NVIDIA today officially launched Cambridge-1, the United Kingdom’s
most powerful supercomputer, which will enable top scientists and
healthcare experts to use the powerful combination of AI and
simulation to accelerate the digital biology revolution and bolster
the country’s world-leading life sciences industry.
Dedicated to advancing healthcare, Cambridge-1 represents a $100
million investment by NVIDIA. Its first projects with AstraZeneca,
GSK, Guy’s and St Thomas’ NHS Foundation Trust, King’s College
London and Oxford Nanopore Technologies include developing a deeper
understanding of brain diseases like dementia, using AI to design
new drugs and improving the accuracy of finding disease-causing
variations in human genomes.
Cambridge-1 brings together decades of NVIDIA’s work in
accelerated computing, AI and life sciences, where NVIDIA Clara™
and AI frameworks are optimized to take advantage of the entire
system for large-scale research. An NVIDIA DGX SuperPOD™
supercomputing cluster, it ranks among the world’s top 50 fastest
computers and is powered by 100 percent renewable energy.
“Cambridge-1 will empower world-leading researchers in business
and academia with the ability to perform their life’s work on the
U.K.’s most powerful supercomputer, unlocking clues to disease and
treatments at a scale and speed previously impossible in the U.K.,”
said Jensen Huang, founder and CEO of NVIDIA. “The discoveries
developed on Cambridge-1 will take shape in the U.K., but the
impact will be global, driving groundbreaking research that has the
potential to benefit millions around the world.”
Cambridge-1 builds on the U.K.’s status as a global leader in
life sciences, technology and AI by providing advanced
infrastructure for current and future generations to carry out
groundbreaking research within the country.
According to a report by Frontier Economics, an economics
consulting firm, Cambridge-1 has the potential to create an
estimated value of £600 million (about $825 million) over the next
10 years.
AstraZeneca: Transforming Drug
Discovery with AI NVIDIA is collaborating with AstraZeneca
to fuel faster drug discoveries by creating a transformer-based
generative AI model for chemical structures. Transformer-based
neural network architectures, which have become available only in
the last several years, allow researchers to leverage massive
datasets using self-supervised training methods, avoiding the need
for manually labeled examples during pre-training.
The MegaMolBART drug discovery model is being used in reaction
prediction, molecular optimization and de novo molecular generation
and will optimize the drug development process. It is based on
AstraZeneca’s MolBART transformer model and is being trained on the
ZINC chemical compound database — using NVIDIA’s Megatron framework
to enable massively scaled-out training on supercomputing
infrastructure. This open-source model will be available to
researchers and developers in the NVIDIA NGC™ software catalog.
NVIDIA and AstraZeneca have a separate project on Cambridge-1
focused on the use of AI in digital pathology. In digital
pathology, significant time and money are spent annotating whole
slide images of tissue samples, to aid the search for new insights.
By using unsupervised AI algorithms trained on thousands of images,
it is possible to remove the process of annotating while
simultaneously finding potential imaging features that correlate
with drug response.
“Training AI algorithms on whole slide images is challenging in
part due to the size of the images,” said Lindsay Edwards, vice
president of Data Science and AI, Respiratory and Immunology,
BioPharmaceuticals R&D at AstraZeneca. “Working with NVIDIA on
Cambridge-1 enables us to scale our current work and develop new
methodologies advancing the use of AI in digital pathology.”
GSK: Steering Great Science with Partners for
PatientsGSK’s research and development approach includes a
focus on genetically validated targets, which are twice as likely
to become medicines and now make up more than 70 percent of its
research pipeline. To maximize the potential of these insights, GSK
has built state-of-the-art capabilities at the intersection of
human genetics, functional genomics, and artificial intelligence
and machine learning.
“Advanced technologies are core to GSK’s R&D approach and
help to unlock the potential of large, complex data through
predictive modeling at new levels of speed, precision and scale,”
said Dr. Kim Branson, senior vice president and global head of
AI-ML at GSK. “We are pleased to have the opportunity to partner
with NVIDIA to deliver on GSK’s drug discovery ambition and
contribute to the U.K.’s rich life sciences ecosystem — both aims
that have patient benefit at the centre.”
Working with partners at the cutting edge of genetics, genomics
and AI/ML can ultimately help GSK predict more about human health,
and develop better medicines that are twice as likely to succeed in
the clinic and go on to become approved therapies that benefit
patients. Access to Cambridge-1 will contribute additional
computational power and state-of-the-art AI technology to GSK’s
drug discovery process.
King’s College London & Guy’s and St Thomas’ NHS
Foundation Trust: AI-Generated Synthetic Brain Data King’s
College London and Guy’s and St Thomas’ NHS Foundation Trust are
using Cambridge-1 to teach AI models to generate synthetic brain
images by learning from tens of thousands of MRI brain scans, from
various ages and diseases. The ultimate goal is to use this
synthetic data model to gain a better understanding of diseases
like dementia, stroke, brain cancer and multiple sclerosis and
enable earlier diagnosis and treatment.
As this AI synthetic brain model can generate an infinite amount
of never-seen brain images with chosen characteristics (age,
disease, etc.), it will allow a better and more nuanced
understanding of what diseases look like, possibly enabling an
earlier and more accurate diagnosis.
“Through this partnership, we will be able to use a scale of
computational power that is unprecedented in healthcare research,”
said Professor Sebastien Ourselin, head of the School of Biomedical
Engineering & Imaging Sciences at King’s College London. “It
will be truly transformational for the health and treatment of
patients.”
This research leverages several of the U.K.’s world-leading
healthcare resources through close collaboration with the National
Health Service and the UK Biobank, one of the richest biomedical
databases in the world. King’s College London intends to share this
synthetic data model with the greater research and startup
community.
“The power of artificial intelligence in healthcare will help to
speed up diagnosis for patients, improve services such as breast
cancer screening, and support the way that we risk assess and
prioritize patients according to clinical need,” said Professor Ian
Abbs, chief executive officer of Guy’s and St Thomas’ NHS
Foundation Trust. “We are excited about our involvement in the
Cambridge-1 data center as it will enable us to be amongst the
first to benefit from these new AI capabilities — using the very
latest technology to benefit our patients, as well as manage
precious resources more efficiently.”
Oxford Nanopore: Scalable, Real-Time
GenomicsOxford Nanopore Technologies’ long-read sequencing
technology is being used in more than 100 countries to gain genomic
insights across a breadth of research areas — from human and plant
health to environmental monitoring and antimicrobial
resistance.
Oxford Nanopore deploys NVIDIA technology in a variety of
genomic sequencing platforms to develop AI tools that improve the
speed and accuracy of genomic analysis. With access to Cambridge-1,
Oxford Nanopore will be able to carry out tasks relating to
algorithm improvement in hours rather than days. These improved
algorithms will ensure improved genomic accuracy for greater
insights and quicker turnaround times in scientists’ hands.
“Harnessing the power of Cambridge-1 will help us further speed
up our algorithm development to support powerful, accurate genomic
analysis,” said Rosemary Sinclair Dokos, vice president of Product
and Programme Management at Oxford Nanopore. “This will in turn
enable the scientists using our technology on the ground to gain
more insights than ever before, across a breadth of research
areas.”
About Cambridge-1Cambridge-1 is the first
NVIDIA supercomputer designed and built for external research
access. The company will collaborate with researchers to make much
of this work available to the greater scientific community.
Featuring 80 DGX™ A100 systems integrating NVIDIA A100 GPUs,
BlueField®-2 DPUs and NVIDIA HDR InfiniBand networking, Cambridge-1
is an NVIDIA DGX SuperPOD that delivers more than 400 petaflops of
AI performance and 8 petaflops of Linpack performance. The system
is located at a facility operated by NVIDIA partner Kao Data.
Cambridge-1 is the first supercomputer NVIDIA has dedicated to
advancing industry-specific research in the U.K. The company also
intends to build an AI Center for Excellence in Cambridge featuring
a new Arm-based supercomputer, which will support more industries
across the country.
Watch the inauguration event and learn more about the
Cambridge-1 supercomputer.
About NVIDIANVIDIA’s (NASDAQ: NVDA) invention
of the GPU in 1999 sparked the growth of the PC gaming market and
has redefined modern computer graphics, high performance computing
and artificial intelligence. The company’s pioneering work in
accelerated computing and AI is reshaping trillion-dollar
industries, such as transportation, healthcare and manufacturing,
and fueling the growth of many others. More information at
https://nvidianews.nvidia.com/.
For further information,
contact:Janette CiborowskiNVIDIA
Corporation+1-734-330-8817jciborowski@nvidia.com
Certain statements in this press release including, but not
limited to, statements as to: the benefits, impact, performance,
features, and availability of our products and services;
Cambridge-1 enabling top scientists and healthcare experts to
accelerate the digital biology revolution and bolster the U.K.’s
world-leading life sciences industry; the details and impact of
NVIDIA’s collaborations with partners including AstraZeneca, GSK,
Guy’s and St Thomas’ NHS Foundation Trust, King’s College London,
and Oxford Nanopore; Cambridge-1’s potential economic value
created; the AI synthetic brain model taught by Cambridge-1
allowing a better and more nuanced understanding of what diseases
look like, possibly enabling an earlier and more accurate
diagnosis; King’s College London’s intent to share synthetic data
model with the greater research and startup community;
transformer-based neural network architectures allowing researchers
to leverage massive datasets; and access to Cambridge-1
contributing additional computational power and state-of-the-art AI
technology to GSK’s drug discovery process are forward-looking
statements that are subject to risks and uncertainties that could
cause results to be materially different than expectations.
Important factors that could cause actual results to differ
materially include: global economic conditions; our reliance on
third parties to manufacture, assemble, package and test our
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development of new products and technologies or enhancements to our
existing product and technologies; market acceptance of our
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as of the date hereof, and, except as required by law, NVIDIA
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