QCi Embraces the Advantages of Edge Computing with a First-to-Market Portable Reservoir Computing Device
Quantum Computing Inc. (“QCi” or the “Company”) (NASDAQ: QUBT), a first-to-market photonic-based quantum technology company, today announced the release of the Company’s first-in-a-series Reservoir Computer, a cost-effective powerful and portable hardware device the size of a small power pack. This launch represents a step in making neuromorphic hardware largely accessible and affordable to individuals and small businesses. Beginning today, QCi is accepting orders via its website here.
Reservoir computing is a framework for computation derived from recurrent neural network (RNN) theory, which maps input signals into higher dimensional computational spaces through the dynamics of a fixed, non-linear system called a reservoir. It has unique advantages in the ease of training, processing speed, power efficiency, system complexity, while addressing exploding and vanishing gradient issues with typical RNN. The performance in time dependent tasks, such as chaotic time series prediction, radar signal classification, and speech recognition is exceptional. To date, the market for reservoir computing has been limited due to computing cost and technical implementation complexities, which is expected to be practically eliminated with QCi’s reservoir computer.
Dr. Yuping Huang, QCi Chief Quantum Scientist commented, “Our core mission at QCi has always been to democratize quantum and photonic technology. We recognize there is a significant barrier for individuals and small business to access large data centers and high-end GPUs, particularly as it relates to AI. We aim to lower this barrier by offering a photonic accelerated system at a low cost and small size. As a result of years of research and development of innovative photonics engineering, combined with custom hardware and advanced AI techniques, our team has created a powerful yet affordable computing platform of machine learning specific hardware.”
QCi’s first reservoir computer uses the Company’s proprietary capability to program commercial FPGA chips to create a small footprint hardware device that requires 80 to 95% less electricity than traditional computers. The QCi Reservoir Computer leverages the company’s unique competencies and expertise in both analog and digital design, resulting in an innovative piece of technology that interfaces seamlessly with a host machine though an Ethernet connection, enabling smooth communication and problem submission. Furthermore, the QCi reservoir computer returns solutions featuring an expanded dimensionality compared to the original data, offering more detailed and comprehensive insights, while simplifying the training process and thereby reducing the training time. It is anticipated that the launch of QCi’s reservoir computer will open up a myriad of possibilities across various industries and sectors from data analytics and optimization to pattern recognition and forecasting. QCi’s reservoir computer can address complex problems in fields such as natural language processing, weather prediction, financial analysis, drug discovery, optimization, autonomous driving, and enhancement of LiDAR capabilities.
“The launch of QCi’s Reservoir Computer represents a significant advancement in computing power and opens up new frontiers in problem-solving across numerous industries. Our talents engineering team designed the reservoir computer to handle the most demanding computational challenges in seconds. Its minimal size, weight, power, and cost factors make it particularly suitable for use as edge computing tools,” commented Robert Liscouski, CEO of Quantum Computing Inc. “To demonstrate the capabilities of the Reservoir Computer, QCi has partners with leading research institutions and organizations to conduct pilot programs and showcase real-world applications. Our current contract with NASA and collaboration with millionways speak to QCi’s Reservoir Computer’s ability to solve complex machine learning problems across different application areas.”
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