Apple FaceID Co-Inventor Launches AI Startup for Brain Diagnostics

Washington DC, United States Jul 15, 2026 ALN: The co-inventor of Apple’s FaceID and Vision Pro technology has embarked on an ambitious journey to revolutionize the field of cognitive diagnostics through artificial intelligence. Gidi Littwin, who played a pivotal role in the development of FaceID, has spent the last six years working on a cutting-edge AI model that aims to decode the electrical activity of the brain, potentially aiding in the diagnosis of various cognitive disorders.

Littwin's startup, Hemispheric, has successfully secured $52 million in funding, a significant milestone that underscores the growing interest and investment in AI-driven healthcare solutions. This funding comes on the heels of extensive data collection efforts, during which the company gathered brain activity data from 100,000 individuals. This data is crucial for training deep learning models that can analyze brain function without the need for invasive procedures, a significant advancement in the realm of medical diagnostics.

Leaving Apple in 2020 marked a pivotal change for Littwin, who was seeking new challenges and opportunities. His journey into the world of AI and brain diagnostics began when he connected with Hagai Lalazar, the co-founder of Hemispheric. Lalazar had already initiated the development of AI technologies aimed at studying the brain non-invasively and was in search of a partner who could bring a commercial perspective to the venture. After reaching out to approximately 75 candidates, he found in Littwin not only a collaborator but also someone with a wealth of experience in data collection and model training.

During his tenure at Apple, Littwin was involved in the development of technologies that required extensive data gathering. For instance, while working on the Vision Pro, he was tasked with compiling data from hundreds of thousands of subjects to train deep learning models for augmented reality applications. This experience proved invaluable as he transitioned to Hemispheric, where he recognized the necessity of similar large-scale data collection to build an effective AI model capable of interpreting brain activity.

Traditionally, diagnosing cognitive disorders such as depression, Alzheimer’s, and Parkinson’s has relied heavily on subjective assessments, including questionnaires and behavioral observations. This method can often lead to misdiagnoses or delayed treatment, highlighting a critical gap in the current diagnostic processes. To address this issue, Littwin and Lalazar focused on collecting what they refer to as their "most prized possession": a staggering quarter of a million hours of brain data from a diverse group of 100,000 paid volunteers. These volunteers participated in activities designed to resemble games, which simultaneously activated different regions of their brains, providing a rich dataset for analysis.

The culmination of this data collection effort has led to the development of a frontier AI model that interprets brain function by analyzing electrical activity within the skull. This process is analogous to how large language models deduce meaning from text through statistical analysis. To validate the model's effectiveness, the team conducted tests on various subsets of individuals, including those diagnosed with conditions such as PTSD, schizophrenia, and depression. The results were promising, with the model demonstrating a capacity to make accurate deductions about the brain health of these individuals.

Currently, the Hemispheric team is engaged in a clinical study aimed at testing the model's ability to diagnose and potentially predict the onset of Alzheimer’s disease, a condition that affects millions globally and poses significant challenges for early detection and treatment.

Looking ahead, Hemispheric plans to submit its first product, designed to assist in the study of PTSD, for FDA approval early next year. This step is critical as it paves the way for the potential rollout of their diagnostic tool to the public, with hopes of making it available by 2027. The product will utilize a lightweight EEG headset that patients will wear for approximately 15 minutes while interacting with an application on a tablet. This innovative approach aims to simplify the diagnostic process, allowing clinicians to decode brain signals and make informed decisions regarding treatment interventions and monitoring progress.

Lalazar envisions a future where this technology becomes as commonplace as blood tests in medical practice. He emphasizes that the device will be affordable and accessible, enabling widespread distribution across mental health clinics, hospitals, and even psychologists’ offices. This democratization of diagnostic tools could significantly enhance the way cognitive disorders are identified and treated, leading to better outcomes for patients.

In the broader context of healthcare, AI-assisted diagnostic tools are already making strides in various fields. For instance, AI technologies are currently in clinical use for diagnosing conditions like lung cancer, facilitating quicker access to treatment across Europe. The entry of major AI players such as OpenAI and Anthropic into the healthcare sector has intensified competition and innovation among startups, including Hemispheric, as they strive to carve out their niche in this rapidly evolving landscape.

Hemispheric's recent funding round has attracted interest from both American and Israeli venture capital firms, as well as individual investors, including notable figures like Howard Morgan, an early backer of Uber. The infusion of capital will support the company's efforts to forge partnerships with governments, healthcare organizations, and pharmaceutical companies, while also enabling them to expand their workforce in the United States. Additionally, the company aims to enhance its model by collecting further brain data from millions of individuals, which will contribute to refining the accuracy and efficacy of its diagnostic tools.

In tandem with their AI model, Littwin and Lalazar are also pursuing the development of their own brain scanners. They believe that these proprietary devices will yield more valuable data for their models compared to traditional EEGs. Littwin points out that existing EEG equipment was not originally designed for machine learning applications, particularly deep learning, and thus may not capture the full spectrum of information needed for advanced AI analysis.

The implications of Hemispheric's work extend far beyond the immediate goals of developing diagnostic tools. As the company progresses, it could play a crucial role in reshaping the landscape of mental health diagnostics, offering new hope for individuals suffering from cognitive disorders. By harnessing the power of AI and large-scale data analysis, Hemispheric aims to bridge the gap between technology and healthcare, ultimately leading to more accurate diagnoses, personalized treatment plans, and improved patient outcomes.

As the field of AI in healthcare continues to evolve, the success of startups like Hemispheric may inspire further innovations and collaborations that could transform the way we understand and treat cognitive disorders. The journey ahead is fraught with challenges, including regulatory hurdles and the need for rigorous clinical validation, but the potential rewards—both for patients and for the healthcare system as a whole—are significant.