Quantum computing utilizes quantum-mechanical phenomena, including superposition and entanglement, to perform operations on data. According to Wikipedia, quantum computers differ from traditional binary digital electronic systems based on transistors. To be sure, digital computing encodes data into binary digits (bits), each of which is always in one or two definite states: 0 or 1. In contrast, quantum computation exploits quantum bits, which can be in superpositions of states.
“[Quantum computing] will mean a new type of computing hardware, which will allow us to solve massively parallel problems much more efficiently,” Richard Murray, lead technologist of emerging technologies and industries at Innovate UK, recently told IDG Connect. “It will be very effective at solving problems like machine learning, image recognition, materials modeling and drug discovery, search and optimization, which classical computers can do in only a very limited way.”
Ergun Ekici, VP of emerging technologies at IPsoft, expressed similar sentiments.
“With quantum we can expand the reach of cognitive intelligence in computers. Quantum computing will be a significant influence on building machines that can reason in parallel with the speed and complexity of the human brain,” he told IDG Connect. “Computational thinking can happen in near real-time, taking full advantage of quantum’s new architecture. This will lead to significantly more advanced AI in the future for a variety of applications in businesses and elsewhere.”
According to Gary Bronner, VP of Rambus Labs, medium sized quantum processors should be available in the next decade. Indeed, existing computer architectures are currently reaching their limits due to the ever-increasing demands of real-time data consumption. This is why, says Bronner, that Rambus is now collaborating with Microsoft researchers to explore future memory requirements for quantum computing.
“[The limits of traditional binary digital electronic systems] are driving the need to explore new high-performance, energy-efficient computer systems,” he explained. “By working with Microsoft on this project, we can leverage our vast expertise in memory systems to identify new architectural models.”
As Bronner points out, Microsoft has invested in projects to advance understanding of quantum computing. More specifically, Microsoft is focusing on exploring theoretical and experimental approaches to creating quantum computers, designing software, hardware and other elements that support the company’s research and direction.
As part of the above-mentioned program, Rambus and Microsoft are pooling resources to further examine potential architectures that can significantly enhance memory capabilities in various scenarios and improve overall system performance.
It should be noted that the field of quantum computing is based on the work of Paul Benioff, Yuri Manin, Richard Feynman and David Deutsch in 1985. Interested in learning more about what the future holds for quantum computing? You check out “Quantum Computing: A Gentle Introduction (Scientific and Engineering Computation)” by Eleanor G. Rieffel and Wolfgang H. Polak, “Quantum Computation and Quantum Information: 10th Anniversary Edition” and “Quantum Computing for Computer Scientists” by Noson S. Yanofsky and Mirco A. Mannucci.