With the advent of deep learning and the availability of big data, it is now possible to train machine learning algorithms for a multitude of visual tasks, such as tagging personal image collections in the cloud, recognizing faces, and 3D shape scanning with phones. However, each of these tasks currently requires training a neural network on a very large image dataset specifically collected and labelled for that task. The resulting networks are good experts for the target task, but they only understand the 'closed world' experienced during training and can 'say' nothing useful about other content, nor can they be applied to other tasks without retraining, nor do they have an ability to explain their decisions or to recognise their limitations. Furthermore, current visual algorithms are usually 'single modal', they 'close their ears' to the other modalities (audio, text) that may be readily available. The core objective of the Programme is to develop the next generation of audio-visual algorithms that does not have these limitations. We will carry out fundamental research to develop a Visual Transformer capable of visual analysis with the flexibility and interpretability of a human visual system, and aided by the other 'senses' - audio and text. It will be able to continually learn from raw data streams without requiring the traditional 'strong supervision' of a new dataset for each new task, and deliver and distill semantic and geometric information over a multitude of data types (for example, videos with audio, very large scale image and video datasets, and medical images with text records). The Visual Transformer will be a key component of next generation AI, able to address multiple downstream audio-visual tasks, significantly superseding the current limitations of computer vision systems, and enabling new and far reaching applications. A second objective addresses transfer and translation. We seek impact in a variety of other academic disciplines and industry which today greatly under-utilise the power of the latest computer vision ideas. We will target these disciplines to enable them to leapfrog the divide between what they use (or do not use) today which is dominated by manual review and highly interactive analysis frame-by-frame, to a new era where automated visual analytics of very large datasets becomes the norm. In short, our goal is to ensure that the newly developed methods are used by industry and academic researchers in other areas, and turned into products for societal and economic benefit. To this end open source software, datasets, and demonstrators will be disseminated on the project website. The ubiquity of digital images and videos means that every UK citizen may potentially benefit from the Programme research in different ways. One example is smart audio-visual glasses, that can pay attention to a person talking by using their lip movements to mask out other ambient sounds. A second is an app that can answer visual questions (or retrieve matches) for text-queries over large scale audio-visual collections, such as a person's entire personal videos. A third is AI-guided medical screening, that can aid a minimally trained healthcare professional to perform medical scans.

A growing consensus identifies autonomous systems as core to future UK prosperity, but only if the present skills shortage is addressed. The AIMS CDT was founded in 2014 to address the training of future leaders in autonomous systems, and has established a strong track record in attracting excellent applicants, building cohorts of research students and taking Oxford's world-leading research on autonomy to achieve industrial impact. We seek the renewal of the CDT to cement its successes in sustainable urban development (including transport and finance), and to extend to applications in extreme and challenging environments and smart health, while strengthening training on the ethical and societal impacts of autonomy. Need for Training: Autonomous systems have been the subject of a recent report from the Royal Society, and an independent review from Professor Dame Wendy Hall and Jérôme Pesenti. Both reports emphatically underline the economic importance of AI to the UK, estimating that "AI could add an additional USD $814 billion (£630bn) to the UK economy by 2035". Both reports also highlight the urgency of training many more skilled experts in autonomy: the summary of the Royal Society's report states "further support is needed to build advanced skills in machine learning. There is already high demand for people with advanced skills, and additional resources to increase this talent pool are critically needed." In contrast with pure Artificial Intelligence CDTs, AIMS places emphasis on the challenges of building end-to-end autonomous systems: such systems require not just Machine Learning, but the disciplines of Robotics and Vision, Cyber-Physical Systems, Control and Verification. Through this cross-disciplinary training, the AIMS CDT is in a unique position to provide positive economic and societal impacts for autonomous systems by 1) growing its existing strengths in sustainable urban development, including autonomous vehicles and quantitative finance, and 2) expanding its scope to the two new application pillars of extreme and challenging environments and smart health. AIMS itself provides evidence for the strong and increasing demand for training in these areas, with an increase in application numbers from 49 to 190 over the last five years. The increase in applications is mirrored by the increase in interest from industrial partners, which has more than doubled since 2014. Our partners span all application areas of AIMS and their contributions, which include training, internships and co-supervision opportunities, will immerse our students in a variety of research challenges linked with real-world problems. Training programme: AIMS has and will provide broad cohort training in autonomous intelligent systems; theoretical foundations, systems research, industry-initiated projects and transferable skills. It covers a comprehensive range of topics centered around a hub of courses in Machine Learning; subsequent spokes provide training in Robotics and Vision, Control and Verification, and Cyber-Physical Systems. The cohort-focused training program will equip our students with both core technical skills via weekly courses, research skills via mini and long projects, as well as transferable skills, opportunities for public engagement, and training on entrepreneurship and IP. The growing societal impacts of autonomous systems demand that future AIMS students receive explicit training in responsible and ethical research and innovation, which will be provided by ORBIT. Additionally, courses on AI ethics, safety, governance and economic impacts will be delivered by Oxford's world-leading Future of Humanity Institute, Oxford Uehiro Centre for Practical Ethics and Oxford Martin Programme on Technology and Employment.

This proposal seeks funding to create a Centre for Doctoral Training (CDT) in Connected Electronic and Photonic Systems (CEPS). Photonics has moved from a niche industry to being embedded in the majority of deployed systems, ranging from sensing, biophotonics and advanced manufacturing, through communications from the chip-to-chip to transcontinental scale, to display technologies, bringing higher resolution, lower power operation and enabling new ways of human-machine interaction. These advances have set the scene for a major change in commercialisation activity where electronics photonics and wireless converge in a wide range of information, sensing, communications, manufacturing and personal healthcare systems. Currently manufactured systems are realised by combining separately developed photonics, electronic and wireless components. This approach is labour intensive and requires many electrical interconnects as well as optical alignment on the micron scale. Devices are optimised separately and then brought together to meet systems specifications. Such an approach, although it has delivered remarkable results, not least the communications systems upon which the internet depends, limits the benefits that could come from systems-led design and the development of technologies for seamless integration of electronic photonics and wireless systems. To realise such connected systems requires researchers who have not only deep understanding of their specialist area, but also an excellent understanding across the fields of electronic photonics and wireless hardware and software. This proposal seeks to meet this important need, building upon the uniqueness and extent of the UCL and Cambridge research, where research activities are already focussing on higher levels of electronic, photonic and wireless integration; the convergence of wireless and optical communication systems; combined quantum and classical communication systems; the application of THz and optical low-latency connections in data centres; techniques for the low-cost roll-out of optical fibre to replace the copper network; the substitution of many conventional lighting products with photonic light sources and extensive application of photonics in medical diagnostics and personalised medicine. Many of these activities will increasingly rely on more advanced systems integration, and so the proposed CDT includes experts in electronic circuits, wireless systems and software. By drawing these complementary activities together, and building upon initial work towards this goal carried out within our previously funded CDT in Integrated Photonic and Electronic Systems, it is proposed to develop an advanced training programme to equip the next generation of very high calibre doctoral students with the required technical expertise, responsible innovation (RI), commercial and business skills to enable the £90 billion annual turnover UK electronics and photonics industry to create the closely integrated systems of the future. The CEPS CDT will provide a wide range of methods for learning for research students, well beyond that conventionally available, so that they can gain the required skills. In addition to conventional lectures and seminars, for example, there will be bespoke experimental coursework activities, reading clubs, roadmapping activities, responsible innovation (RI) studies, secondments to companies and other research laboratories and business planning courses. Connecting electronic and photonic systems is likely to expand the range of applications into which these technologies are deployed in other key sectors of the economy, such as industrial manufacturing, consumer electronics, data processing, defence, energy, engineering, security and medicine. As a result, a key feature of the CDT will be a developed awareness in its student cohorts of the breadth of opportunity available and the confidence that they can make strong impact thereon.