How many times must a phenomenon occur before it graduates from a coincidence to a pattern? Usually, the answer depends on how unlikely, how far from the ordinary, and how (seemingly) inexplicable the phenomenon is. The more so, the lower the threshold. I was very surprised (and pleased) to read of this year's winners of the Nobel Prize in Physics: John Hopfield, a professor of Molecular Biology and earlier of Chemistry and Biology, together with Geoffrey Hinton, a professor of Computer Science. Their affiliations name three major scientific fields, none of them being Physics!

In this white paper, I present my community effort to automatically co-design cheaper, faster and more energy-efficient software and hardware for AI, ML and other popular workloads with the help of the Collective Mind framework (CM), virtualized MLOps, MLPerf benchmarks and reproducible optimization tournaments. I developed CM to modularize, automate and virtualize the tedious process of building, running, profiling and optimizing complex applications across rapidly evolving open-source and proprietary AI/ML models, datasets, software and hardware. I achieved that with the help of portable, reusable and technology-agnostic automation recipes (ResearchOps) for MLOps and DevOps (CM4MLOps) discovered in close collaboration with academia and industry when reproducing more than 150 research papers and organizing the 1st mass-scale community benchmarking of ML and AI systems using CM and MLPerf. I donated CM and CM4MLOps to MLCommons to help connect academia and industry to learn how to build and run AI and other emerging workloads in the most efficient and cost-effective way using a common and technology-agnostic automation, virtualization and reproducibility framework while unifying knowledge exchange, protecting everyone's intellectual property, enabling portable skills, and accelerating transfer of the state-of-the-art research to production. My long-term vision is to make AI accessible to everyone by making it a commodity automatically produced from the most suitable open-source and proprietary components from different vendors based on user demand, requirements and constraints such as cost, latency, throughput, accuracy, energy, size and other important characteristics.

AI coding assistants should set stages of developing AI4SE tools that consistently produce highquality clear expectations for usage, integrate with advanced IDE capabilities results for specific coding tasks [5] [3] [4]. Academic researchers and existing extensions, use extendable backend designs, and and industry practitioners lack well-defined frameworks collect app data responsibly for downstream analyses. We propose for positioning and evaluating emerging AI coding assistants in the open questions and challenges that academia and industry should traditional programming paradigms[11] [2], while users lack clear address to realize the vision of next-generation AI coding assistants.

For decades, artificial intelligence (AI) research has coexisted in academia and industry, but the balance is tilting toward industry as deep learning, a data-and-compute-driven subfield of AI, has become the leading technology in the field. E.g.: Industry's AI successes are easy to see on the news. This article is quite interesting about how AI impacts both the academia and industry, so I just made some review or summary on it. For decades, artificial intelligence (AI) research has coexisted in academia and industry, but the balance is tilting toward industry as deep learning, a data-and-compute-driven subfield of AI, has become the leading technology in the field. E.g.: Industry's AI successes are easy to see on the news.

The Fourth Industrial Revolution, also known as Industry 4.0, represents the technological evolution from traditional manufacturing systems to cyber-physical systems, which leads to improvement of overall productivity and reductions of environmental impact, thus promoting sustainable economic development. Industry 4.0 has been driven by emerging technology developments in the field of digital twin, artificial intelligence, robotic and automation, Internet of Things (IoT), cloud computing, and edge/fog computing, and has been a hot topic in both academia and industry. The resulting big data are fed to AI-based mission-critical systems to perform effectively production monitoring, quality inspection, root cause analysis, quality prediction, and process control. The proper adoption of relevant industry 4.0 technologies should lead to significant efficiency improvement and cost reduction in various industrial sectors. The goal of this special issue is to bring together researchers and practitioners from academia and industry to provide a forum for discussing industrial automation research on smart manufacturing and machine learning.

An internationally leading robotics initiative that enables academia and industry to find innovative solutions to real world challenges, celebrated its success with a Hot Robotics Symposium hosted across three UK regions last week. The National Nuclear User Facility (NNUF) for Hot Robotics is a government funded initiative that supports innovation in the nuclear sector by making world-leading testing facilities, sensors and robotic equipment easily accessible to academia and industry. Ground-breaking, impactful research in robotics and artificial intelligence will benefit the UK's development of fusion energy as safe, low carbon and sustainable energy source in addition to adjacent sectors such as nuclear decommissioning, space, and mobile applications. Visitors to UKAEA's RACE (UK Atomic Energy Authority / Remote Applications in Challenging Environments) in Oxfordshire, the University of Bristol facility in Fenswood Farm (North Somerset), and the National Nuclear Laboratory in Cumbria, were treated to a host of robots in action, tours and a packed speaker programme. A combination of robotic manipulators, ground, aerial and underwater vehicles along with deployment robots, plant mock-ups, and supporting infrastructure, were all showcased to demonstrate the breadth of the scheme.

For many in the field of technology and computer science, the future doesn't exist without artificial intelligence. That was the topic of discussion and interest at the AI & the Future of Houston Conference in April, where professionals and science educators, including University of Houston-Victoria faculty, gathered to discuss the future of the field. The two-day conference was held April 29-30 in Houston and hosted by Houston Community College. Representatives from HCC, Houston-area universities, businesses and health care facilities and HCC students attended the event. UHV participated in the conference as sponsors and vendors, and UHV faculty also spoke at the event.

The 39th edition of the IEEE International Conference on Robotics and Automation (ICRA) took place at the Pennsylvania Convention Center in Philadelphia (USA) and online May 23-27. ICRA 2022 brought together the world's top researchers and companies to share ideas and advances in the fields of robotics and automation. Nearly 8,000 participants from academia and industry, including 4700 in person, from a total of 97 countries, joined the largest conference in robotics. Indeed, these figures reflect the evolution of the field in the last 34 years, with the last ICRA in Philadelphia (1988) only welcoming around 300 participants and a few exhibitors. "We were thrilled to see the robotics community respond so positively to the first in-person ICRA conference since the pandemic started," ICRA 2022 General Co-Chair George J. Pappas (University of Pennsylvania) commented.

As the next edition of the Swiss Robotics Day is in preparation in Lausanne, let's revisit the November 2021 edition, where the vitality and richness of Switzerland's robotics scene was on full display at StageOne Event and Convention Hall in Zurich. It was the first edition of NCCR Robotics's flagship event after the pandemic, and it surpassed the scale of previous editions, drawing in almost 500 people. You can see the photo gallery here. Welcome notes from ETH President Joël Mesot and NCCR Robotics Director Dario Floreano opened a dense conference programme, chaired by NCCR Robotics co-Director Robert Riener and that included scientific presentations from Marco Hutter (ETH Zurich), Stéphanie Lacour and Herb Shea (both from EPFL), as well as the industry perspective from ABB's Marina Bill, Simon Johnson from the Drone Industry Association and Hocoma co-founder Gery Colombo. A final roundtable – including Robert Riener, Hocoma's Serena Maggioni, Liliana Paredes from Rehaklinik and Georg Rauter from the University of Basel – focused on the potential and the challenges of innovation in healthcare robotics.

The Association for the Advancement of Artificial Intelligence's 2021 International Conference on Artificial Intelligence and Interactive Digital Entertainment was held October 11-15, 2021. There were three workshops in the program: Experimental AI in Games, Programming Languages in Entertainment, and Strategy Games. This report contains summaries of some, but not all symposia. The 2021 Experimental AI in Games Workshop helped to encourage experimentation and discovery in game AI research and game development. This year saw fourteen presentations exploring established subjects such as level and narrative generation, to theoretical and practitioner work.