MyMind
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Introduction
Modulating behavior via subtle changes applied to one's ongoing visual feed may be a promising direction for noninvasive clinical and nonclinical interventions of human benefit. Such perturbations can be designed using our best AI models of visual processing in the human brain, and could potentially be delivered via low-latency augmented reality glasses, or by augmenting any otherwise screen-delivered visual stimulus. Our latest research shows that the leading models are now accurate enough to support applications of behavior modulation and neural control via nearly imperceptible visual input perturbations.
Problem
Anxiety and depression are at historic global highs, affecting hundreds of millions and placing a significant burden on individuals, health systems, and economies. Current standard-of-care treatments are primarily pharmaceutical, which, while effective for some, often come with limitations -- side effects, variable efficacy, long-term dependence, and limited personalization. Access to traditional therapy remains restricted by cost, availability, and stigma. There is an urgent, unmet need for noninvasive, accessible, and evidence-based interventions that can support mental health at scale -- empowering individuals to manage and improve their well-being without relying solely on medication.
Opportunity
We propose modulating behavior via subtle changes applied to one's ongoing visual feed as a promising direction for noninvasive clinical and nonclinical interventions of human benefit. Such perturbations can be designed using our best AI models of visual processing in the human brain, and could potentially be delivered via low-latency augmented reality glasses, or by augmenting any otherwise screen-delivered visual stimulus. Our latest research shows that the leading models are now accurate enough to support applications of behavior modulation and neural control via nearly imperceptible visual input perturbations.