This is a benchmark of our model from an evaluation published a week ago. Since then, the models have undergone another training phase focused on applying physics and mathematical reasoning to real-world environments. The launch date is currently redacted. We have been working through multiple training and evaluation cycles and are seeing some interesting results. A quantized version of the model will also be open sourced.

Tuesday is for trading on testnet. This is how it feels to be in the testnet chat. Join here: t.me/+8RKMPylZnnlhZTMx

Another massive launch happening today on @HyperliquidX powered by @sedaprotocol

Hmm. Maybe we should turn off inflation? Make SEDA purely deflationary.

Introducing P37 Neuro, our open-source robot brain at @OntosWorld. For a while, we’ve been working on a question: Can we build a robot brain that keeps working when the body or task changes? P37 Neuro is part of our answer. The system is designed to understand the body it controls, interpret the state of the robot and its environment, follow a task or demonstration, and turn that information into physical actions. A new robot or task shouldn’t always require a completely new model. P37 has an embodiment layer that represents the robot itself, high- and low-level policies for planning and control, and memory that carries context across actions and failures. It also supports reinforcement learning, simulation in MuJoCo and Isaac Lab, and a C++ runtime that connects the learned policy to the physical machine. Around the model, we’ve built the infrastructure for training, evaluation, safety, model releases, fleet feedback, and rollback. The current software path covers P37-E0 through E6. We’ve begun testing the ideas behind the system. A shared model has been trained across different synthetic robot morphologies and evaluated on bodies it had never encountered during training. We’ve also tested demonstration conditioning on unseen tasks, with no fine-tuning during evaluation. For the memory tests, we gave the model information before a simulated failure, then compared its performance when that memory was preserved and when it was removed.

$5.2B needed by EOD tomorrow + 1 new partners API missing from the count. More projects. More data requests. More burn.

Calling SEDA's first $50B powered by EOW. base:0x306acd0c07c430abbbb2e74ef7bde94f32a898c0 burn up, volume up, OPs up.