Wind farms are now a reality in the U.S., heralding a new chapter in the country's sustainable energy production ambitions. But new technologies come with new challenges, and for offshore wind generation, inspection is one of the biggest. In much the same way as energy companies operate and maintain oil and gas subsea assets, wind farm cables, structural foundations, and all other components of the turbines need continuous monitoring and maintenance. That's dangerous work for humans, but it's a job tailor made for underwater robots and smart AI-powered analytics. Given the bright future and growing (albeit still small) footprint of offshore wind in the nation's energy power generation infrastructure, I reached out to Harry Turner, a machine learning specialist for Vaarst, a business driving the future of marine robotics, to discuss how robots and machine learning are changing the game for energy creation.
Synopsys' Manuel Mota shows how splitting SoCs into smaller dies for advanced packaging and using die-to-die interfaces to enable high bandwidth, low latency, and low power connectivity can benefit hyperscale data centers. Siemens EDA's Chris Spear explains the relationship between classes and objects in SystemVerilog with a handy visualization and notes the difference between SystemVerilog variables and class variables. Cadence's Paul McLellan listens in as Waylon Grange of Stage 2 Security demonstrates hacking the embedded software in a home's solar power controller and how it points to areas where embedded security still needs improvement. In a blog for Arm, Alp Acar of Boston University explains the concept of federated learning, a privacy-preserving paradigm to train machine learning models in a decentralized fashion, leaving a user's data on the device. In a video, Infineon's Thomas Aichinger dives into how to make the gate oxide of SiC MOSFETs more reliable in the field through voltage screening and marathon stress tests.
NASA's InSight lander is struggling to retain power as it explores Mars as dust is accumulating on its solar panels, which could result in its mission ending within the next year. The American space agency announced Tuesday that 80 percent of the solar panels are obstructed by dust, leaving less than 700 watt-hours of power per Martian day. It was hoped that winds would clean the lander and allow it to continue to collect seismic data on its extended mission, which was supposed to last until the end of 2022. NASA attempted to remove dust from the top on InSight earlier this month using the lander's robotic arm, which trickled sand near one solar panel with the hopes wind would carry off the panel's dust. NASA's InSight lander is struggling to retain power as it explores Mars due to Martian dust accumulating on its solar panels, which could result in its mission within the next year The death of InSight was discussed at a June 21 meeting of NASA's Mars Exploration Program Analysis Group, SpaceNews reports.
Farming robots that can move autonomously in an open field or greenhouse promise a cleaner, safer agricultural future. But there are also potential downsides, from the loss of much-needed jobs to the safety of those working alongside the robots. To ensure that the use of autonomous robots on farms creates more benefits than losses, a process of responsible development is required. Society as a whole needs to be involved in setting the trajectories for future farming. We are part of a project called Robot Highways, which is currently demonstrating multiple uses for autonomous robots made by Saga Robotics on a fruit farm in south-east England.
Tesla's Senior Director of AI, Andrej Karpathy, unveiled the electric vehicle automaker's new supercomputer during a presentation at the 2021 Conference on Computer Vision and Pattern Recognition (CVPR). Last year, Elon Musk highlighted Tesla's plans to build a "beast" of a neural network training supercomputer called "Dojo". For several years, the company has been teasing its Dojo supercomputer, which Musk has hinted will be the world's fastest supercomputer, outperforming the current world leader, Japan's Fugaku supercomputer which runs at 415 petaflops. The new supercomputer seems to be a predecessor to the Dojo project, with Karpathy stating that it is the number five supercomputer in the world in terms of floating-point operations per second (FLOPS). This supercomputer is certainly not lacking in the processing department.
Rapid and widespread adoption of EV has been impeded by consumers' anxiety over the reliability of batteries, limited autonomous options, and many other issues. Now the automotive market is being flooded with new players, giving the due spotlight to the importance of electric vehicle options. Consequently, the competition with some of the big giants sitting on the top of this sector is leading to highly advanced technologies being integrated into EVs and leaving all the worries of the consumers at the bay. With Resources shrinking and environmental pressures soaring, it is not a surprise that the world is seeking other and better alternatives. Countries like, The UK, France, Norway and Germany have even brought in legislation to ban the sales of non-electric vehicles as early as 2025.
In the latest study, researchers mapped out the physics of small building blocks made up of atoms, then used machine learning techniques to estimate how larger structures created from those same building blocks might behave. It's a bit like looking at a single Lego brick to try to predict the strength of a much larger castle. It's a pursuit that could be a boon for the electronics that underpin our daily lives, from smartphones and electric cars to emerging quantum computers. One day, engineers could use the team's methods to pinpoint in advance weak points in the design of electronic components. The project is part of a larger focus on how the world of very small things, such as the wiggling of atoms, can help people build new and more efficient computers--even ones that take their inspiration from human brains. Artem Pimachev, a research associate in aerospace engineering at CU Boulder, is a co-author of the new study.
The development and adoption of advanced technologies including smart automation and artificial intelligence has the potential not only to raise productivity and GDP growth but also to improve well-being more broadly, including through healthier life and longevity and more leisure. Alongside such benefits, these technologies also have the potential to reduce disruption and the potentially destabilizing effects on society arising from their adoption. Tech for Good: Smoothing disruption, improving well-being (PDF–1MB) examines the factors that can help society achieve such benefits and makes a first attempt to calculate the impact of technology adoption on welfare growth beyond GDP. Our modeling suggests that good outcomes for the economy overall and for individual well-being come about when technology adoption is focused on innovation-led growth rather than purely on labor reduction and cost savings through automation. This needs to be accompanied by proactive transition management that increases labor market fluidity and equips workers with new skills. Technology for centuries has both excited the human imagination and prompted fears about its effects. Today's technology cycle is no different, provoking a broad spectrum of hopes and fears.
A British-built solar powered drone with a 115ft wingspan that can stay in the air for over a year will be an alternative to low Earth orbit satellites, its developers claim. PHASA-35 is a cutting edge drone being developed by BAE systems at their facility in Warton, Lancashire that can fly about at 70,000ft above the surface for 20 months. It harnesses power from the Sun to stay airborne, charging a bank of small batteries during the day to keep it flying overnight, allowing for longer operations. The 150kg drone is able to carry a payload of up to 15kg including cameras, sensors and communications equipment to allow troops to talk to each other or provide internet access to rural locations during a natural disaster or emergency. BAE systems say it will be available by the middle of the decade and provide a'persistent and affordable alternative to satellite technology.'
Fighting climate change is both an urgent global imperative and a massive business opportunity. Climate change is the most pressing threat that the human species faces today. Artificial intelligence is the most powerful tool that humanity has at its disposal in the twenty-first century. Can we deploy the second to combat the first? A group of promising startups has emerged to do just that. Both climate change and artificial intelligence are sprawling, cross-disciplinary fields. Both will transform literally every sector of the economy in the years ahead. There is therefore no single "silver bullet" application of AI to climate change. Instead, a wide range of machine learning use cases can help in the race to decarbonize our world. Nearly every major activity that humanity engages in today contributes to our carbon footprint to some extent: building things, moving things, powering things, eating things, computing things.