Advances in Artificial Intelligence (AI) and Machine Learning (ML) have enabled the scientific community to advance the frontiers of knowledge by learning from complex, large-scale experimental datasets. With the scientific community generating huge amounts of data from observatories to large-scale experimental facilities, AI for Science at Exascale is on the horizon. However, in the absence of systematic approaches to evaluate AI models and AI algorithms at exascale, the AI for Science community, and, in fact, the general AI community, are facing a major barrier ahead. This proposal aims to setup a working group with an overarching goal of identifying the scope and plans for developing AI benchmarks to enable the development of AI for Science at Exascale, in ExCALIBUR - Phase II. Although AI Benchmarking is becoming a well-explored topic, a number of issues are still to be addressed, including, but not limited to: a) There are no efforts aimed at AI benchmarking at exascale, particularly for science; b) A range of scientific problems involving real-world large-scale scientific datasets, such as those from experimental facilities or observatories, are largely ignored in benchmarking; and c) It is worth having benchmarks to serve as a catalogue of techniques offering template solutions to different types of scientific problems. In this proposal, when scoping the development of an AI benchmark suite, we will aim to address these issues. In developing a vision, a scope and a plan for this significant challenge, the working group will not only engage with the community of scientists from a number of disciplines, and industry, but will also engineer a scalable and functional AI benchmark, so as to learn and embed the practical aspects of developing an AI benchmark into the vision, scope, and plan. The exemplary benchmark will focus on removing noise from images, which is a common issue across multiple disciplines including, life sciences, material sciences and astronomy. The specific problems from each of these disciplines are, removing noise from cryogenic electron microscopic (cryo-em) datasets, denoising X-Ray tomographic images, and minimising the noise from weak lensing images, respectively.

The current global fashion supply chain is characterised by its lack of transparency, forced labour, poor working conditions, unequal power relationships and overproduction caused by fast fashion. Lacking ethics, the global fashion supply chain is also highly polluting. The total footprint of clothing in use in the UK, including global and territorial emissions, was 26.2 million tonnes CO2 in 2016, up from 24 million tonnes in 2012 (equivalent to over a third of household transport emissions). The Textiles Circularity Centre (TCC) proposes materials security for the UK by circularising resource flows of textiles. This will stimulate innovation and economic growth in the UK textile manufacturing, SME apparel and creative technology sectors, whilst reducing reliance on imported and environmentally and ethically impactful materials, and diversifying supply chains. The TCC will provide underpinning research understanding to enable the transition to a more circular economy that supports the brand 'designed and made in the UK'. To enact this vision, we will catalyse growth in the fashion and textiles sector by supporting the SME fashion-apparel community with innovations in materials and product manufacturing, access to circular materials through supply chain design, and consumer experiences. Central to our approach is to enable consumers to be agents of change by engaging them in new cultures of consumption. We will effect a symbiosis between novel materials manufacturing and agentive consumer experiences through a supply chain design comprised of innovative business models and digital tools. Using lab-proven biotechnology, we will transform bio-based waste-derived feedstock (post-consumer textiles, crop residues, municipal solid waste) into renewable polymers, fibres and flexible textile materials, as part of a CE transition strategy to replace imported cotton, wood pulp and synthetic polyester fibres and petrochemical finishes. We will innovate advanced manufacturing techniques that link biorefining of organic waste, 3D weaving, robotics and additive manufacturing to circular design and produce flexible continuous textiles and three-dimensional textile forms for apparel products. These techniques will enable manufacturing hubs to be located on the high street or in local communities, and will support SME apparel brands and retailers to offer on-site/on-demand manufacture of products for local customisation. These hubs would generate regional cultural and social benefits through business and related skills development. We will design a transparent supply chain for these textiles through industrial symbiosis between waste management, farming, bio-refinery, textile production, SME apparel brands, and consumer stakeholders. Apparel brands will access this supply chain through our digital 'Biomaterials Platform', through which they can access the materials and data on their provenance, properties, circularity, and life cycle extension strategies. Working with SME apparel brands, we will develop an in-store Configurator and novel affective and creative technologies to engage consumers in digitally immersive experiences and services that amplify couplings between the resource flow, human well being and satisfaction, thus creating a new culture of consumption. This dematerialisation approach will necessitate innovation in business models that add value to the apparel, in order to counter overproduction and detachment. Consumers will become key nodes in the circular value chain, enabling responsible and personalised engagement. As a human-centred design led centre, TCC is uniquely placed to generate these innovations that will catalyse significant business and skills growth in UK textile manufacturing, SME fashion-apparel, and creative technology sectors, and drastically reduce waste and carbon emissions, and environmental and ethical impacts for the textiles sector.

Public opinion on complex scientific topics can have dramatic effects on industrial sectors (e.g. GM crops, fracking, global warming). In order to realise the industrial and societal benefits of Autonomous Systems, they must be trustworthy by design and default, judged both through objective processes of systematic assurance and certification, and via the more subjective lens of users, industry, and the public. To address this and deliver it across the Trustworthy Autonomous Systems (TAS) programme, the UK Research Hub for TAS (TAS-UK) assembles a team that is world renowned for research in understanding the socially embedded nature of technologies. TASK-UK will establish a collaborative platform for the UK to deliver world-leading best practices for the design, regulation and operation of 'socially beneficial' autonomous systems which are both trustworthy in principle, and trusted in practice by individuals, society and government. TAS-UK will work to bring together those within a broader landscape of TAS research, including the TAS nodes, to deliver the fundamental scientific principles that underpin TAS; it will provide a focal point for market and society-led research into TAS; and provide a visible and open door to engage a broad range of end-users, international collaborators and investors. TAS-UK will do this by delivering three key programmes to deliver the overall TAS programme, including the Research Programme, the Advocacy & Engagement Programme, and the Skills Programme. The core of the Research Programme is to amplify and shape TAS research and innovation in the UK, building on existing programmes and linking with the seven TAS nodes to deliver a coherent programme to ensure coverage of the fundamental research issues. The Advocacy & Engagement Programme will create a set of mechanisms for engagement and co-creation with the public, public sector actors, government, the third sector, and industry to help define best practices, assurance processes, and formulate policy. It will engage in cross-sector industry and partner connection and brokering across nodes. The Skills Programme will create a structured pipeline for future leaders in TAS research and innovation with new training programmes and openly available resources for broader upskilling and reskilling in TAS industry.