Most AI models stop learning once training ends. They can generate text, but they can’t evolve. I started wondering what would happen if they could.
Humans work differently. We replay experiences in our sleep, strengthening what matters and pruning what doesn’t. That cycle of reflection is what makes our learning continuous.
I wanted to see if a machine could do the same.
So I built Dream ML, a framework that gives AI models a kind of sleep cycle. During downtime, the model replays its own experiences with added entropy. It connects patterns that were never seen together, fine-tunes itself locally through LoRA adapters, and wakes up slightly changed.
Each dream cycle helps the model reorganize and deepen its internal representations.
This started as part of my project to build a local AI clone that learns from my data and runs fully on-device. It observes how I write, reason, and communicate, then improves through Dream ML cycles without ever sending data to the cloud.
mkmccarty3•3mo ago
Humans work differently. We replay experiences in our sleep, strengthening what matters and pruning what doesn’t. That cycle of reflection is what makes our learning continuous.
I wanted to see if a machine could do the same.
So I built Dream ML, a framework that gives AI models a kind of sleep cycle. During downtime, the model replays its own experiences with added entropy. It connects patterns that were never seen together, fine-tunes itself locally through LoRA adapters, and wakes up slightly changed.
Each dream cycle helps the model reorganize and deepen its internal representations.
This started as part of my project to build a local AI clone that learns from my data and runs fully on-device. It observes how I write, reason, and communicate, then improves through Dream ML cycles without ever sending data to the cloud.
Write-up and details in the linked essay.