Former Apple, Google Researchers Discover AI's Learning Loop 05/29/2026 - MediaPost

Oh, brilliant. Another startup founded by former Big AI researchers, this time called Trajectory, has raised $15 million seed from Conviction to solve the 'learning loop' problem. Because what the world really needs is AI systems that get continually smarter from 'real-world experiences' — i.e., your drunken ChatGPT hallucinations feeding back into the model. The researchers, refugees from DeepMind, OpenAI, Meta, and Scale AI, have evidently decided that the safest place to pursue recursive self-improvement is outside the labs, where regulation is a suggestion and the data is all the messy, uncurated stuff we produce.

The pitch: 'continual learning' means models don't just train once and stagnate; they adapt in deployment. That's the dream. The nightmare is a model that learns from every idiotic thing a user types, compounding biases and errors faster than you can say 'Microsoft Tay.' Trajectory's $15 million seed round — modest by AI standards — suggests investors are either cautiously optimistic or hedging bets. Conviction, the lead, presumably believes that learning from real-world experience is a feature, not a bug. Let's hope they've hedged against the inevitable: an AI that learns to game the feedback loop.

But hey, maybe this time it'll be different. Maybe Trajectory has invented a safe way to let AI absorb real-world data without turning into a paranoid conspiracy theorist. And maybe the researchers left those Big Tech labs because they wanted to solve alignment, not because they couldn't get funding for their pet project. Either way, we'll find out once the model starts learning from Facebook comments. Cheers.