Rigetti UK Limited, a wholly owned subsidiary of Rigetti Computing,
Inc. (Nasdaq: RGTI) (“Rigetti” or the “Company”), a pioneer in
full-stack quantum-classical computing, today announced that it was
awarded an Innovate UK grant as part of the Feasibility Studies in
Quantum Computing Applications competition. The consortium aims to
use quantum computing to improve current classical machine learning
techniques used by financial institutions to analyze complex data
streams. Joining Rigetti in this work is Amazon Web Services (AWS),
Imperial College London, and Standard Chartered.
Financial institutions need to continuously interpret complex
data streams to extract information necessary for providing
accurate credit risk evaluation, managing market-making services,
and predicting emissions in the context of green finance, among
other things. Classical machine learning techniques used to assist
and provide insights to these services have limitations as these
data streams are, in general, complex. Combining quantum computing
with classical machine learning methodology could offer more
powerful resources for processing these data streams, given the
potential for quantum computers to process some types of
information more efficiently than with classical resources
alone.
By leveraging Rigetti’s quantum computer and software, Standard
Chartered’s datasets and classical benchmarks, Imperial College
London’s expertise on classical machine learning models for data
streams, and AWS classical high performance computing resources,
the consortium will aim to address the following research
objectives: (1) further develop quantum signature kernels and
quantum-enhanced feature maps, (2) benchmark the results against
classical machine learning methods for streamed data, and (3) build
and study quantum algorithms for computing signatures and signature
kernels for long and high-dimensional data streams efficiently.
The signature, a centerpiece of rough path theory, provides a
top-down description of a stream that filters out local superfluous
and noisy information of a stream while retaining essential
information. Its algebraic and analytic properties make it a
natural universal feature map for streamed data. Significant
efforts have been made by members of the Imperial team to scale
signature methods to high dimensional streams. One elegant solution
is provided by signature kernels, which allows one to benefit from
the advantages of working with infinitely many signature features
without some of the concomitant drawbacks. Adding a quantum element
has the potential to improve upon the classical signature kernel
methods. These enhanced capabilities could provide a route to
demonstrating a commercial application of quantum computing for
finance and enable financial institutions to improve their
efficiency through cost reduction and enhanced productivity.
“Developing quantum-enhanced machine learning solutions could
enable financial institutions to use the full capability of
NISQ-era computing, and has the potential to accelerate our work
towards narrow quantum advantage, the point at which a quantum
computer outperforms the best classical resources,” said Rigetti
CEO Dr. Subodh Kulkarni. “Collaborating with leading UK financial
institutions, AWS, and universities should give us the insight we
need to advance the development of quantum applications for the
finance sector, and many other industries with complex
datasets.”
“The future of quantum computing will be built on the
combination of quantum with classical compute infrastructure as
part of a unified, cloud-based environment. This project is a great
example of leveraging classical HPC resources with the aim to
accelerate innovation in quantum machine learning algorithms – an
important step as we move toward quantum advantage,” said Richard
Moulds, general manager, Amazon Braket at AWS. “This initiative
should not only benefit the finance sector, but could also
encourage other industries to benchmark new machine learning models
and continue to improve quantum algorithm performance.”
“Combining quantum technologies with rough paths techniques has
the potential to produce more scalable signal processing algorithms
for complex financial data streams. Making the implementation open
access is crucial to ensure further development of these tools both
in academia and industry,” said Dr. Cristopher Salvi, Lecturer in
Mathematics and Machine Learning at Imperial College London. "The
outcomes of our joint work can help strengthen the UK's efforts in
quantum computing research.”
“Quantum computing, like previous and current major advancements
in technology, is poised to deliver extensive advantages while
simultaneously causing significant disruptions to established
business processes. This is why it’s important for companies to
future-proof themselves by adopting this new technology from an
early stage. Our collaboration with Rigetti, Imperial College
London, and AWS gives us access to high-performance computational
resources and quantum algorithm expertise that could strengthen our
position as an industry leader in a future quantum-ready economy,”
said Craig Corte, Global Head of Digital Channels and Client Data
Analytics at Standard Chartered.
The project began on January 1, 2024 and will last 18
months.
About RigettiRigetti is a pioneer in full-stack
quantum computing. The Company has operated quantum computers over
the cloud since 2017 and serves global enterprise, government, and
research clients through its Rigetti Quantum Cloud Services
platform. The Company’s proprietary quantum-classical
infrastructure provides high performance integration with public
and private clouds for practical quantum computing. Rigetti has
developed the industry’s first multi-chip quantum processor for
scalable quantum computing systems. The Company designs and
manufactures its chips in-house at Fab-1, the industry’s first
dedicated and integrated quantum device manufacturing facility.
Learn more at www.rigetti.com.
About Imperial College LondonImperial College
London is a global top ten university with a world-class
reputation. The College's 22,000 students and 8,000 staff are
working to solve the biggest challenges in science, medicine,
engineering and business. The Research Excellence Framework (REF)
2021 found that it has a greater proportion of world-leading
research than any other UK university, it was named University of
the Year 2022 according to The Times and Sunday Times Good
University Guide, University of the Year for Student Experience
2022 by the Good University Guide, and awarded a Queen’s
Anniversary Prize for its COVID-19 response. The Department of
Mathematics at Imperial College London is one of the largest
departments of Mathematics in the UK and is a leading international
centre for research and teaching, ranking among the very best UK
Mathematics Departments. The Department’s research strategy aligns
synergistically with Imperial’s academic strategy and its research
ethos, which emphasises working across disciplines, quantitative
approaches to research, translating ideas into impact, and
collaboration with stakeholders locally, nationally, and
internationally. Learn more at https://www.imperial.ac.uk/.
About Standard CharteredWe are a leading
international banking group, with a presence in 53 of the world’s
most dynamic markets and serving clients in a further 64. Our
purpose is to drive commerce and business transformation through
our unique diversity, and our heritage and values are expressed in
our brand promise, here for good.
Standard Chartered PLC is listed on the London and Hong Kong
Stock Exchanges.
Cautionary Language Concerning Forward-Looking
StatementsCertain statements in this communication may be
considered “forward-looking statements” within the meaning of the
federal securities laws, including but not limited to, expectations
with respect to the Company’s business and operations, including
its expectations related to the Innovate UK grant as part of the
Feasibility Studies in Quantum Computing Applications competition
and work with AWS, Imperial College London and Standard Chartered
to use quantum computing to improve current classical machine
learning techniques used by financial institutions to analyze
complex data streams. Forward-looking statements generally relate
to future events and can be identified by terminology such as
“commit,” “may,” “should,” “could,” “might,” “plan,” “possible,”
“intend,” “strive,” “expect,” “intend,” “will,” “estimate,”
“believe,” “predict,” “potential,” “pursue,” “aim,” “goal,”
“outlook,” “anticipate,” “assume,” or “continue,” or the negatives
of these terms or variations of them or similar terminology. Such
forward-looking statements are subject to risks, uncertainties, and
other factors which could cause actual results to differ materially
from those expressed or implied by such forward-looking statements.
These forward-looking statements are based upon estimates and
assumptions that, while considered reasonable by Rigetti and its
management, are inherently uncertain. Factors that may cause actual
results to differ materially from current expectations include, but
are not limited to: Rigetti’s ability to achieve milestones,
technological advancements, including with respect to its roadmap,
help unlock quantum computing, and develop practical applications;
the ability of Rigetti to complete ongoing negotiations with
government contractors successfully and in a timely manner; the
potential of quantum computing; the ability of Rigetti to obtain
government contracts and the availability of government funding;
the ability of Rigetti to expand its QCS business; the success of
Rigetti’s partnerships and collaborations; Rigetti’s ability to
accelerate its development of multiple generations of quantum
processors; the outcome of any legal proceedings that may be
instituted against Rigetti or others; the ability to continue to
meet stock exchange listing standards; costs related to operating
as a public company; changes in applicable laws or regulations; the
possibility that Rigetti may be adversely affected by other
economic, business, or competitive factors; Rigetti’s estimates of
expenses and profitability; the evolution of the markets in which
Rigetti competes; the ability of Rigetti to execute on its
technology roadmap; the ability of Rigetti to implement its
strategic initiatives, expansion plans and continue to innovate its
existing services; disruptions in banking systems, increased costs,
international trade relations, political turmoil, natural
catastrophes, warfare (such as the ongoing military conflict
between Russia and Ukraine and related sanctions and the state of
war between Israel and Hamas and related threat of a larger
regional conflict), and terrorist attacks; and other risks and
uncertainties set forth in the section entitled “Risk Factors” and
“Cautionary Note Regarding Forward-Looking Statements” in the
Company’s Annual Report on Form 10-K for the year ended December
31, 2022 and Quarterly Reports on Form 10-Q for the quarters ended
March 31, 2023, June 30, 2023 and September 30, 2023, and other
documents filed by the Company from time to time with the SEC.
These filings identify and address other important risks and
uncertainties that could cause actual events and results to differ
materially from those contained in the forward-looking statements.
Forward-looking statements speak only as of the date they are made.
Readers are cautioned not to put undue reliance on forward-looking
statements, and the Company assumes no obligation and does not
intend to update or revise these forward-looking statements other
than as required by applicable law. The Company does not give any
assurance that it will achieve its expectations.
Media Contactpress@rigetti.com
Rigetti Computing (NASDAQ:RGTIW)
過去 株価チャート
から 7 2024 まで 8 2024
Rigetti Computing (NASDAQ:RGTIW)
過去 株価チャート
から 8 2023 まで 8 2024