AI Case Studies, How AI is being used in industry and research

AI in Research & Higher Education

AI in Research & Higher Education Higher education is at the frontlines of major global challenges, training innovators in AI, accelerated computing, and data science. At the same time, institutions need to meet the demand for more flexible, accessible education options. The ability to handle large workloads, increase efficiency, and lower operational costs with centralised infrastructure and computational excellence is key and this can be delivered in any learning environment by using GPU-accelerated AI and HPC, to enable researchers to leverage modelling, simulation, and experimental datasets to address even the biggest challenges.

Published 27 FEB 2023

Fathom Global

The global leader in flood and climate risk technology.

Updated 11 JAN 2023

King’s College London

King’s College London is bringing artificial intelligence in medical imaging allowing the results gained from X-rays, CT or MRI scans to be delivered immediately at the time of the patient-doctor interaction.

Published 31 MAY 2022

inooLabs

Using Natural Language Processing inooLabs has built a product which delivers information to students on any given topic from multiple sources in a simple manner.

Published 10 MAR 2022

University of Liverpool

Using DGX A100 to map and understand molecules

Published 15 JAN 2021

EnvirometriX and OpenGeoHub

Learn how OpenGeoHub and EnvirometriX pioneered a global predictive vegetation and soil mapping system using AI technology.

AI for the Energy Industry

Energy touches every aspect of modern society, from our personal lives to impacting world economies. Today, the industry faces challenges in exploring new resources, reducing costs, maintaining safe conditions for workers and communities, and ensuring reliable energy delivery to customers. There are numerous ways that GPU-accelerated systems can help address these challenges including enhancing the performance of complex geophysical and engineering applications to reduce time to results. The high compute power, massively paralleled processors and high-speed memory of GPUs allow oil and gas companies to visualise and analyse petabytes of well location data in milliseconds, implement advanced algorithms to locate faults in underground structure and use deep learning training on raw seismic trace data to accelerate exploration and discover faults in geology.

AI for the Finance Industry

Financial services business face a growing number of challenges - massive datasets, perpetual market fluctuations, the need for swift analysis and rising demand for personalised assistance. Intelligent GPU-accelerated technologies can address critical challenges within the modern financial services industry allowing institutions to boost risk management, make better data-backed decisions, increase security and reduce fraud - all whilst enhancing customer experiences with advances such as natural language processing (NLP) being implemented to better tailor customer interactions.

Published 12 JAN 2024

Quantum Qube

Discover how Scan helped Quantum Qube to model the trading markets using statistical learning.

Published 22 MAR 2021

Cognitiv+

With Cognitiv+ Out of the Box Solution, it’s easy to analyse your documents, extract key provisions, save time and mitigates risks involved in document review.

Published 19 FEB 2021

TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

AI for the Healthcare Industry

The world’s leading health organisations are equipping their doctors and scientists with GPU-accelerated compute systems to drive AI adoption - helping them transform lives and the future of research. With AI, they can tackle interoperable data, meet the increasing demand for personalised medicine and next-generation VR-enabled operating theatres. It is also being used to increase accuracy and reduce diagnosis times, freeing consultants up to perform more surgeries, and accelerate areas such as image analysis and drug discovery.

Updated 11 JAN 2023

King’s College London

King’s College London is bringing artificial intelligence in medical imaging allowing the results gained from X-rays, CT or MRI scans to be delivered immediately at the time of the patient-doctor interaction.

Published 26 APR 2022

Peptone

Accelerating protein-based drug discovery using computational molecular physics

Published 10 MAY 2021

Bering, iCAIRD and NHSGCC

Learn how AI-powered chest X-ray image diagnosis technology is being adapted to help early identification of COVID-19 cases.

Published 28 FEB 2021

Vet AI

Joii, which was developed in accordance with world-class vets, enables pet owners to make the best choice for their dog or cat.

Published 19 FEB 2021

TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

AI for Manufacturing

The most progressive industrial companies in the world are implementing GPU-accelerated technologies to deploy large-scale AI initiatives. This enables deep learning and AI at industrial scale, letting you take advantage of unprecedented amounts of sensor and operational data to bring down labour costs, reduce product defects, shorten unplanned downtimes, improve transition times and increase production speed. AI -powered visual analytics is also being used to improve employ safety and compliance when using personal protection equipment (PPE).

Published 19 FEB 2021

TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

AI for the Robotics Industry

From smart automation in manufacturing to last-mile delivery, robots are becoming more ubiquitous in everyday life. Today's robots can do more than just perform tasks - they can learn, adapt and evolve using capabilities such as machine learning, computer vision, navigation and more. The AI in robots not only helps to learn the model to perform certain tasks but also makes machines more intelligently react to different scenarios, making them much more flexible to deal with everyday situations.

Published 4 DEC 2023

Oxford Robotics Institute

Emerging Oscillatory Latent-Space Dynamics for Sensorimotor Control.

Published 2 MAY 2023

Oxford Robotics Institute

Touching a NeRF: leveraging neural radiance fields for tactile sensory data generation.

Published 2 MAY 2023

Oxford Robotics Institute

Efficient skill acquisition for complex manipulation tasks in obstructed environments.

Published 14 JULY 2022

Oxford Robotics Institute

Leveraging Translational Invariance of the Fourier Transform for Efficient and Accurate Radar Odometry

Published 30 JUNE 2022

Oxford Robotics Institute

Next Steps: Learning a Disentangled Gait Representation for Versatile Quadruped Locomotion

Published 13 MAY 2021

Oxford Robotics Institute

Learning to understand objects in images without supervision for robotics applications.

AI in Transportation

Autonomous vehicles are transforming the way we live, work and play, creating safer and more efficient roads. With the power of GPU-accelerated systems embedded within vehicles, AI models can be deployed to improve road safety, increase productivity and develop greener transportation. Embedded platforms can simultaneously process data from a wide array of sensors, constantly collecting vital data for building a robust autonomous driving training library spanning a wide variety of traffic scenarios and conditions - essential for the development of safe self-driving vehicles.

Published 22 MAY 2022

Gaist

Using AI to understand the condition of highway infrastructure and assets and enable detailed lifecycle planning. Read more

Published 19 FEB 2021

TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

AI for the Surveillance Industry

Surveillance using multiple sensors at the edge connected to AI-powered analytics has the ability to influence outcomes in a number of environments - retail, warehousing, logistics and entertainment. Leading organisations are leveraging AI to reduce shrinkage, improve forecasting, automate warehouse logistics, determine in-store promotions and real-time pricing, deliver personalisation and recommendations to customers, and deliver better experiences both in stores, theatres, casinos and more.

AI for Smart Cities

AI has the ability to deliver new ways to create more sustainable cities, maintain infrastructure and improve public services for residents and communities. It all starts with the ability to gather data from trillions of sensors and other IoT devices and extract actionable insights in real time - to improve operational efficiency, resource allocation, disaster response and perform realtime traffic flow analysis and re-routing to ensure minimal commuter delays and optimal public transport performance.

Published 19 FEB 2021

TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

AI for the Retail Sector

Leading retailers are leveraging AI to reduce shrinkage, improve forecasting, automate warehouse logistics, determine in-store promotions and real-time pricing, enable customer personalisation and recommendations, and deliver better shopping experiences—both in stores and online. Understanding customer behaviour has never been more critical for retailers looking to drive growth. AI applications powered by video analytics can give retailers the same visibility into customer behaviour in stores as they currently have online.

Published 3 NOV 2021

Interaction Care

Interaction Care uses a unique combination of technologies to help our clients proactively protect their customers and employees on site from high-risk situations that could jeopardise their health and safety.

Published 19 FEB 2021

TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

AI in Space Research

AI is enabling an exciting new era of enhanced capabilities and agencies such as NASA and ESA are embracing this to explore and apply new methods to critical challenges in earth science, space exploration and planetary stewardship. With our planet’s challenges mounting, data from satellites is enabling the investigation of phenomena such as floods, superstorms and global wildfires, with the ultimate aim of prediction and forewarning - for the benefit of all humankind.

Published 18 DEC 2023

FDL Europe 2023 - Foundational Model Adaptors for Disasters

Can LLMs collate and interpret information on emerging and historic disasters, to improve response and analysis?

Published 18 DEC 2023

FDL Europe 2023 - Generalisable SSL Synthetic Aperture Radar

Can foundation models for SAR data address a range of downstream tasks and deliver results across time and space?

Published 18 DEC 2023

FDL Europe 2023 - Live Twin for Space Weather

Can machine learning onboard space observatories and on Earth help build a near real-time warning system for potentially dangerous solar weather events?

Published 12 JAN 2023

FDL Europe 2022 - Live Twin Hydrological Models

Can data-driven ML models, informed by real-time satellite data build an end-to-end flood prediction system?

Published 12 JAN 2023

FDL Europe 2022 - Live Twin Aerosols

Understanding how aerosols and other emissions from extreme fires affect weather and climate.

Published 12 SEP 2022

FDL Europe 2021 – World Food Embeddings

Researching whether AI and satellite images can be used to track the world’s food supply.

Published 12 SEP 2022

FDL Europe 2021 - Extreme Event Hot Spots

Can onboard AI technology be deployed on satellites to improve observations on extreme weather events?

Published 7 JULY 2021

FDL Europe 2020 - Clouds and Aerosols

The project team used observations from a geo-stationary satellite over the Southern Atlantic Ocean, combined with data from ECMWF and IMERG estimates to better understand the aerosol impact on cloud structure through the application of multiple machine learning methods.

Published 7 JULY 2021

FDL Europe 2020 - Digital Twin Earth

The DTE project set out to discover whether machine learning can learn forecast precipitation by fusing simulated satellite weather data with physical model data, to offer a low-cost alternative to expensive simulation infrastructure.

AI Case Studies

AI in Research & Higher Education

Fathom Global

King’s College London

inooLabs

University of Liverpool

EnvirometriX and OpenGeoHub

AI for the Energy Industry

AI for the Finance Industry

Quantum Qube

Cognitiv+

TurinTech

AI for the Healthcare Industry

King’s College London

Peptone

Bering, iCAIRD and NHSGCC

Vet AI

TurinTech

AI for Manufacturing

TurinTech

AI for the Robotics Industry

Oxford Robotics Institute

Oxford Robotics Institute

Oxford Robotics Institute

Oxford Robotics Institute

Oxford Robotics Institute

Oxford Robotics Institute

AI in Transportation

Gaist

TurinTech

AI for the Surveillance Industry

AI for Smart Cities

TurinTech

AI for the Retail Sector

Interaction Care

TurinTech

AI in Space Research

FDL Europe 2023 - Foundational Model Adaptors for Disasters

FDL Europe 2023 - Generalisable SSL Synthetic Aperture Radar

FDL Europe 2023 - Live Twin for Space Weather

FDL Europe 2022 - Live Twin Hydrological Models

FDL Europe 2022 - Live Twin Aerosols

FDL Europe 2021 – World Food Embeddings

FDL Europe 2021 - Extreme Event Hot Spots

FDL Europe 2020 - Clouds and Aerosols

FDL Europe 2020 - Digital Twin Earth

We're adding new case studies all the time...