Parasma Launches to Enable Human Brain Cells to Do Next-Token Prediction

Parasma, enabling biological compute with living neurons, led by Sean Cole, announced its public launch. The company is developing the algorithms and infrastructure for compute powered by human brain cells as an energy-efficient alternative to GPUs.

The work behind Parasma first entered public view earlier this year. In a project unveiled in late February, founder Sean Cole collaborated with Cortical Labs to train a culture of human neurons to play Doom.

Token Prediction.

Parasma’s system converts context words into electrical stimulation for human brain cells, measures their responses, and decodes those responses into tokens.

The cells achieved 90% accuracy on next-token prediction using full sentence context, significantly outperforming randomized controls. In a harder non-linear task, the cells reached 78.1% accuracy, exceeding the 75% ceiling of a silicon linear decoder.

The results suggest biological computing could offer new capabilities for language-based prediction beyond conventional silicon architectures.

What This Could Enable.

In the near term, Parasma will focus on repeatable benchmarks across cultures, devices, and time, while exploring richer contextual prediction and adaptive-control tasks.

Longer term, the company aims to develop programmable biological computing for applications requiring continual learning and high energy or sample efficiency, creating new model paradigms that could serve as alternatives to GPU-based computing.

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