

A pivotal shift in Brown’s thinking came in 2019, when research into AI scaling laws examined how specific combinations of computing power, data volume, and model size governed a model’s capabilities. Until that point, researchers broadly understood that larger models with more compute tended to perform better — but the precise relationship remained opaque.

The scaling studies produced what Brown described as a recipe: a systematic method for determining “what exact combinations of compute, data, and model size resulted in a given level of intelligence.” The findings compressed his earlier timeline dramatically. What had seemed like a 50-year horizon suddenly looked far closer. “That gave us kind of the confidence that this stuff would continue to advance at the rapid rate that it has been, which ended up leading to the founding of Anthropic,” he said. The researchers concluded the breakthrough could arrive “not in 50 years but in, on the order of under 10 years.”

Anthropic’s Mission and Its OpenAI Roots

Anthropic was founded in 2021 by former OpenAI researchers, including siblings Dario Amodei and Daniela Amodei. The San Francisco-based company develops the Claude family of AI models and has positioned itself explicitly around safety and broad societal benefit. “Anthropic is focused on making sure that as we go through this very rapid kind of a, like, AI revolution, things go well for everyone,” Brown said.

This comes amid an intensifying global race in generative AI. OpenAI, established in 2015 as a research organisation, brought AI into mainstream public consciousness with the release of ChatGPT in late 2022, triggering a wave of investment and competition among technology companies developing advanced models. Anthropic is among the most prominent challengers in that field.

What This Signals for the AI Industry

Brown’s account underscores how a small circle of researchers, galvanised by a shared conviction about AI’s trajectory, seeded two of the most influential companies in the field. The scaling-laws research he referenced has since become foundational to how the industry thinks about model development and resource allocation. As AI capabilities continue to accelerate, the question of whether safety-first organisations like Anthropic can keep pace — and keep the technology’s risks in check — remains one of the defining challenges of the decade.