Real-time learning.
AI should learn from every interaction. Corrections, follow-ups, changes in direction, and user behavior should help the system improve in real time.
Node 185 / Research Page Content
We build AI that understands people.
Today’s AI can understand language, but it still treats everyone largely the same.
We believe the next leap in AI will come from personalization: systems that learn from you, remember what matters, and improve through every interaction.
01 / Research
What we are solving.
For AI to become truly personal, it needs to learn continuously. We focus on four areas.
Persistent memory.
What the system learns should not disappear. We explore ways for AI to retain preferences, context, and learned behavior across conversations.
Model-centric systems.
Most AI products are built around code, with the model added at the end. We build systems where the model sits at the center.
Online evaluation.
A response can perform well on a benchmark and still be wrong for one person. We study how live behavior can help models understand what worked.
02 / How we work
Research depth. Consumer scale.
We are researchers and engineers who ship.
Every research direction is tested through live products used by millions of people. We learn through real-world experimentation, build quickly, and publish what we discover.
AI is becoming the interface for information, entertainment, education, and work. For it to genuinely serve people, it must be able to adapt to them.
We’re building personalized AI.