These solutions will help Huawei deliver intelligent connectivity that is characterized by ubiquitous gigabit, deterministic experience, and hyper-automation in order to build industry Intelligent Twins. Huawei also launched autonomous driving network (ADN) solutions for enterprises, propelling enterprise networks into the ADN era and accelerating the intelligent upgrades of industries. David Wang, Huawei Executive Director and Chairman of the Investment Review Board, delivered a keynote speech titled "Building industry Intelligent Twins with intelligent connectivity." According to Mr. Wang, connectivity is productivity. It is not mere computing power, but strong connectivity that makes Intelligent Twins smarter.

Tackling carbon emissions is one of the biggest challenges faced by the world today. For big business, this means making a strategic and managed move towards increasing the use of renewable energy sources, as well as creating efficiencies across all aspects of their operations. It's a difficult task to manage alone, even for an enterprise on the scale of tech giant Microsoft or energy titan Shell. But working together creates new possibilities that go further than what it is likely they could accomplish individually. Beyond meeting their own zero-carbon commitments, there's the opportunity to help other companies within their vast ecosystems of customers and suppliers to meet their environmental and safety goals, too.

As more and more industries take on artificial intelligence to solve some of their biggest challenges, can machines help us understand and fix climate change issues? So your phone recognises your face, and your bank can block any transaction unlike your spending habits. And your online supermarket nudges you with their vegan products just because you've bought that oat milk once, while your online movie platform keeps throwing B-movies at you after you watched that soap opera last month. A growing number of our devices and services are relying on artificial intelligence (AI), a technology that continues to branch out and pop up in more and more areas of our lives. Scientists, entrepreneurs, and governments are leveraging AI to explore solutions for some of society's biggest challenges.

At HUAWEI CONNECT 2020, IDC and Huawei jointly released the white paper for the electric power industry -- Building the Future-Ready Power Enterprise: Road to a Successful Digital Transformation. In the white paper, IDC proposed a methodology for the transformation of electric power enterprises. This methodology supports and aligns with Huawei's digital transformation methodology. IDC and Huawei follow a similar approach with frameworks and blueprints to help organizations design their digital transformation priorities and set their agenda, which in turn enables power enterprises to deliver business value of scale. The power industry has long faced disruption. Power enterprises are now facing multiple changes.

How machine learning and AI are being used to cut emissions, picture the past, and study DNA. This company claims their AI platform can cut carbon dioxide emissions by improving buildings' efficiency. Read how an artist used machine learning to extrapolate realistic portraits of ancient Roman emperors. Researchers at the University of California San Diego have used machine learning to solve a long-standing question about gene activation in humans.

Tackling carbon emissions is one of the biggest challenges faced by the world today. For big business, this means making a strategic and managed move towards increasing the use of renewable energy sources, as well as creating efficiencies across all aspects of their operations. It's a difficult task to manage alone, even for an enterprise on the scale of tech giant Microsoft or energy titan Shell. But working together creates new possibilities that go further than what it is likely they could accomplish individually. Beyond meeting their own zero-carbon commitments, there's the opportunity to help other companies within their vast ecosystems of customers and suppliers to meet their environmental and safety goals, too.

Forests are having their moment. Because trees can vacuum carbon from the atmosphere and lock it away in wood, governments and businesses are embracing efforts to fight climate change by reforesting cleared areas and planting trees on a massive scale. But scientists have warned that the enthusiasm and money flowing to forest-based climate solutions threaten to outpace the science. Two papers published this week seek to put such efforts on a firmer footing. One study quantifies how much carbon might be absorbed globally by allowing forests cleared for farming or other purposes to regrow. The other calculates how much carbon could be sequestered by forests in the United States if they were fully “stocked” with newly planted trees. Each strategy has promise, the studies suggest, but also faces perils. To get a worldwide perspective on the potential of second-growth forests, an international team led by ecologist Susan Cook-Patton of the Nature Conservancy (TNC) assembled data from more than 13,000 previously deforested sites where researchers had measured regrowth rates of young trees. The team then trained a machine-learning algorithm on those data and dozens of variables, such as climate and soil type, to predict and map how fast trees could grow on other cleared sites where it didn't have data. > Can the forest regenerate naturally, or can we do something to help? > > Susan Cook-Patton , the Nature Conservancy A TNC-led team had previously calculated that some 678 million hectares, an area nearly the size of Australia, could support second-growth forests. (The total doesn't include land where trees might not be desirable, such as farmland and ecologically valuable grasslands.) If trees were allowed to take over that entire area, new forests could soak up one-quarter of the world's fossil fuel emissions over the next 30 years, Cook-Patton and colleagues report in Nature . That absorption rate is 32% higher than a previous estimate, based on coarser data, produced by the Intergovernmental Panel on Climate Change. But the total carbon drawdown is 11% lower than a TNC-led team estimated in 2017. The study highlights “what nature can do all on its own,” Cook-Patton says. And it represents “a lightning step forward” in precision compared with earlier studies, says geographer Matthew Fagan of the University of Maryland, Baltimore County, who was not involved in the work. But, Fagan adds, “Natural regrowth is not going to save the planet.” One problem: There is often little economic incentive for private landowners to allow forests to bounce back. Under current policies and market pricing, “nobody will abandon cattle ranching or agriculture for growing carbon,” says Pedro Brancalion, a forest expert at the University of São Paulo in Piracicaba, Brazil. And even when forests get a second life, they often don't last long enough to store much carbon before being cleared again. Fagan notes that even in Costa Rica, renowned as a reforestation champion for doubling its forest cover in recent decades, studies have found that half of second-growth forests fall within 20 years. Given such realities, some advocates are pushing to expand tree planting in existing forests. To boost that concept, a team of researchers at the U.S. Forest Service (USFS) quantified how many additional trees U.S. forests could hold. Drawing on a federal inventory, they found that more than 16% of forests in the continental United States are “understocked”—holding fewer than 35% of the trees they could support. Fully stocking these 33 million hectares of forest would ultimately enable U.S. forests to sequester about 18% of national carbon emissions each year, up from 15% today, the team reports in the Proceedings of the National Academy of Sciences . But for that to happen, the United States would have to “massively” expand its annual tree-planting efforts, from about 1 billion to 16 billion trees, says lead author Grant Domke, a USFS research forester in St. Paul, Minnesota. Cook-Patton says planting trees might make sense in some places, but natural regeneration, where possible, provides more bang for the buck. “For any given site,” she says, “we should always ask ourselves first: ‘Can the forest regenerate naturally, or can we do something to help?’”

As Doctor Who, Tom Baker fought Daleks and Cybermen, robot mummies and gothic monsters -- but his latest'creature feature' has taken the form of an accolade. Australian palaeontologists have named a newly-found species of trilobite -- a segmented sea creature from 450 million years ago -- in honour of the actor. Trilobites loosely resemble woodlice -- and their closest living relatives include lobsters, crabs and scorpions. They fell extinct around 251.9 million years ago. The fossil -- 'Gravicalymene bakeri' -- was found preserved in shale rocks in Northern Tasmania that date back to the so-called'Late Ordovician' period.

Artificial Intelligence is transforming the world at a rapid and accelerating pace, offering huge potential, but also posing social and economic challenges. Human beings are naturally fearful of machines – this is a constant. Technological advancements tend to outpace cultural shifts. It has taken the shock of a global pandemic to accelerate the uptake of many technologies that have been around for at least a decade. Unsurprisingly, much of the public discussion on AI has focused on recent controversies around facial recognition, automated decision-making and exam algorithms.

Held virtually today on the sidelines of the 64th IAEA General Conference, the first ever IAEA meeting discussing the use of artificial intelligence (AI) for nuclear applications showcased the ways in which AI-based approaches in nuclear science can benefit human health, water resource management and nuclear fusion research. Open to the public, the event gathered over 300 people from 43 countries and launched a global dialogue on the potential of AI for nuclear science and the related implications of its use, including ethics and transparency. AI refers to a collection of technologies that combine numerical data, process algorithms and continuously increasing computing power to develop systems capable of tracking complex problems in ways similar to human logic and reasoning. AI technologies can analyse large amounts of data to "learn" how to complete a particular task, a technique called machine learning. "Artificial Intelligence is advancing exponentially," said Najat Mokhtar, IAEA Deputy Director General and Head of the Department of Nuclear Sciences and Applications.