Scientists at Cambridge Quantum Computing (CQC) have developed methods and demonstrated that quantum machines can learn to infer hidden information from very general probabilistic reasoning models. These methods could improve a broad range of applications, where reasoning in complex systems and quantifying uncertainty are crucial. Examples include medical diagnosis, fault-detection in mission-critical machines, or financial forecasting for investment management.
Cambridge Quantum Computing Pioneers Quantum Machine Learning Methods for Reasoning
How AI and Quantum Computers Could Bring Massive Change
In this contributed, Anthony Coggine, HR professional turned business analyst, discusses how the future of computing could one day be a confluence of AI and quantum computers. AI and quantum computers are immensely intriguing frontiers. Both are marvels of modern computer science and sit at the bleeding edge of what’s possible.
D-Wave Breakthrough Demonstrates First Large-Scale Quantum Simulation of Topological State of Matter
D-Wave Systems Inc., a leader in quantum computing systems and software, published a milestone study demonstrating a topological phase transition using its 2048-qubit annealing quantum computer. This complex quantum simulation of materials is a major step toward reducing the need for time-consuming and expensive physical research and development.
Everything You Need to Know about Quantum Computing
In this contributed article, Josh Althauser, an entrepreneur with a background in design and M&A, outlines the field of quantum computing and how this technology may address the need for more computationally complex machines to power our most pressing problems. Quantum computers could lead us to some very compelling solutions.
Innovate UK Awards Grant to AI Planning Optimization Project Using D-Wave System
D-Wave Systems Inc., the leader in quantum computing systems and software, announced its involvement in a grant-funded UK project to improve logistics and planning operations using quantum computing algorithms. The work will focus on an area known as AI/Hierarchical Task Network planning techniques, used to optimize resource management and operations for a wide range of industries including law enforcement, telecommunications, and transportation.