EASY Residency(@EASYResidency):Most market simulators rely heavily on historical data and handcrafted assumptions. By the time the model is deployed, market behaviour may already have changed. @De1_ai is building a financial world model that learns from live execution: > Real-capital execution provides continuous feedback, allowing the model to refresh daily > Aggregated order flow across the network expands the learning set beyond its own trades The team reports $800M+ in daily volume across 200+ institutions, 1,000+ liquidity sources, and 40+ chains. Its reinforcement-learning trading system has also processed more than $400B in client flow. Catch De1 at EASY Residency S4 Demo Day.

2026.09.08 12:30

Most market simulators rely heavily on historical data and handcrafted assumptions. By the time the model is deployed, market behaviour may already have changed. @De1_ai is building a financial world model that learns from live execution: > Real-capital execution provides continuous feedback, allowing the model to refresh daily > Aggregated order flow across the network expands the learning set beyond its own trades The team reports $800M+ in daily volume across 200+ institutions, 1,000+ liquidity sources, and 40+ chains. Its reinforcement-learning trading system has also processed more than $400B in client flow. Catch De1 at EASY Residency S4 Demo Day.

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