Founded | 1991 |
---|---|
Founders | |
Type | Division |
Owner | Microsoft |
Key people |
|
Subsidiaries | Havok Group |
Employees (in 2016) | ~500 [1] |
Website | www |
Microsoft Research (MSR) is the research subsidiary of Microsoft. It was created in 1991 by Richard Rashid, [2] Bill Gates and Nathan Myhrvold with the intent to advance state-of-the-art computing and solve difficult world problems through technological innovation in collaboration with academic, government, and industry researchers. The Microsoft Research team has more than 1,000 computer scientists, physicists, engineers, and mathematicians, including Turing Award winners, [3] Fields Medal winners, MacArthur Fellows, and Dijkstra Prize winners.
Between 2010 and 2018, 154,000 AI patents were filed worldwide, with Microsoft having by far the largest percentage of those patents, at 20%. [4] According to estimates in trade publications, Microsoft spent about $6 billion annually in research initiatives from 2002 to 2010 and has spent from $10–14 billion annually since 2010. [5] [6]
Microsoft Research has made significant advances in the field of AI which it has infused in its products including Kinect, Bing, Holo Lens, Cortana, Microsoft Translator, Linkedin, Havok and Dynamics to provide its customers with more benefits and better service. [5]
The mission statement of MSR is:
Microsoft Research includes the core Microsoft Research labs and Microsoft Research AI, Microsoft Research NExT (for New Experiences and Technologies), and other incubation efforts all directed by corporate vice president Peter Lee.
Microsoft research is categorized into the following broad areas: [7]
Microsoft Research sponsors the Microsoft Research Fellowship for graduate students.
Microsoft has research labs around the world including the following non-exhaustive list: [9]
Microsoft Research invests in multi-year collaborative joint research with academic institutions at Barcelona Supercomputing Center, [22] INRIA, [23] Carnegie Mellon University, Massachusetts Institute of Technology, São Paulo Research Foundation (FAPESP), the Microsoft Research Centre for Social NUI and others. [24] [25]
Since 2016, Microsoft has partnered with Toyota Connected to research technology for telematics, data analytics and network security services. [26]
In October 2019, Microsoft partnered with Novartis to apply artificial intelligence to enhance personalized medicine research. [27]
In 2023, Microsoft signed a multi-year deal to collaborate with Syneos Health in development of a platform to leverage machine learning for the optimization of clinical trials. [28]
Microsoft's "AI for Good" initiative represents a significant commitment to leveraging artificial intelligence technology for social and environmental benefits. This initiative is part of a broader vision by Microsoft to utilize AI in addressing some of the world's most challenging issues, including those related to health, the environment, accessibility, cultural heritage, and humanitarian action. [29] AI for Good includes topics like Microsoft AI for Earth.
Microsoft Azure Quantum has researched quantum information science since 2000 and is developing a topological quantum computer based on Majorana zero modes. [30]
In 2000, physicist Alexei Kitaev at Microsoft Research proposed developing a topological quantum computer from Majorana quasiparticles. [31] [30]
In 2002, Michael Freedman, who led Microsoft’s quantum research at Station Q in 2005, authored a paper with Kitaev demonstrating how a topological quantum computer could perform any computation that a conventional quantum computer could. [32]
In 2005, 2006 and 2008, Sankar Das Sarma, Freedman and Chetan Nayak developed theoretical proposals for a topological qubit using the fractional quantum Hall effect and for topological quantum computing based on non-abelian anyons. [33] [34] [35]
In 2015, Microsoft developed the theoretical framework of Majorana zero modes for information processing through braiding-based topological quantum computing. [36]
In 2023, Microsoft research demonstrated the creation and control of Majorana quasiparticles for topological quantum computing. [37]
In 2024, Microsoft created 4 logical qubits from 30 physical qubits, demonstrating reliable logical qubits by reducing the logical error rate by 800x compared to the physical error rate. [38]
A quantum computer is a computer that exploits quantum mechanical phenomena. On small scales, physical matter exhibits properties of both particles and waves, and quantum computing leverages this behavior using specialized hardware. Classical physics cannot explain the operation of these quantum devices, and a scalable quantum computer could perform some calculations exponentially faster than any modern "classical" computer. Theoretically a large-scale quantum computer could break widely used encryption schemes and aid physicists in performing physical simulations; however, the current state of the art is largely experimental and impractical, with several obstacles to useful applications.
This is a timeline of quantum computing.
In physics, an anyon is a type of quasiparticle so far observed only in two-dimensional systems. In three-dimensional systems, only two kinds of elementary particles are seen: fermions and bosons. Anyons have statistical properties intermediate between fermions and bosons. In general, the operation of exchanging two identical particles, although it may cause a global phase shift, cannot affect observables. Anyons are generally classified as abelian or non-abelian. Abelian anyons, detected by two experiments in 2020, play a major role in the fractional quantum Hall effect.
Quantum Information Science is a field that combines the principles of quantum mechanics with information theory to study the processing, analysis, and transmission of information. It covers both theoretical and experimental aspects of quantum physics, including the limits of what can be achieved with quantum information. The term quantum information theory is sometimes used, but it does not include experimental research and can be confused with a subfield of quantum information science that deals with the processing of quantum information.
In computer science and quantum physics, the Church–Turing–Deutsch principle is a stronger, physical form of the Church–Turing thesis formulated by David Deutsch in 1985. The principle states that a universal computing device can simulate every physical process.
Quantum error correction (QEC) is a set of techniques used in quantum computing to protect quantum information from errors due to decoherence and other quantum noise. Quantum error correction is theorised as essential to achieve fault tolerant quantum computing that can reduce the effects of noise on stored quantum information, faulty quantum gates, faulty quantum state preparation, and faulty measurements. Effective quantum error correction would allow quantum computers with low qubit fidelity to execute algorithms of higher complexity or greater circuit depth.
Quantum programming is the process of designing or assembling sequences of instructions, called quantum circuits, using gates, switches, and operators to manipulate a quantum system for a desired outcome or results of a given experiment. Quantum circuit algorithms can be implemented on integrated circuits, conducted with instrumentation, or written in a programming language for use with a quantum computer or a quantum processor.
A topological quantum computer is a theoretical type of quantum computer proposed by Russian-American physicist Alexei Kitaev in 1997. It utilizes quasiparticles, known as anyons, in two-dimensional systems. These anyons' world lines intertwine to form braids in a three-dimensional spacetime. These braids act as the logic gates of the computer. The primary advantage of using quantum braids over trapped quantum particles is enhanced stability. While small, cumulative perturbations can cause quantum states to decohere and introduce errors in traditional quantum computations, such perturbations do not alter the topological properties of the braids. This stability is akin to the difference between cutting and reattaching a string to form a different braid versus a ball colliding with a wall.
A Majorana fermion, also referred to as a Majorana particle, is a fermion that is its own antiparticle. They were hypothesised by Ettore Majorana in 1937. The term is sometimes used in opposition to a Dirac fermion, which describes fermions that are not their own antiparticles.
Sankar Das Sarma is an India-born American theoretical condensed matter physicist. He has been a member of the department of physics at University of Maryland, College Park since 1980.
D-Wave Quantum Systems Inc. is a quantum computing company with locations in Palo Alto, California and Burnaby, British Columbia. D-Wave claims to be the world's first company to sell computers that exploit quantum effects in their operation. D-Wave's early customers include Lockheed Martin, the University of Southern California, Google/NASA, and Los Alamos National Laboratory.
Hartmut Neven is a scientist working in quantum computing, computer vision, robotics and computational neuroscience. He is best known for his work in face and object recognition and his contributions to quantum machine learning. He is currently Vice President of Engineering at Google where he is leading the Quantum Artificial Intelligence Lab which he founded in 2012.
In quantum many-body physics, topological degeneracy is a phenomenon in which the ground state of a gapped many-body Hamiltonian becomes degenerate in the limit of large system size such that the degeneracy cannot be lifted by any local perturbations.
In quantum computing, a qubit is a unit of information analogous to a bit in classical computing, but it is affected by quantum mechanical properties such as superposition and entanglement which allow qubits to be in some ways more powerful than classical bits for some tasks. Qubits are used in quantum circuits and quantum algorithms composed of quantum logic gates to solve computational problems, where they are used for input/output and intermediate computations.
The Eastin–Knill theorem is a no-go theorem that states: "No quantum error correcting code can have a continuous symmetry which acts transversely on physical qubits". In other words, no quantum error correcting code can transversely implement a universal gate set, where a transversal logical gate is one that can be implemented on a logical qubit by the independent action of separate physical gates on corresponding physical qubits.
This glossary of quantum computing is a list of definitions of terms and concepts used in quantum computing, its sub-disciplines, and related fields.
Zhenghan Wang is a Chinese-American mathematician. He is a principal researcher at Microsoft Station Q, as well as a professor of mathematics at the University of California, Santa Barbara.
Microsoft Azure Quantum is a public cloud-based quantum computing platform developed by Microsoft, that offers quantum hardware, software, and solutions for developers to build quantum applications. It supports variety of quantum hardware architectures from partners including Quantinuum, IonQ, and Atom Computing. To run applications on the cloud platform, Microsoft developed the Q# quantum programming language.
Chetan Nayak is an American physicist and computer scientist specializing in quantum computing. He is a professor at the University of California, Santa Barbara and a technical fellow and distinguished engineer on the Microsoft Azure Quantum hardware team. He joined Microsoft in 2005 and became director and general manager of Quantum Hardware at Microsoft Station Q at Microsoft Research in 2014.