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QpiAI Achieves High Speed Quantum Error Correction on Superconducting Systems with New Decoder Platform - Business Wire India

Google News – Quantum Computing
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⚡ Quantum Brief
The decoder, based on a union-find algorithm, is designed to operate in real time alongside superconducting qubits and represents a key step toward practical fault-tolerant quantum computing. A scalable quantum error correction system has been developed by QpiAI to enable fast, scalable error correction using a rotated surface code architecture. QpiAI, a leader in quantum computing and generative AI, announced its maiden external funding of $6.5 million to build Quantum computing and Generative AI products and platforms. QpiAI, a leader in quantum computing and AI today announced QpiAISense™ platform for room temperature qubit control.
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Quantum News · Media Library

QpiAI Gen-1 25 qubit Quantum computer Indus, picture from QpiAI Bangalore centre with CEO Dr Nagendra Nagaraja (Left) and VP of Quantum hardware Dr Manjunath R V (Right). A scalable quantum error correction system has been developed by QpiAI to enable fast, scalable error correction using a rotated surface code architecture. The decoder, based on a union-find algorithm, is designed to operate in real time alongside superconducting qubits and represents a key step toward practical fault-tolerant quantum computing. A scalable quantum error correction system has been developed by QpiAI to enable fast, scalable error correction using a rotated surface code architecture. The decoder, based on a union-find algorithm, is designed to operate in real time alongside superconducting qubits and represents a key step toward practical fault-tolerant quantum computing. QpiAI, a leader in quantum computing and generative AI, announced its maiden external funding of $6.5 million to build Quantum computing and Generative AI products and platforms. QpiAI, a leader in quantum computing and AI today announced QpiAISense™ platform for room temperature qubit control. QpiAISense™ accelerates ML library using discrete FPGA DSPs currently. But in future it would support massive ML compute capability as much as 8000 trillion operations per second per watt (8000 Tops/watt ) using Qpisemi’s (https://www.qpisemi.tech) silicon photonics based AI20P001 to be integrated on QpiAISense™ platform. 5th Floor, 405-B DLF Cyber Park,Tower- B, Sector-20 Udyog Vihar Phase- lll Gurugram Haryana 122016 Copyright © 2026 Business Wire India.

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