How will quantum computing affect artificial intelligence applications?

A University of Minnesota Twin Cities-led team has developed a new superconducting diode, a key component in electronic devices, that could help scale up quantum computers for industry use and improve the performance of artificial intelligence systems. The paper is published in A diode allows current to flow one way but not the other in an electrical circuit. It essentially serves as half of a transistor — which is the main element in computer chips. Diodes are typically made with semiconductors, substances with electrical properties that form the base for most electronics and computers, but researchers are interested in making them with superconductors, which additionally have the ability to transfer energy without losing any power along the way. Compared to other superconducting diodes, the researchers’ device is more energy efficient, can process multiple electrical signals at a time, and contains a series of gates to control the flow of energy, a feature that has never before been integrated into a superconducting diode. “We want to make computers more powerful, but there are some hard limits we are going to hit soon with our current materials and fabrication methods,” said The University of Minnesota researchers created the device using three Josephson junctions, which are made by sandwiching pieces of non-superconducting material between superconductors. In this case, the researchers connected the superconductors with layers of semiconductors. The device’s unique des...

Posted by Jarrod McClean, Staff Research Scientist and Hsin-Yuan (Robert) Huang 1, Intern, Google Quantum AI The idea of quantum advantage is typically phrased in terms of computational advantages. That is, given some task with well defined inputs and outputs, can a quantum computer achieve a more accurate result than a classical machine in a comparable runtime? There are a number of algorithms for which quantum computers are suspected to have overwhelming advantages, such as availability of data. As such, understanding when a quantum computer can help in a machine learning task depends not only on the task, but also the data available, and a complete understanding of this must include both. In “ Computational Power of Data The idea of quantum advantage over a classical computer is often framed in terms of computational complexity classes. Examples such as factoring large numbers and simulating quantum systems are classified as bounded quantum polynomial time (BQP) problems, which are those thought to be handled more easily by quantum computers than by classical systems. Problems easily solved on classical computers are called bounded probabilistic polynomial (BPP) problems. We show that learning algorithms equipped with data from a quantum process, such as a natural process like fusion or chemical reactions, form a new class of problems (which we call BPP/Samp) that can efficiently perform some tasks that traditional algorithms without data cannot, and is a subclass of th...

The technological fields of AI and quantum technology have evolved in parallel, and have demonstrated considerable potential to complement each other. Amalgamation of them refers to the use of AI techniques to develop algorithms for quantum computing (QC) and quantum physics, as well as the use of QC to enhance AI applications. QC has the potential to revolutionize various fields. Controlling quantum systems is notoriously difficult, which is one of the major obstacles standing in the way of widespread use of QC. AI has opened up new avenues for automated control of quantum systems. In particular, the application of AI can provide invaluable insight into the complex and multifaceted domain of quantum physics to accelerate the discovery of quantum physics laws, and can potentially alleviate challenges that have been historically associated with QC and quantum communication. On the other hand, QC can also be used to enhance AI applications. For instance, QC can be used to haste the training of neural networks, which are used in machine learning. Concurrently, a series of advancements in quantum technology can serve to drive innovation in the realm of machine learning by enabling the development of novel algorithms, frameworks, and hardware. This article presents a comprehensive overview on the reciprocal relationship between AI and quantum technology, emphasizing the utility of AI in the field of quantum technology, and the potential of quantum technology to catalyze the evo...

Few areas in computer science have generated the kind of attention Artificial Intelligence and quantum computing have enjoyed in recent years. These technologies are often discussed but often misunderstood. How can industries determine what’s real and what’s overblown hype? MIT’s Computer Science and Artificial Intelligence Laboratory and MIT’s Center for Quantum Engineering are teaming up to assemble leaders across AI and Quantum to discuss the promise and practical realities - as we know them today - about quantum computing, Artificial Intelligence, and how they will affect the economy and the world. Join us November 14 for Convergence: The Promise and Reality of AI & Quantum a one-day program that is essential for those wanting to understand where quantum research stands and harness the power of quantum and AI. This program will be held in-person at MIT and virtually. Learn more about conference speakers Conference Schedule • Opening Remarks | 9:15-9:25am • Lori Glover: Managing Director, MIT CSAIL Alliances • J • • • Quantum Keynote | 9:25-9:55am • • AI Keynote | 9:55-10:25am • • Keynote Q&A | 10:25-10:45am • • • Panel 1: Where We Are with Quantum and AI (Really!) and Where We Are Going | 11:00-12:00pm • Moderator: • • Henriette Fleischmann, Co-Founder & COO, Hosta a.i. • Professor Aram Harrow, MIT Physics • • Panel 2: Advances Have Real Impact: Industry Use Cases | 1:00-2:00pm • Moderator: • Yudong Cao, CTO & Co-Founder, Zapata Computing • • Tim Menke, Co-Founder & CO...

Quantum computing is on the rise. Maybe not yet for the mainstream, but governments and industry giants have taken notice. This level of attention is there for a good reason. Quantum computing is indomitable and could increase efficiency in various fields. Here’s a quick lowdown on why it’s such a big deal. Want More Tech News? Subscribe to ComputingEdge Newsletter Today! What Is Quantum Computing? Quantum computing leverages the laws of quantum mechanics identified by physics. This branch of physics studies how the universe works at a subatomic level. Two of its properties, superposition, and entanglement, can be used to innovate computing as we know it today. Superposition is the property that allows two different states to define a system. It is not just one or another, but it can be both at a given time. In classic computing, computers work through bits that have a value of either ‘1’ or ‘0’. Quantum computing uses an equivalent called ‘qubits,’ which can have two values at a given time. Quantum entanglement describes the phenomenon where quantum particles stay connected. No matter the distance, quantum particles maintain a connection with one another. What affects one particle can affect another. These quantum properties translated to computing technology provide promising prospects. These are especially useful when exploring possibilities or going through massive amounts of data. This is an entirely different way of computing from what we use today. Quantum computing...

LinkedIn and 3rd parties use essential and non-essential cookies to provide, secure, analyze and improve our Services, and to show you relevant ads (including professional and job ads) on and off LinkedIn. Learn more in our Select Accept to consent or Reject to decline non-essential cookies for this use. You can update your choices at any time in your Two cutting-edge topics have drawn a lot of interest in the age of cutting-edge technology: quantum computing and artificial intelligence (AI). While they are very different from one another, both have the potential to completely revolutionize business. Let's examine how quantum computing and AI differ. Quantum computing, a ground-breaking discipline that uses the ideas of quantum mechanics to process data, has the potential to completely alter science and industry. Quantum computers have the capacity to overcome the constraints of conventional computing systems, giving previously unheard-of speed, efficiency, and precision. This is accomplished by utilizing the exceptional qualities of quantum bits, or qubits, such as superposition and entanglement. Let’s explore Quantum computing first Let's use an analogy to understand the idea of quantum computing. Consider yourself searching a huge library for a particular book. When using old computing, you would look through each bookcase and book one by one until you found the one you wanted. Especially if the book you're looking for is near the library's conclusion, this linear strat...