HNCDI set to boost UK productivity, innovation and economic growth

Progress report shows how the HNCDI is enabling businesses to adopt artificial intelligence (AI) and quantum computing to overcome industrial challenges.

A new report confirms that the Hartree National Centre for Digital Innovation (HNCDI) is generating increasingly substantial economic and societal benefits for the UK across many sectors.

Launched in 2021, the HNCDI is a £210 million, five-year collaboration between the Science and Technology Facilities Council’s (STFC) Hartree Centre and IBM, located at STFC’s Daresbury Laboratory, at Sci-Tech Daresbury.

It is enabling businesses to adopt the skills and necessary digital technologies, such as AI and quantum computing, to overcome a range of industrial challenges, from precision medicine to flood risks.

Solving industry challenges with digital adoption

The HNCDI progress report completed by technopolis showcases its progress made so far, 18 months into the programme.

Outlining both the successes and challenges for building up the HNCDI in its first 18 months, the report demonstrates successful case studies, indicating the progress achieved across each of the HNCDI’s workstreams. Each workstream addresses four key stages of digital adoption:

  • explore: applying digital and AI technologies to industry challenges
  • excelerate: embedding AI solutions across UK industry
  • emerging technology: driving future investment decisions into emerging technologies
  • explain: application training in digital technologies

Positive impacts

The positive impacts section in the report confirm that, as of December 2022, the HNCDI programme has:

  • launched 44 projects across the emerging technology, explore and excelerate research and development workstreams
  • engaged 22 partner organisations across these three workstreams, guaranteeing £157,080 in contributions from industry collaborations
  • achieved 10 peer-reviewed publications, with two patent submissions in progress
  • engaged with 544 individuals from 239 organisations through its free training to industry, under the training workstream, explain

Reducing risk

Kate Royse, Director of the STFC Hartree said:

At the Hartree Centre, we want to support UK businesses by reducing the risk of exploring and adopting the new digital technologies they need to solve important industry challenges.

It is therefore great to know that the HNCDI is already making substantial progress to help businesses upskill their staff, explore new technologies and embed new products and processes that take advantage of advanced digital technologies.

Whatever the size of a business or organisation, we have a successful track record working with industry, from start-ups to large corporates, and public sector organisations.

It is really important to us that support for digital technology adoption reaches as many companies across the UK as possible, putting digital innovation at the heart of our future economic sustainability.

Supporting local businesses across the UK

With this in mind, the progress report also highlights the recent announcement of the Hartree Centre SME hubs.

Hartree Centre small and medium-sized enterprise (SME) hubs were set up to enable regional SMEs across the UK to adopt advanced digital technologies to boost their competitiveness and growth.

Cardiff University, Newcastle University and Ulster University were selected to set up the hubs. They will provide support and promote knowledge exchange to enable their local SMEs to upskill and unlock their potential through digital transformation.

Case studies highlighted in the HNCDI progress report

AI powered precision medicine for inflammatory bowel disease

Biotech company REPROCELL accelerated the development of machine learning algorithms used in precision medicine by working with the HNCDI on an AI-powered platform capable of simplifying complicated medical datasets.

Through this, pharmaceutical companies can streamline new effective drug treatments quickly and cost effectively for those suffering from inflammatory bowel disease, with the potential to expand out into cancer therapies.

Quantum machine learning strategies for accelerated drug discovery

The Hartree Centre and IBM investigated the potential of quantum computing to accelerate the drug discovery process and reduce costs. This was done through researching a specific technique that screens digital databases of molecules to identify structures most likely to bind to a drug target.

They found that quantum machine learning strategies outperformed both classical high performance computing algorithms and the deep learning methodologies (currently state of the art in drug discovery). The quantum machine learning strategies support calculations at exponentially higher-orders of complexity to increase efficiency and accuracy.

The team published a paper on the results earlier this year, and is now discussing follow-on projects with UK pharmaceutical companies.

Using AI to map the risk of flooding

Mapping the risk of climate events requires the analysis of comprehensive datasets, usually done through a time-consuming, semi-manual process.

At the HNCDI, the team developed an AI machine learning algorithm, through which they were able to speed up the process of identifying past and current flood events using satellite data.

As a result, the team successfully developed a platform that can map climate events and improve the resilience of UK infrastructure, enhancing the capability to address damage and prepare crisis responses across multiple climate applications.

NSG Pilkington embraces data science

NSG Pilkington manufactures and processes glass for the architectural and automotive sectors.

Collaborating with the Hartree Centre on two materials discovery projects inspired a company-wide recognition of potential data science applications. NSG piloted a programme to train their staff in data science through the HNCDI EXPLAIN training programme.

From materials science to legal teams, NSG staff registered for 61 courses, and reported improved confidence in framing and communicating their requirements to data science experts. They also reported feeling better equipped to tackle internal data science challenges.

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