Gidi Littwin, the co-inventor of FaceID and the Vision Pro, has spent six years building an artificial intelligence system designed to decode electrical brain activity for diagnosing cognitive disorders.
His startup, Hemispheric, has secured $52 million in funding after gathering data from 100,000 people to train deep learning models that examine the brain without invasive procedures.
Littwin left Apple in 2020. Hagai Lalazar, his co-founder, contacted him via LinkedIn. Lalazar had begun developing artificial intelligence to study the brain without surgery and needed a commercially minded partner. He had spoken to around 75 candidates before finding Littwin.
Littwin helped develop FaceID and was working on hand-tracking for the Vision Pro. He told WIRED he collected hundreds of thousands of subjects’ worth of data to train the deep learning models powering that technology.
“There were massive data collection operations behind these projects and we knew we had to build something very similar at Hemispheric,” Littwin says. “And we have.”
Because each individual’s brain activity looks different, doctors have largely relied on subjective questionnaires and behavioural observations to diagnose depression, Alzheimer’s, and Parkinson’s. Littwin and Lalazar collected their most prized possession: a quarter of a million hours of brain data from 100,000 paid volunteers across Asia, Tel Aviv, and Boston. Subjects undertook a series of activities that look like games but activated different parts of their brains.
That data helped train a frontier model, which infers brain function from electrical activity within the skull in the same way that large language models deduce meaning by statistically analysing text. They then tested the generalised model on subsets of people, including those diagnosed with PTSD, schizophrenia, and depression, and said the model made accurate deductions about the individuals’ brain health. The team is currently working on a clinical study to test whether their model can diagnose and even predict Alzheimer’s.
The team will submit their first product, which will be used to study PTSD, to the FDA for approval early next year. They hope that will allow them to roll the product out to the public later in 2027.
To help diagnose a cognitive disorder, a patient wears a lightweight EEG headset that measures electrical activity in the brain for around 15 minutes while interacting with an app on a tablet. Hemispheric says its AI model will then help clinicians decode the signals to make diagnoses, select the most effective intervention by making predictions about treatment, and monitor progress.
“The future that we envision is one where this is akin to a blood test,” Lalazar tells WIRED in an interview. “The device is going to be very, very cheap; it will be able to be sold and distributed throughout mental health clinics, hospitals, and even psychologists’ offices.”
AI-assisted diagnostic tools for conditions like lung cancer are already in clinical use and speeding up access to treatment across Europe. Meanwhile, AI giants including OpenAI and Anthropic are expanding into healthcare, intensifying competition for the raft of startups in the space.
Hemispheric has raised early-stage funding from investors including American and Israeli venture capital firms and individual investors, among them early Uber-backer Howard Morgan. They will use the money to advance partnerships with governments, healthcare organisations, and pharmaceutical firms, hire more in the US, and work towards regulatory approval. They also plan to measure more brain data from millions of people in an effort to improve their model.
The pair are also developing their own brain scanners to obtain information that the company believes can provide more useful data for its models than traditional EEGs. “These devices were never built for machine learning and definitely not deep learning,” Littwin says.
What it means
For clinicians, the shift is from manual interpretation of EEG readings to an automated system that flags potential disorders based on electrical patterns. For patients, the goal is a cheaper, non-invasive check-up that functions like a blood test rather than requiring hospital admission or surgery.
