The restart
Dake restarts as a deep tech research project operating at the intersection of quantum physics, artificial intelligence and energy engineering. This is not a simple update: the project is reconfigured from the ground up with an ambitious mandate and a rigorous scientific foundation.
Energy network optimization
The central axis of the research is energy network optimization through AI. Deep Learning algorithms are applied to the modeling and control of energy distribution infrastructures, with the goal of studying the reduction of transmission losses. Early laboratory results are encouraging, but the research is ongoing and real-scale validation remains an objective to be achieved.
Research areas
The project is structured around three exploratory fronts:
- Quantum systems: study and simulation of quantum phenomena applicable to combinatorial optimization and distributed computing.
- Distributed energy infrastructures: modeling of decentralized networks for energy production, storage and distribution.
- Gravitational potential energy harvesting: research on innovative systems for energy recovery from gravitational sources, a field that remains largely unexplored.
Technology stack
The technologies employed include Deep Learning, Physics Simulation, Quantum Computing, Reinforcement Learning and Graph Neural Networks — a set of tools that reflects the interdisciplinary nature and computational complexity of the project.