March 13, 2016. Game 2. Move 37.
AlphaGo made a move that no human would ever make. Go masters called it "beautiful" and "incomprehensible." It was a glimpse into the future where AI could discover what humans have not yet imagined.
AI got superhuman at Go because it had a perfect training environment to practice millions of games. But for the world's most critical engineering challenges, those environments don't exist. The most valuable engineering knowledge isn't documented anywhere. It's experiential: the intuition to debug a failing chip, the workflow that optimizes complex systems, the trial-and-error process that gives researchers taste.
Frontier models can't learn semiconductor design from the internet because the knowledge lives in the heads of the few thousand engineers who've spent decades mastering these domains. To automate these industries, someone has to extract this knowledge and build a bridge between these domains and frontier labs.
Phinity distills expert engineering workflows into RL environments, focusing on the engineering disciplines across hardware, AI, mechanics, and manufacturing, giving AI the training grounds it needs to master the skills that reshape civilization.
Today, we are building the training grounds for a much bigger Move 37.
That move won't be played on a 19×19 board.
It will be the semiconductor breakthrough that extends Moore's Law another decade. The manufacturing innovation that cuts global production costs in half. The materials discovery that unlocks room-temperature fusion.
And just like the original Move 37, when it happens, it will seem incomprehensible.
Our founders have helped train 340B+ parameter models at large foundation model labs, built specialized models and agents for chip design, healthcare, retail, and compliance.
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