Better AI starts with living neurons.

We start where
AI hits its limits.

We identify a specific problem in an AI model, such as slow generation or high computing costs, and design an experiment to explore a better way to compute.

A chip beneath a culture of living neurons lets us send electrical signals and record how the network responds.

We turn video data into electrical signals.

We convert information from video into patterns of electrical stimulation. By changing those patterns, we can test how living neurons respond to different inputs.

We record how the neurons respond.

We measure how electrical activity moves through the network and changes over time. These recordings let us study how the neurons process information we send.

StimulatedResponding

We look for better ways to compute.

We compare the inputs with responses, looking for patterns in timing and how neurons interact. Those patterns can suggest new ways for an AI model to process information more efficiently.

StimulatedResponding

We turn discoveries into better AI models.

Our researchers turn promising findings into algorithms and test them in AI models. We compare each modified model with the original to see whether it works better, runs faster or uses less compute.

The neurons stay in our lab. What leaves is cheaper, faster, and better AI.

You get faster video generation at lower cost.

We build the improvements into a TBC video model that runs on existing AI hardware. That means less waiting, lower costs and more freedom to experiment and create.

*Comparisons against the original open-weight video model.