공시 • May 01
Ionq Demonstrates Quantum-Enhanced Applications Advancing Ai
IonQ announced new research advancements in applying quantum computing to artificial intelligence (AI) and Machine Learning, marking significant progress in hybrid quantum-classical approaches that enhance both large language models (LLMs) and generative AI. Detailed in two new research papers, IonQ researchers demonstrated how quantum computing can support advanced materials development by generating synthetic images of rare anomalies and enhancing Large Language Models by adding a quantum layer for fine-tuning. These efforts reflect IonQ's continued focus on practical, near-term commercial quantum applications in AI to drive value in data-scarce settings and for complex tasks. In a newly published paper, IonQ introduced a hybrid quantum-classical architecture designed to enhance LLM fine-tuning, where a pre-trained LLM is supplemented with a small set of training data to customize its functionality via quantum machine learning. In a separate research publication, IonQ collaborated with a top-tier automotive manufacturer to apply quantum-enhanced generative adversarial networks (GANs) to materials science. Researchers trained GANs to sample the output distribution of a quantum circuit, generating synthetic images of steel microstructures that augment conventional imaging techniques, where data is often sparse, and therefore model trainability is poor. Industrial AI models often rely on proprietary data sets, which may result in lack of data, imbalance of data, or high costs in generating data. The ability to supplement image data is vital to developing AI models where the objective is to optimize manufacturing process parameters to result in material properties that meet stringent requirements. With its latest Forte Enterprise-class quantum computers, IonQ continues to push the boundaries with new capabilities that can outperform classical computing and provide opportunities to integrate AI. These research milestones follow IonQ's recent announcement of a new quantum simulation tool with Ansys, which demonstrated improvements of up to 12% for workflows used in the Computer Aided Engineering industry. IonQ has also signed a memorandum of understanding (MOU) with AIST's Global Research and Development Center for Business by Quantum AI (G-QuAT) to help advance hybrid quantum computing technologies with AI. Statements that are not historical in nature, including the terms "accessible," "aimed, available, "believe," "can," could, "cutting-edge," "delivering, "designed, drive, "focus, "growth," "impactful," "impactful," "leading, leader, making, may, "paves the way," "pioneering, "progress," " push," "solving," and other similar expressions are intended to identify forward-looking statements. These statements include those related to the IonQ's quantum computing capabilities and plans; IonQ's technology driving commercial quantum advantage in the future; the relevance, accuracy, quality, cost and energy efficiency, commercial-readiness, and utility of quantum algorithms and applications run on IonQ's quantum computers; the commercial value, effectiveness, and future impacts of IonQ's offerings available today.