Jeff Bezos Is Funding a Wild Hunt for the Brain’s ‘Core Algorithm’

With $500 million in funding and a reported $2.5 billion valuation, Flourish wants to reinvent AI by putting real neurons under the microscope.

Rob Williams knows how to pitch Jeff Bezos: You write a press release as if your product has already been built. Bezos reads it and gives a thumbs up or down.

Williams went through this process a lot as an executive on Amazon’s “S-team,” in charge of software products such as Alexa, until his departure last fall. But the pitch he made a few weeks later—in December 2025—was different. Now he was collaborating with Thomas Reardon, a neuroscientist and repeat startup founder, and approaching Bezos as a funder, not a boss.

Here’s what Bezos, sitting on his yacht somewhere, read while Williams anxiously watched on Zoom:

Flourish is a neuro AI company that is solving the two most difficult problems facing AI today: power efficiency and continuous learning. We are building Cortex AI, the first synthetic intelligence system designed to match the computational capacity, learning efficiency, and power budget of the human brain.

A month later, I’m lunching with Reardon and Williams in the Flatiron neighborhood in New York City. Reardon gets right to the point. AI has dug itself into a hole, he says. Though increasingly powerful, large language models are greedy consumers of computer power and data.

Though the inspiration for LLMs was rooted in biology, current frontier models have little in common with the human brain. A person uses about 20 watts of energy to process information; a single chip in an AI training cluster uses more than 30 times that amount. The hyperscalers require thousands of chips and gigawatts of energy, enough to power small cities. And those models need to suck up virtually all of what humans have written. Each new model requires more, more, more. For all of that, the models don’t learn. Once you train them, they’re stuck.

The goal, Reardon tells me, is to build “a synthetic artificial intelligence brain that runs on 50 watts or less.” It should adapt to its conditions, be as nimble as a human mind, and burn a tiny fraction of an LLM’s compute power and energy. The proof of concept is thriving inside our skulls. “There’s something fundamentally wrong with saying, ‘I need to basically read every book ever written 20 times over in order to learn English,’” Reardon says. “A human baby does it with a couple hundred thousand utterances.”

Reardon and Williams haven’t figured out yet how to build systems that match the magic of a human brain. What they have is a belief that an expert, well-resourced t