Microsoft is accelerating its efforts to make a quantum computer as it looks to a future of computing beyond today's PCs and servers. Microsoft has researched quantum computing for more than a decade. Now the company's goal is to put the theory to work and create actual hardware and software. To that effect, Microsoft has put Todd Holmdahl--who was involved in the development of Kinect, HoloLens, and Xbox--to lead the effort to create quantum hardware and software. The company has also hired four prominent university professors to contribute to the company's research.
While Google, Microsoft, IBM and others have made a lot of noise around their quantum computing efforts in recent months, AWS remained quiet. The company, after all, never had its own quantum research division. Today, though, AWS announced the preview launch of Braket (named after the common notation for quantum states), its own quantum computing service. With Braket, developers can get started on building quantum algorithms and basic applications and then test them in simulations on AWS, as well as the quantum hardware from its partners. That's a smart move on AWS's part, as it's hedging its bets without incurring the cost of trying to build a quantum computer itself.
At some point in time between the rapid jump in facial recognition abilities of my iPhone and the Google DeepMind defeat of world champion Lee Sedol in the ancient game of Go, I began paying attention to developments in artificial intelligence. Both of these achievements occurred years ahead of predictions by computer scientists who are familiar with the extraordinary challenges posed by machine learning. Pictures of faces are packed with a huge amount of complex information – information that is changing over time, and involves different lighting conditions, image quality, and camera angles. The extraction of a simple quantitative feature (e.g., my name) from a database of photos seems like a Herculean task. The game of Go is another complex challenge.
IBM has announced a major new initiative to make universal quantum computers available commercially. IBM Q will offer up the power of quantum computation via the IBM Cloud platform, a first for the industry, and potentially a major step forward for the field. Quantum hardware has already been made available by the likes of D-Wave, but its hardware is limited in the kinds of computation it can achieve. IBM Q marks the first time that a universal quantum computer is being offered up. A universal quantum computer is capable of tackling problems that are too large for a conventional system, so IBM Q would have many applications beyond what's possible with current technology.
Google recently released TensorFlow Quantum, a toolset for combining state-of-the-art machine learning techniques with quantum algorithm design. This is an essential step to build tools for developers working on quantum applications. Simultaneously, they have focused on improving quantum computing hardware performance by integrating a set of quantum firmware techniques and building a TensorFlow-based toolset working from the hardware level up – from the bottom of the stack. The fundamental driver for this work is tackling the noise and error in quantum computers. Here's a small overview of the above and how the impact of noise and imperfections (critical challenges) is suppressed in quantum hardware.