At Automatski, we’ve rebuilt RL from the ground up using deterministic algorithms. Our approach eliminates the need for massive sampling, reducing sample complexity from exponential

Automatski redefines deep learning by eliminating backpropagation entirely—replacing it with forward-only learning that slashes compute costs, removes the need for GPUs, and enables training of

Scalable system for solving machine learning and linear algebra problems with billions of variables. Offers exponential advantage over traditional HHL algorithm approaches.

Universal quantum computing system with over a billion qubits and tunable infinite precision. Enables unrestricted-depth quantum logic processing.

Large-scale annealing system supporting 10¹⁸ (quintillion) qubits for massive combinatorial optimization. Robust for physical annealing use cases.