Adaptive Intelligence With Digital Brains
AI that learns, understands, and interacts with the world like the brain
Our mission
We build AI with Adaptive Intelligence that can learn, understand, and interact with the world like the brain to make intelligent interactive real time assistance accessible to everybody.
Our uniqueness
With unmatched expertise and experience in developing one-of-a-kind Digital Brain technology, inait is building AI for life-like interactions in complex dynamic environments. Our revolutionary approach involves teaching digital brains, the closest proxy to real brains, to naturally evolve cognitive skills. By leveraging modern AI for sensory pre-processing and for language, inait is building Intelligent Action Models (iAMs) to provide holistic, generalizable AI for all industry verticals, starting with finance and robotics. With key strategic partners in technology & go-to-market and with robust financial backing, inait represents a winner-take-all opportunity in the post-genAI era.
The Problem
We stand at the threshold of an “Adaptive Automation Gap,” where current AI, built on rigid data-heavy and energy-hungry foundations, excels at pattern recognition and generation yet struggles to interact with never-ending changes of real-world complexity. Although these systems can leverage correlations with superhuman ability, they lack causal understanding of consequences from actions that is needed to develop advanced cognitive skills for navigating the rules of engagement. Each new task demands exponentially greater data and energy, causing skill acquisition to plateau. As a result, modern AI cannot accumulate all the abilities to achieve generalized intelligence for life-like interactions in dynamic physical, virtual or data-rich environments.
Modern AI cannot
achieve life-like interactions in dynamic physical, virtual and data-rich environments
accumulate new skills without an exponential rise in data and energy needs
develop exponential cognition that is needed to reach generalized forms of artificial intelligence
keep up in dynamic environments because correlations are insufficient to learn the rules of engagement
grow in intelligence remotely, relying on expensive centralized version updates
The Solution
Digital Brain Technology that bridges the Adaptive Automation Gap with evolutionary solved architectures for general intelligence, including a Neural Code that captures the brain’s language, and a Causal Learning Rule that grasps cause-and-effect. Free from the bounds of brute-force correlation, these Digital Brains adapt with minimal data, learning on the fly without centralized retraining. By fusing with modern AI—leveraging the raw power of CNNs, RNNs, GNNs, RLMs, and LLMs—we create Intelligent Action Models (iAMs) that unite life-like flexibility with world-class pattern recognition, forging a truly interactive, ever-evolving intelligence to master real-world dynamics.
AI that learns
cause and effect from actions and consequences, allowing learning of the rules of engagement and the natural emergence of cognitive skills
new skills easier and easier as seen in all biological organisms, not harder and harder as seen in all modern AI
to accumulate the full cognitive skill sets needed to adapt to interact intelligently in any given dynamic environment
and develops agency through embodiment to achieve life-like interactions in complex dynamic environments
continuously and remotely from new experiences without needing retraining with more data and energy
The Founder
Henry Markram
Professor of Neuroscience and serial entrepreneur
Henry has pioneered groundbreaking initiatives that have redefined brain research and computational neuroscience, including founding the Brain Mind Institute, the Blue Brain Project, and the Human Brain Project, and serving as co-founder and chairman of Frontiers, the Frontiers Research Foundation, the Frontiers Planet Prize, and Inait. He is also the founder and president of the Board of the Open Brain Institute and inait. A visionary leader and pioneer in simulation neuroscience, Henry has led revolutionary efforts to work out how to build digital brains, how they work, and how they learn.
