Cortisonic
Physics-Powered Learning Machines.
Cortisonic
Physics-Powered Learning Machines.
Physics-Powered Learning Machines.
Physics-Powered Learning Machines.
Cortisonic is pioneering the future of AI with reservoir computing, powered by large, interconnected arrays of nanomechanical oscillators. Our breakthrough approach harnesses the natural dynamics of oscillatory systems to perform ultra-efficient, real-time AI processing.
Backed by a successful seed-round raise, Cortisonic is poised to revolutionize machine learning by providing an alternative to traditional deep learning models. Our technology leverages the inherent memory and processing capabilities of mechanical reservoirs, enabling low-power, high-performance AI solutions.
As we scale our technology and expand our research, Cortisonic is on a mission to reshape AI’s computational foundation. By fusing physics with intelligence, we are building a smarter, more sustainable future—one oscillator at a time.
This work shows how computation can emerge from the physics of motion itself. By using vibrations to carry and process information, it demonstrates a path toward mechanical intelligence — computing that’s efficient and built from the motion of matter.
A demonstration on how the precise control of sound at the microscale can reshape how information flows. By directing vibrations with near-perfect efficiency, it opens the door to integrated acoustic circuits.
By showing that sound can tunnel through solid matter at microscopic scales, this research reveals a new way to connect and control motion on a chip. It’s a glimpse into the foundation of computing built from the physics of vibration and resonance.
Phys. Rev. Applied 15, 054036 (2021)
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