In the near future, the physicians will be able to monitor the patients at their homes using virtual reality tools, computer scientists are convinced. A team of researchers from Kaunas University of Technology (KTU), Lithuania, proposed a deep-learning-based method for the three-dimensional human shape reconstruction when the original figure is only partly visible. The main advantage of the method is its relatively low cost, high compression of the images obtained and easy integration with the existing virtual reality tools. The method was developed using a real-world dataset, the clinical trial is pending. The rapid advancements in computer vision and three-dimensional object representation enables the development of virtual reality tools and the expansion of their application sphere.

The manufacturing industry is the backbone of the European economy, accounting for around 20 % of the EU's GDP. AI and advanced robotics are opening new horizons in all sectors of industry, developing novel manufacturing techniques as well as reimagining the interaction between human workers and automated tools. This new Results Pack presents the results of 14 innovative Horizon 2020 projects that are reshaping AI and industry. As economies aim for sustained post-COVID recoveries, industry needs to innovate in a way that is in line with the priorities of the European Commission, in particular those laid out by the European Green Deal, a Europe Fit for the Digital Age and an Economy that Works for People. Industry 5.0 provides a coherent vision for such a future industry, focused on human centricity, sustainability and resilience.

Machines can use artificial intelligence to create photos or voice recordings that look or sound like those in real life. Researchers at the Horst Görtz Institute for IT Security at Ruhr-Universität Bochum are interested in how such artificially generated data, known as deepfakes, can be distinguished from real data. They found that real and fake voice recordings differ in the high frequencies. To date, deepfakes had mainly been analysed in image files. The new findings should help to recognise fake language recordings in the future.

How can artificial intelligence (AI) draw on principles from nature to solve complex problems? When it comes to recognizing patterns in large amounts of data, AI is faster and more capable than humans. However, it has difficulties when it has to make connections or deal with uncertainties and fuzziness. Through evolution, development, and learning, nature has developed much more practical problem-solving solutions. Yaochu Jin, the Alexander von Humboldt Professor of Artificial Intelligence at Bielefeld University since the autumn, is looking at how such principles can be transferred to AI. The Humboldt Professor will be continuing his previous research on nature-inspired artificial intelligence at Bielefeld University and looking for applications of nature-inspired and self-organized AI. 'My goal is to understand and borrow successful mechanisms from nature and transfer them into artificial intelligence for problem-solving,' says Jin.

Eye movements read by a new AI application can reveal thoughts, memories, goals -- and brain diseases. A new tool developed at the Kavli Institute for Systems Neuroscience in Norway and described in an article in Nature Neuroscience, predicts gaze direction and eye movement directly from magnetic resonance imaging (MRI) scans. The goal is to make eye tracking diagnostics a standard in brain imaging research and hospital clinics. Whenever you explore an environment or search for something, you scan the scene using continuous rapid eye movements. Your eyes also make short stops to fixate on certain elements of the scene that you want more detailed information about.

The Sustainable AI Lab of the University of Bonn is on a mission at COP26 in Glasgow While there is a growing number of research publications directed towards Artificial Intelligence (AI) for the Sustainable Development Goals, there is little research addressing, the often hidden, environmental costs of AI. The Sustainable AI Lab of the University of Bonn (Germany) addresses this topic and is present at COP26 with a unique artwork to remind people of what nature is doing and that AI is getting in the way of this. The head of the Lab, Prof. Aimee van Wynsberghe, will speak at the conference on November 10th at 11:00. AI and environmental injustice Artificial intelligence (AI) can be an important tool for sustainable development to minimize energy usage in large factories or to predict natural disasters before they happen. However, these uses can also have a downside.

Researchers at the University of Zurich have developed a new approach to autonomously fly quadrotors through unknown, complex environments at high speeds using only on-board sensing and computation. The new approach could be useful in emergencies, on construction sites or for security applications. When it comes to exploring complex and unknown environments such as forests, buildings or caves, drones are hard to beat. They are fast, agile and small, and they can carry sensors and payloads virtually everywhere. However, autonomous drones can hardly find their way through an unknown environment without a map.

From October 5 to 10, 2021, the KIT Science Week will celebrate its premiere. Researchers from all over the world, actors from politics and industry, and citizens from Karlsruhe and the region are invited to immerse into the world of artificial intelligence, AI for short. This new type of event of Karlsruhe Institute of Technology (KIT) will offer diverse access to AI and open rooms for discourse. KIT, for its part, will receive impetus for its research agenda. All these are learning systems that increasingly enter our lives. From October 5 to 10, 2021, the KIT Science Week will give experts from science, industry, politics, and culture, and in particular the interested public the opportunity to exchange ideas and opinions.

Commencing on Monday 18 October and funded through the National Skills Fund as part of the Government's Plan for Jobs, this sixteen-week AI Skills Bootcamp will provide learners with the opportunity to build both their tech and non-tech skills, therefore enabling them to be fast-tracked to an interview with an employer NEXT month the University of Huddersfield is to deliver an Artificial IntelligenceSkills Bootcampthat will connect people to employment. Commencing on Monday 18 October and funded through the National Skills Fund as part of theGovernment's Plan for Jobs, this sixteen-week AI Skills Bootcampwill provide learnerswith the opportunity to build both their tech and non-tech skills, therefore enabling them to be fast-tracked to an interview with an employer. Working with employers, local authorities and a consortium of universities, led by the Institute of Coding, this skills bootcamp will support learners from across the UK to develop personalised learning and employment plans, alongside a range of Artificial Intelligence and transferable skills. The Skills Bootcamp will combine interdisciplinary expertise from across the University including a team from Computer Science, led by Professor Richard Hill, a team from Huddersfield Business School, led by Dr Abdul Jabbar, and the University's Careers and Employability Service, led by Dave Stanbury. Professor Rupert Ward, who is leading the AI Skills Bootcamp at the University of Huddersfield, said: "The Skills Economy is rapidly evolving, both in the UK and globally. Employees are expected to reskill in response to these changes, and job applicants need to demonstrate they have in demand skills in order to be selected for interview. "Our Skills Bootcamp is being provided in response to a local and national need from employers for Artificial Intelligence capabilities.

An artificial intelligence (AI) program can spot signs of lung cancer on CT scans a year before they can be diagnosed with existing methods, according to research presented at the European Respiratory Society International Congress. Lung cancer is often diagnosed at a late stage when treatment is less likely to succeed. Researchers hope that using AI to support lung cancer screening could make the process quicker and more efficient, and ultimately help diagnose more patients at an early stage. Computerised tomography or CT scans are already used to spot signs of lung tumours, followed by a biopsy or surgery to confirm whether the tumour is malignant. But each scan involves an expert radiologist examining around 300 images and looking for signs of cancer that can be very small.