̽��ֱ�� of Cambridge - Department of Computer Science and Technology

Hundreds of A-level students see grades rise and secure places at top universities following Cambridge's STEM SMART initiative

sb726 — Mon, 07 Apr 2025 07:30:17 +0000

UCAS evaluation shows the most engaged sixth formers saw their results jump by a grade on average, were up to four times as successful in achieving an A*, and around twice as successful in securing an Oxbridge place.

Turbocharging the race to protect nature and climate with AI

lw355 — Sun, 06 Apr 2025 17:00:51 +0000

Rebalancing the planet must happen faster. Cambridge researchers are using AI to help.

Opinion: AI can help us heal the planet

lw355 — Fri, 04 Apr 2025 16:23:55 +0000

AI can do in seconds what might take a team of experts a year. This is why we must harness it to reverse the damage we’ve done to the planet. Anil Madhavapeddy explains.

Nobel laureate and Cambridge ̽��ֱ�� alumnus Sir Demis Hassabis heralds a new era of AI drug discovery at 'digital speed'

sb726 — Mon, 24 Mar 2025 14:02:09 +0000

Google DeepMind co-founder tells Cambridge audience 'digital biology’ could reduce the amount of time it takes to identify new drugs from years to weeks.

Fully AI driven weather prediction system could start revolution in forecasting

sc604 — Thu, 20 Mar 2025 15:56:54 +0000

̽��ֱ��system, Aardvark Weather, has been supported by the Alan Turing Institute, Microsoft Research and the European Centre for Medium Range Weather Forecasts. It provides a blueprint for a new approach to weather forecasting with the potential to transform current practices. The results are reported in the journal Nature.

“Aardvark reimagines current weather prediction methods offering the potential to make weather forecasts faster, cheaper, more flexible and more accurate than ever before, helping to transform weather prediction in both developed and developing countries,” said Professor Richard Turner from Cambridge’s Department of Engineering, who led the research. “Aardvark is thousands of times faster than all previous weather forecasting methods.”

Current weather forecasts are generated through a complex set of stages, each taking several hours to run on powerful supercomputers. Aside from daily usage, the development, maintenance and use of these systems require significant time and large teams of experts.

More recently, research by Huawei, Google, and Microsoft has shown that one component of the weather forecasting pipeline, the numerical solver (which calculates how weather evolves over time), can be replaced with AI, resulting in faster and more accurate predictions. This combination of AI and traditional approaches is now being used by the European Centre for Medium Range Weather Forecasts (ECMWF).

But with Aardvark, researchers have replaced the entire weather prediction pipeline with a single, simple machine learning model. ̽��ֱ��new model takes in observations from satellites, weather stations and other sensors and outputs both global and local forecasts.

This fully AI driven approach means predictions that were once produced using many models – each requiring a supercomputer and a large support team to run – can now be produced in minutes on a desktop computer.

When using just 10% of the input data of existing systems, Aardvark already outperforms the United States national GFS forecasting system on many variables. It is also competitive with United States Weather Service forecasts that use input from dozens of weather models and analysis by expert human forecasters.

“These results are just the beginning of what Aardvark can achieve,” said first author Anna Allen, from Cambridge’s Department of Computer Science and Technology. “This end-to-end learning approach can be easily applied to other weather forecasting problems, for example hurricanes, wildfires, and tornadoes. Beyond weather, its applications extend to broader Earth system forecasting, including air quality, ocean dynamics, and sea ice prediction.”

̽��ֱ��researchers say that one of the most exciting aspects of Aardvark is its flexibility and simple design. Because it learns directly from data it can be quickly adapted to produce bespoke forecasts for specific industries or locations, whether that's predicting temperatures for African agriculture or wind speeds for a renewable energy company in Europe.

This contrasts to traditional weather prediction systems where creating a customised system takes years of work by large teams of researchers.

“ ̽��ֱ��weather forecasting systems we all rely on have been developed over decades, but in just 18 months, we’ve been able to build something that’s competitive with the best of these systems, using just a tenth of the data on a desktop computer,” said Turner, who is also Lead Researcher for Weather Prediction at the Alan Turing Institute.

This capability has the potential to transform weather prediction in developing countries where access to the expertise and computational resources required to develop conventional systems is not typically available.

“Unleashing AI’s potential will transform decision-making for everyone from policymakers and emergency planners to industries that rely on accurate weather forecasts,” said Dr Scott Hosking from ̽��ֱ��Alan Turing Institute. “Aardvark’s breakthrough is not just about speed, it’s about access. By shifting weather prediction from supercomputers to desktop computers, we can democratise forecasting, making these powerful technologies available to developing nations and data-sparse regions around the world.”

“Aardvark would not have been possible without decades of physical-model development by the community, and we are particularly indebted to ECMWF for their ERA5 dataset which is essential for training Aardvark,” said Turner.

“It is essential that academia and industry work together to address technological challenges and leverage new opportunities that AI offers,” said Matthew Chantry from ECMWF. “Aardvark’s approach combines both modularity with end-to-end forecasting optimisation, ensuring effective use of the available datasets."

“Aardvark represents not only an important achievement in AI weather prediction but it also reflects the power of collaboration and bringing the research community together to improve and apply AI technology in meaningful ways,” said Dr Chris Bishop, from Microsoft Research.

̽��ֱ��next steps for Aardvark include developing a new team within the Alan Turing Institute led by Turner, who will explore the potential to deploy Aardvark in the global south and integrate the technology into the Institute’s wider work to develop high-precision environmental forecasting for weather, oceans and sea ice.

Reference:
Anna Allen, Stratis Markou et al. ‘End-to-end data-driven weather prediction.’ Nature (2025). DOI: 10.1038/s41586-025-08897-0

Adapted from a media release by ̽��ֱ��Alan Turing Institute

A new AI weather prediction system, developed by researchers from the ̽��ֱ�� of Cambridge, can deliver accurate forecasts tens of times faster and using thousands of times less computing power than current AI and physics-based forecasting systems.

̽��ֱ��Alan Turing Institute

Professor Richard Turner using Aardvark Weather

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Cambridge Festival Speaker Spotlight: Dr Sam Nallaperuma-Herzberg

zs332 — Tue, 11 Mar 2025 13:39:34 +0000

Dr Sam Nallaperuma-Herzberg is a Senior Research Associate at Cambridge ̽��ֱ��’s Department of Computer Science and Technology, and a Fellow in Artificial Intelligence (AI) for Science and Society at the Accelerate Programme for Scientific Discovery.

Arm donates £3.5 million for Cambridge PhD students to study computer architecture and semiconductor design

skbf2 — Wed, 20 Nov 2024 13:05:14 +0000

̽��ֱ��first three students to be supported by the Arm donation will begin their studies at the new research centre in the autumn of 2025. They will be followed by another three students each year for the following four years.

Arm – the company building the future of computing with its global headquarters in Cambridge – is the first organisation to donate to the new CASCADE Research Centre, part of the Department of Computer Science and Technology.

“We’re very grateful to them for their generous support,” said Professor Timothy Jones, Director of the Centre. “As well as funding 15 PhD students over the next five years, Arm’s involvement is helping us realise our vision of a centre where research into addressing key challenges in this field is informed and supported by our industrial partners.This is extremely valuable to us as we work to make the Centre a destination for collaboration between companies, generating pre-competitive open-source artefacts and driving development of novel computer architectures.”

Richard Grisenthwaite, executive vice president and chief architect, Arm said: “Our long-standing commitment to the ̽��ֱ�� of Cambridge through this latest CASCADE funding highlights the vital collaboration between academia and industry as we embark on ground-breaking intent-based programming work to realize the future promise of AI through the next generation of processor designs."

“ ̽��ֱ��Centre has the potential to enable further technology innovation within the semiconductor industry and is an important part of Arm’s mission to build the future of computing.”

Jones added: "Computer architecture is a critical area of computing. It underpins today’s technologies and drives the next generation of computing systems. Here in the Department of Computer Science and Technology, we’re proud of our research and innovation in this area. And the recently published National Semiconductor Strategy underlined how vital such work is, showing that the UK is currently a leader in computer architecture."

"But to maintain this leading position, we need to invest in developing the research leaders of tomorrow. That's why we have established the new CASCADE Research Centre to fund PhD students working in this area, through support from industry. It is currently taking applications for its first cohort of students."

̽��ֱ��Centre will focus on research that addresses some of the grand challenges in computer architecture, design automation and semiconductors.

PhD students will work alongside researchers here who have expertise across the breadth of the area, encompassing the design and optimisation of general-purpose microprocessors, specialised accelerators, on-chip interconnect and memory systems, verification, compilation and networking, quantum architecture and resource estimation. This will allow them to explore the areas they are most passionate about, while addressing industry-relevant research.

Students receiving funding from Arm will be working in the general area of intent-based computing, researching systems that communicate what programs will do in the future so that the processor can make better decisions about how to execute them.

Arm was born in Cambridge in 1990 with the goal of changing the computing landscape. Its success since then in designing, architecting, and licensing high-performance, power-efficient CPUs — the 'brain' of all computers and many household and electronic devices — helped fuel the smartphone revolution and has made it a household name.

Arm has long had a research relationship with Cambridge ̽��ֱ��. Most notably, this has led to the development of new cybersecurity technology, focusing on innovative ways to design the architecture of a computer’s CPU to make software less vulnerable to security breaches.

Adapted from a news release published by the Department of Computer Science and Technology

Arm is donating £3.5 million to enable 15 PhD students over the next five years to study at CASCADE, the ̽��ֱ��'s new Computer Architecture and Semiconductor Design Centre.

Yuichiro Chino via Getty Images

Futuristic circuit board and semiconductor

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̽��ֱ�� of Cambridge alumni awarded 2024 Nobel Prize in Chemistry

Anonymous — Wed, 09 Oct 2024 10:21:22 +0000

In 2020, Hassabis and Jumper of Google DeepMind presented an AI model called AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified.

Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic.

̽��ֱ��duo received the Nobel along with Professor David Baker of the ̽��ֱ�� of Washington, who succeeded in using amino acids to design a new protein in 2003.

Sir Demis Hassabis read Computer Science as an undergraduate at Queens' College, Cambridge, matriculating in 1994. He went on to complete a PhD in cognitive neuroscience at ̽��ֱ�� College London and create the videogame company Elixir Studios.

Hassabis co-founded DeepMind in 2010, a company that developed masterful AI models for popular boardgames. ̽��ֱ��company was sold to Google in 2014 and, two years later, DeepMind came to global attention when the company achieved what many then believed to be the holy grail of AI: beating the champion player of one of the world’s oldest boardgames, Go.

In 2014, Hassabis was elected as a Fellow Benefactor and, later, as an Honorary Fellow of Queens' College. In 2024, he was knighted by the King for services to artificial intelligence.

In 2018, the ̽��ֱ�� announced the establishment of a DeepMind Chair of Machine Learning, thanks to a benefaction from Hassabis’s company, and appointed Professor Neil Lawrence to the position the following year.

“I have many happy memories from my time as an undergraduate at Cambridge, so it’s now a real honour for DeepMind to be able to contribute back to the Department of Computer Science and Technology and support others through their studies,” said Hassabis in 2018.

“It is wonderful to see Demis’s work recognised at the highest level — his contributions have been really transformative across many domains. I’m looking forward to seeing what he does next!” said Professor Alastair Beresford, Head of the Department of Computer Science and Technology and Robin Walker Fellow in Computer Science at Queens' College.

In a statement released by Google DeepMind following the announcement by the Nobel committee, Hassabis said: "I’ve dedicated my career to advancing AI because of its unparalleled potential to improve the lives of billions of people... I hope we'll look back on AlphaFold as the first proof point of AI's incredible potential to accelerate scientific discovery."

Dr John Jumper completed an MPhil in theoretical condensed matter physics at Cambridge's famous Cavendish Laboratory in 2008, during which time he was a member of St Edmund’s College, before going on to receive his PhD in Chemistry from the ̽��ֱ�� of Chicago.

"Computational biology has long held tremendous promise for creating practical insights that could be put to use in real-world experiments," said Jumper, Director of Google DeepMind, in a statement released by the company. "AlphaFold delivered on this promise. Ahead of us are a universe of new insights and scientific discoveries made possible by the use of AI as a scientific tool."

“ ̽��ֱ��whole of the St Edmund’s community joins me in congratulating our former Masters student Dr John Jumper on this illustrious achievement – the most inspiring example imaginable to our new generation of students as they go through their matriculation this week,” said St Edmund’s College Master, Professor Chris Young.

Professor Deborah Prentice, Vice-Chancellor of the ̽��ֱ�� of Cambridge: “I’d like to congratulate Demis Hassabis and John Jumper, who, alongside Geoffrey Hinton yesterday, are all alumni of our ̽��ֱ��. Together, their pioneering work in the development and application of machine learning is transforming our understanding of the world around us. They join an illustrious line-up of Cambridge people to have received Nobel Prizes – now totalling 125 individuals – for which we can be very proud.”

Article updated on 10 October 2024 to reflect that the number of Cambridge people to have received Nobel Prizes now totals 125.

Two ̽��ֱ�� alumni, Sir Demis Hassabis and Dr John Jumper, have been jointly awarded this year’s Nobel Prize in Chemistry for developing an AI model to solve a 50-year-old problem: predicting the complex structures of proteins.

I have many happy memories from my time as an undergraduate at Cambridge

Sir Demis Hassabis

Left: Demis Hassabis; Right: John Jumper

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