Hartmut Neven

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Hartmut Neven
Hartmut Neven.png
Hartmut Neven at Further Future 2016
Born1964 (age 59–60)
Aachen, Germany
Nationality German
Scientific career
Fields Physics, Computer Science, Neuroscience
Doctoral advisor Christoph von der Malsburg

Hartmut Neven (born 1964) 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. [1] [2] [3] [4] [5] [6]

Contents

Education

Hartmut Neven studied Physics and Economics in Brazil, Köln, Paris, Tübingen and Jerusalem. He wrote his Master thesis on a neuronal model of object recognition at the Max Planck Institute for Biological Cybernetics under Valentino Braitenberg. In 1996 he received his Ph.D. in Physics from the Institute for Neuroinformatics at the Ruhr University in Bochum, Germany, for a thesis on "Dynamics for vision-guided autonomous mobile robots" written under the tutelage of Christoph von der Malsburg. He received a scholarship from the Studienstiftung des Deutschen Volkes, Germany’s most prestigious scholarship foundation.

Work

1998 Neven became research professor of computer science at the University of Southern California at the Laboratory for Biological and Computational Vision. 2003 he returned as the head of the Laboratory for Human-Machine Interfaces at USC's Information Sciences Institute.

Face recognition, avatars and face filters

Neven co-founded two companies, Eyematic for which he served as CTO and Neven Vision which he initially led as CEO. At Eyematic he developed face recognition technology and real-time facial feature analysis for avatar animation. [7] Teams led by Neven have repeatedly won top scores in government sponsored tests designed to determine the most accurate face recognition software. [8] Face filters, now ubiquitous on mobile phones, were launched for the first time by Neven Vision on the networks of NTT DoCoMo and Vodafone Japan in 2003. Neven Vision also pioneered mobile visual search for camera phones. [9] [10] Neven Vision was acquired by Google in 2006. [11]

Object recognition and adversarial images

At Google he managed teams responsible for advancing Google's visual search technologies. His team launched Google Goggles [12] [13] [14] [15] now Google Lens. The concept of adversarial patterns originated in his group when he tasked Christian Szegedy with a project to modify the pixel inputs of a deep neural network to lower the activity of select output nodes. [16] The motivation was to use this technique for object localization which did not work out. But the idea gave rise to the fields of adversarial learning and DeepDream art. In 2013 his optical character recognition team won the ICDAR Robust Reading Competition by a wide margin [17] and in 2014 the object recognition team won the ImageNet challenge. [18]

Google Glass

Neven was a co-founder of the Google Glass project. His team completed the first prototype, codenamed Ant, in 2011.

Quantum Artificial Intelligence

In 2006 Neven started to explore the application of quantum computing to hard combinatorial problems arising in machine learning. In collaboration with D-Wave Systems he developed the first image recognition system based on quantum algorithms. It was demonstrated at SuperComputing07. [19] At NIPS 2009 his team demonstrated the first binary classifier trained on a quantum processor. [20] [21] [22]

In 2012 together with Pete Worden at NASA Ames he founded the Quantum Artificial Intelligence Laboratory. In 2014 he invited John M. Martinis and his group at UC Santa Barbara to join the lab to start a fabrication facility for superconducting quantum processors. The Quantum Artificial Intelligence team performed the first experimental demonstration of a scalable simulation of a molecule. [23]

In 2016 the team formulated an experiment to demonstrate quantum supremacy. [24] Quantum supremacy was then declared by Google in October 2019. [25]

In 2023 Quantum AI researchers demonstrated that quantum error correction works in practice by showing for the first time that the error of a logical qubit decreases when increasing the number of physical qubits it is composed of. [26] [27]

Google’s quantum processors have been used to study the physics of quantum many body states that otherwise are challenging to prepare in a laboratory such as time crystals, [28] traversable wormholes [29] [30] and non-Abelian anyons. [31] [32]

Neven's Law

The observation that quantum computers are gaining computational power at a doubly exponential rate is called "Neven's law". [33]

Hartmut Neven was named as one of Fast Company’s Most Creative People of 2020. [34] Citing Neven: "It’s not one company versus another, but rather, humankind versus nature — or humankind with nature." [35]

Related Research Articles

<span class="mw-page-title-main">Quantum computing</span> Technology that uses quantum mechanics

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. In particular, 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.

Superconducting quantum computing is a branch of solid state quantum computing that implements superconducting electronic circuits using superconducting qubits as artificial atoms, or quantum dots. For superconducting qubits, the two logic states are the ground state and the excited state, denoted respectively. Research in superconducting quantum computing is conducted by companies such as Google, IBM, IMEC, BBN Technologies, Rigetti, and Intel. Many recently developed QPUs use superconducting architecture.

<span class="mw-page-title-main">Quantum neural network</span> Quantum Mechanics in Neural Networks

Quantum neural networks are computational neural network models which are based on the principles of quantum mechanics. The first ideas on quantum neural computation were published independently in 1995 by Subhash Kak and Ron Chrisley, engaging with the theory of quantum mind, which posits that quantum effects play a role in cognitive function. However, typical research in quantum neural networks involves combining classical artificial neural network models with the advantages of quantum information in order to develop more efficient algorithms. One important motivation for these investigations is the difficulty to train classical neural networks, especially in big data applications. The hope is that features of quantum computing such as quantum parallelism or the effects of interference and entanglement can be used as resources. Since the technological implementation of a quantum computer is still in a premature stage, such quantum neural network models are mostly theoretical proposals that await their full implementation in physical experiments.

In physics, quantum acoustics is the study of sound under conditions such that quantum mechanical effects are relevant. For most applications, classical mechanics are sufficient to accurately describe the physics of sound. However very high frequency sounds, or sounds made at very low temperatures may be subject to quantum effects.

<span class="mw-page-title-main">D-Wave Systems</span> Canadian quantum computing company

D-Wave Quantum Systems Inc. is a Canadian quantum computing company, based in 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 Lab.

<span class="mw-page-title-main">Quantum simulator</span> Simulators of quantum mechanical systems

Quantum simulators permit the study of a quantum system in a programmable fashion. In this instance, simulators are special purpose devices designed to provide insight about specific physics problems. Quantum simulators may be contrasted with generally programmable "digital" quantum computers, which would be capable of solving a wider class of quantum problems.

D-Wave Two is the second commercially available quantum computer, and the successor to the first commercially available quantum computer, D-Wave One. Both computers were developed by Canadian company D-Wave Systems. The computers are not general purpose, but rather are designed for quantum annealing. Specifically, the computers are designed to use quantum annealing to solve a single type of problem known as quadratic unconstrained binary optimization. As of 2015, it was still debated whether large-scale entanglement takes place in D-Wave Two, and whether current or future generations of D-Wave computers will have any advantage over classical computers.

The Quantum Artificial Intelligence Lab is a joint initiative of NASA, Universities Space Research Association, and Google whose goal is to pioneer research on how quantum computing might help with machine learning and other difficult computer science problems. The lab is hosted at NASA's Ames Research Center.

<span class="mw-page-title-main">Quantum machine learning</span> Interdisciplinary research area at the intersection of quantum physics and machine learning

Quantum machine learning is the integration of quantum algorithms within machine learning programs.

In quantum computing, quantum supremacy or quantum advantage is the goal of demonstrating that a programmable quantum computer can solve a problem that no classical computer can solve in any feasible amount of time, irrespective of the usefulness of the problem. The term was coined by John Preskill in 2012, but the concept dates to Yuri Manin's 1980 and Richard Feynman's 1981 proposals of quantum computing.

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.

<span class="mw-page-title-main">Sycamore processor</span> 2019 quantum processor by Google

Sycamore is a transmon superconducting quantum processor created by Google's Artificial Intelligence division. It has 53 qubits.

<span class="mw-page-title-main">Sergio Boixo</span> Spanish physicist

Sergio Boixo has degrees in computer engineering, philosophy, mathematics, and master and PhD in physics, and is best known for his work on quantum computing. He is currently working as Chief Scientist Quantum Computer Theory for Google's Quantum Artificial Intelligence Lab, a team he joined in 2013, shortly after its foundation.

<span class="mw-page-title-main">Quantum engineering</span>

Quantum engineering is the development of technology that capitalizes on the laws of quantum mechanics. Quantum engineering uses quantum mechanics as a toolbox for the development of quantum technologies, such as quantum sensors or quantum computers.

Cross-entropy benchmarking is a quantum benchmarking protocol which can be used to demonstrate quantum supremacy. In XEB, a random quantum circuit is executed on a quantum computer multiple times in order to collect a set of samples in the form of bitstrings . The bitstrings are then used to calculate the cross-entropy benchmark fidelity via a classical computer, given by

This glossary of quantum computing is a list of definitions of terms and concepts used in quantum computing, its sub-disciplines, and related fields.

Andrew A. Houck is an American physicist, quantum information scientist, and professor of electrical and computer engineering at Princeton University. He is director of the Co-Design Center for Quantum Advantage, a national research center funded by the U.S. Department of Energy Office of Science, as well as co-director of the Princeton Quantum Initiative. His research focuses on superconducting electronic circuits to process and store information for quantum computing and to simulate and study many-body physics. He is a pioneer of superconducting qubits.

<span class="mw-page-title-main">Pedram Roushan</span> Iranian-american physicist

Pedram Roushan is an Iranian-American physicist working at Google AI on quantum computing and quantum simulation.

References

  1. ↑ "10 Breakthrough Technologies". MIT Technology Review. 2017-03-01. Archived from the original on 2017-04-05. Retrieved 2017-04-11.
  2. ↑ "The Infinity Machine". Time Magazine. 2014-02-17.
  3. ↑ Quantum AI Lab
  4. ↑ "A first look inside Google's futuristic quantum lab". The Verge.
  5. ↑ "The World-Changing Race to Develop the Quantum Computer". New Yorker. 2022.
  6. ↑ "Publications Hartmut Neven". Google Research Blog.
  7. ↑ "Seal of Excellence Winners". Animation Magazine. Archived from the original on 2012-02-13. Retrieved 2008-04-13.
  8. ↑ "Face Recognition Vendor Test". Archived from the original on 2018-09-28. Retrieved 2008-04-13.
  9. ↑ "Phones That Get in Your Face". Wired Magazine.
  10. ↑ "Hyperlinking the World". The Feature. Archived from the original on 2016-03-03. Retrieved 2008-04-13.
  11. ↑ Flanigan, James (2007-01-18). "The Route From Research to Start-Up". The New York Times. Retrieved 2010-05-04.
  12. ↑ Graham, Jefferson (2008-09-17). "Google can sort digital photos on face value". USA Today. Retrieved 2010-05-04.
  13. ↑ "Google begins blurring faces in Street View". CNET News.
  14. ↑ "Google Goggles". Google Labs.
  15. ↑ "A new landmark in computer vision". Google Blog.
  16. ↑ Szegedy, Christian; Zaremba, Wojciech; Sutskever, Ilya; Bruna, Joan; Erhan, Dumitru; Goodfellow, Ian; Fergus, Rob (2013). "Intriguing properties of neural networks". arXiv: 1312.6199 [cs.CV].
  17. ↑ PhotoOCR: Reading Text in Uncontrolled Conditions
  18. ↑ "Going Deeper with Convolutions" (PDF). Archived from the original (PDF) on 2019-08-05. Retrieved 2019-08-02.
  19. ↑ "D-Wave's quantum computer ready for latest demo". CNET News.
  20. ↑ "Google demonstrates quantum computer image search". New Scientist.
  21. ↑ "Google exploring quantum computing algorithms". Physics Today. Archived from the original on 2011-09-18. Retrieved 2010-06-19.
  22. ↑ "Machine Learning with Quantum Algorithms". Google Research Blog.
  23. ↑ o'Malley, P. J. J.; et al. (2016). "Scalable Quantum Simulation of Molecular Energies". Physical Review X. 6 (3): 031007. arXiv: 1512.06860 . Bibcode:2016PhRvX...6c1007O. doi:10.1103/PhysRevX.6.031007. S2CID   4884151.
  24. ↑ Boixo, Sergio; Isakov, Sergei V.; Smelyanskiy, Vadim N.; Babbush, Ryan; Ding, Nan; Jiang, Zhang; Bremner, Michael J.; Martinis, John M.; Neven, Hartmut (2018). "Characterizing quantum supremacy in near-term devices". Nature Physics. 14 (6): 595–600. arXiv: 1608.00263 . Bibcode:2018NatPh..14..595B. doi:10.1038/s41567-018-0124-x. S2CID   256713071.
  25. ↑ Arute, Frank; Arya, Kunal; Babbush, Ryan; Bacon, Dave; Bardin, Joseph C.; Barends, Rami; Biswas, Rupak; Boixo, Sergio; Brandao, Fernando G. S. L.; Buell, David A.; Burkett, Brian; Chen, Yu; Chen, Zijun; Chiaro, Ben; Collins, Roberto; Courtney, William; Dunsworth, Andrew; Farhi, Edward; Foxen, Brooks; Fowler, Austin; Gidney, Craig; Giustina, Marissa; Graff, Rob; Guerin, Keith; Habegger, Steve; Harrigan, Matthew P.; Hartmann, Michael J.; Ho, Alan; Hoffmann, Markus; et al. (23 October 2019). "Quantum supremacy using a programmable superconducting processor". Nature. 574 (7779): 505–510. arXiv: 1910.11333 . Bibcode:2019Natur.574..505A. doi:10.1038/s41586-019-1666-5. PMID   31645734. S2CID   204836822.
  26. ↑ "Our progress toward quantum error correction". The Keyword. 22 February 2023.
  27. ↑ Acharya, Rajeev; et al. (2023). "Suppressing quantum errors by scaling a surface code logical qubit". Nature. 614 (7949): 676–681. Bibcode:2023Natur.614..676G. doi:10.1038/s41586-022-05434-1. PMC   9946823 . PMID   36813892.
  28. ↑ Mi, Xiao; et al. (2022). "Time Crystals". Nature. 601 (7894): 531–536. arXiv: 2107.13571 . doi:10.1038/s41586-021-04257-w.
  29. ↑ "Making a Dual of a Traversable Wormhole with a Quantum Computer". Google Research Blog.
  30. ↑ Jafferis, Daniel; Zlokapa, Alexander; Lykken, Joseph D.; Kolchmeyer, David K.; Davis, Samantha I.; Lauk, Nikolai; Neven, Hartmut; Spiropulu, Maria (2022). "Traversable wormhole dynamics on a quantum processor". Nature. 612 (7938): 51–55. Bibcode:2022Natur.612...51J. doi:10.1038/s41586-022-05424-3. PMID   36450904.
  31. ↑ "The world's first braiding of non-Abelian anyons". Google Research Blog.
  32. ↑ Andersen, T. I.; et al. (2023). "Non-Abelian braiding of graph vertices in a superconducting processor". Nature. 618 (7964): 264–269. arXiv: 2210.10255 . Bibcode:2023Natur.618..264G. doi:10.1038/s41586-023-05954-4.
  33. ↑ Hartnett, Kevin (2019-06-18). "Does Neven's Law Describe Quantum Computing's Rise?". Quanta Magazine.
  34. ↑ Google scientist Hartmut Neven coined the term ‘Quantum AI.’
  35. ↑ "Google quantum breakthrough will help solve 'impossible problems'". Financial Times. Oct 24, 2019. Retrieved 2019-10-28.
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