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QpiAI Announces AI-Enabled QpiAISense Platform


Insider Brief:

  • QpiAI has announced the release of its QpiAISense platform for room-temperature qubit control.
  • Further to accelerate the optimization workload on the quantum computers, QpiAI will be integrating the Trion SoC onto the QpiAISense platform.
  • QpiAIsense hardware platform and QpiAI-Quantum software platform have a roadmap with the integration of a hybrid classical-Quantum compute chipset solution that QpiAI is working on to vertically integrate AI and Quantum processing to accelerate Quantum application adoption.

PRESS RELEASE — MILPITAS, Calif. and BENGALURU, India, August 24, 2022 — 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 silicon photonics-based AI20P001 to be integrated on QpiAISense platform. Qubit control and high-fidelity operation of a Quantum computer require ML-based technology, which QpiAI provides readily.

Further to accelerate the optimization workload on the quantum computers, QpiAI will be integrating the Trion SoC onto QpiAISense platform. Trion will be a gateway for hybrid Classical-Quantum compute software development and application. Current applications which will be run on QpiAISense will be running smoothly with both AI20P001 and Trion integration of QpiAISense.

  • QpiAI begins deployment of QpiAISense room temperature Qubit controller platform, which has native ML acceleration capability to control various qubits types including Superconducting, Spin and Ion-traps.
  • QpiAISense platform is thoroughly tested with real-world applications like logistics, Finance, materials discovery, AI/ML applications via interfacing with QpiAI-Quantum software libraries.
  • Along with the number of channels of 16, which is the highest in the Industry, ML acceleration is the key differentiator to tuning the Qubits continuously to ensure high performance and lower operations error of the qubits.
  • QpiAISense Single unit box can control 16 channels. But it can be modularly stacked to control as many qubits as possible. QpiAISense platform can control 25, 50, 124, 256, 512 ,1024 and 2048 qubits.
  • QpiAIsense hardware platform and QpiAI-Quantum software platform have a roadmap with the integration of a hybrid classical-Quantum compute chipset solution that QpiAI is working on to vertically integrate AI and Quantum processing to accelerate Quantum application adoption.
  • In the near term future, QPIAIsense integrates an Optimization processor (QpiAI Trion) and AI processor based on silicon photonics (QpiSemi AI20P001) that offers up to 8000 ToPs/W of ML acceleration capability for tuning and analytics on 1024+ logical qubits (millions of physical Qubits) and support AI and quantum applications.

QpiAISense Product Details

  • High speed Integrated control and readout electronics for quantum processors.
  • Control and readout of up to 16 qubits.
  • Trigger to AWG pulse <40ns.
  • Feedback Latency <100ns.
  • Capability for Quantum Error Correction and Error mitigation.
  • Available for Shipping Q4 2022

About QpiAI

QpiAI is a world leader in AI and Quantum computing. QpiAI is vertically integrating Quantum computing and AI to offer solutions to areas like manufacturing, industrial, transportation, finance, pharma and materials. It has various software platforms and products including QpiAI-pro, QpiAI-explorer, QpiAISense, QpiAI-logistics, QpiAIopt, QpiAIsim, QpiAIML. It is building a complete hardware stack based on 3 chip solutions of Trion (universal optimizer Chip), Bumblebee (scalable cryogenic control chip) and scalable spin-qubit-based QPU (Quantum processing unit) , which can be scalable to 2048 logical qubits. QpiAI is currently ready with room temperature control electronics based on its hardware platform QpiAI-Sense. QpiAI is a subsidiary of Qpi Technology.


SOURCE: QpiAI

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The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

Picture of Jake Vikoren

Jake Vikoren

Company Speaker

Picture of Deep Prasad

Deep Prasad

Company Speaker

Picture of Araceli Venegas

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