Our end-to-end approach
From data collection, preprocessing, to machine learning, we develop the entire BCI stack in-house.
State of the Art Results
Our methods have already achieved state of the art EEG reconstruction accuracy. These are just early results on our baseline models and datasets; we are developing much larger improvements that we will soon release.
The Interface of the Future
By decoding neural signals in an interpretable way, we can unlock a wealth of possibilities. These can include:
Groundbreaking Research
We have pioneered research in the field of neural decoding. We made the largest datasets and trained state-of-the-art models for brain decoding. Applying these breakthroughs to EEG, we are excited to achieve orders of magnitude performance improvements for consumer level neural-decoding.
MindEye2
MindEye2 introduces a multi-subject architecture that can train 40 times faster than the previous state-of-the-art model while maintaining the same performance
Our Team
We are a world-class group of researchers in neural decoding and machine learning. We have previously worked at various top institutions.
Scientific Advisory Board
Backed by Leading Experts in Neuroscience and AI
Dr. Thomas Naselaris
Associate Professor, Department of Neuroscience at the University of Minnesota
Dr. Paul Scotti
Head of NeuroAI at Stability AI, Ph.D. in Cognitive Neuroscience from Ohio State University
Dr. Tanishq Mathew Abraham
Board Director at Stability AI, CEO of MedARC, Ph.D. in Biomedical Engineering from the University of California, Davis
We`re using machine learning, software engineering, and neuroscience to build the next generation of brain computer interfaces. If you are excited about meaningful work in these areas, we are actively hiring!
Reach us at [email protected].
