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Global Big Data Conference

#artificialintelligence

Researchers at ETH Zurich and the Frankfurt School have developed an artificial neural network that can solve challenging control problems. The self-learning system can be used for the optimization of supply chains and production processes as well as for smart grids or traffic control systems. Power cuts, financial network failures and supply chain disruptions are just some of the many of problems typically encountered in complex systems that are very difficult or even impossible to control using existing methods. Control systems based on artificial intelligence (AI) can help to optimize complex processes--and can also be used to develop new business models. Together with Professor Lucas Böttcher from the Frankfurt School of Finance and Management, ETH researchers Nino Antulov-Fantulin and Thomas Asikis--both from the Chair of Computational Social Science--have developed a versatile AI-based control system called AI Pontryagin which is designed to steer complex systems and networks towards desired target states.


Controlling complex systems with artificial intelligence

#artificialintelligence

Researchers at ETH Zurich and the Frankfurt School have developed an artificial neural network that can solve challenging control problems. The self-learning system can be used for the optimization of supply chains and production processes as well as for smart grids or traffic control systems. Power cuts, financial network failures and supply chain disruptions are just some of the many of problems typically encountered in complex systems that are very difficult or even impossible to control using existing methods. Control systems based on artificial intelligence (AI) can help to optimize complex processes--and can also be used to develop new business models. Together with Professor Lucas Böttcher from the Frankfurt School of Finance and Management, ETH researchers Nino Antulov-Fantulin and Thomas Asikis--both from the Chair of Computational Social Science--have developed a versatile AI-based control system called AI Pontryagin which is designed to steer complex systems and networks towards desired target states.


Houthi drone attacks expose UAE vulnerabilities, say analysts

Al Jazeera

A deadly drone attack by Yemen's Houthis on the United Arab Emirates (UAE) has exposed the country's vulnerability while jeopardising its reputation as a tourism and business hub and pushing it towards rapprochement with neighbouring Tehran, say analysts. The Iran-backed Houthi rebel group targeted a key oil facility in Abu Dhabi, killing three people. The suspected drone attack also caused a fire at Abu Dhabi's international airport, attracting condemnation and a pledge for retaliation from the UAE. Hailing the attack as "a successful military operation", the Houthi military spokesman Yahya Saree warned they could target more facilities in the UAE, which has been part of the Saudi-led war on Yemen that has killed tens of thousands of people and pushed the country towards humanitarian catastrophe. On Tuesday, Saudi Arabia launched air raids in the Yemeni capital Sanaa, killing more than a dozen people.


Three killed in suspected Houthi drone attacks in UAE: Live

Al Jazeera

A suspected drone attack by Yemen's Houthi rebels targeting a key oil facility in Abu Dhabi killed three people and started a separate fire at Abu Dhabi's international airport, police said. Police in the United Arab Emirates identified the dead as two Indian nationals and one Pakistani. "Small flying objects" were found as three petrol tanks exploded in an industrial area and a fire was ignited at the airport, police said, as Houthi rebels announced "military operations" in the UAE. The UAE which had largely scaled down its military presence in Yemen in 2019, continues to hold sway through the Yemeni forces it armed and trained. Drone attacks are a hallmark of the Houthis' assaults on Saudi Arabia, the UAE ally that is leading the coalition fighting for Yemen's government in the grinding civil war.


Computing With Light

#artificialintelligence

This article will look at a technology for AI inference processing using light rather than electrons from LIghtmatter and combined with traditional CMOS including SRAM memory. This article is based upon an interview with Lightmatter CEO, Nick Harris. The company sees this product being useful for data center inference and perhaps eventually in some AI computation intensive industrial and consumer applications (such as autonomous vehicles). There are widely cited forecasts that project accelerating information and communications technology (ICT) energy consumption increases through the 2020's with a 2018 Nature article estimating that if current trends continue, this will consume more than 20% of electricity demand by 2030. At several industry events I have heard talks that say one of the important limits of data center performance will be the amount of energy consumed.


(PDF) Distributed Effects of Climate Policy: A Machine Learning Approach

#artificialintelligence

We employ machine learning techniques to estimate household carbon footprints (HCFs) for the average household in each Census tract-geographic areas that represent roughly 4,000 people. We find that there is significant variation in carbon footprints across income and geography; income effects are driven by higher footprints related to transportation and consumer products and services, while geographic effects are primarily a result of the variable carbon intensity of the electricity grid. Using these footprints, we assess the net effects of various climate policies on households in the United States paying particular attention to the distribution across geography, urbanity, and income groups. Our objective is to improve the understanding of the potential for regressivity, geographic transfers, and rural-urban transfers among climate policy options and test for ways to control for transfers-preserving transfers from high-income households to low-income households, but mitigating transfers from rural areas to urban areas and from the Midwest and South to the Coasts. Our focus is on the net increase or decrease of annual household expenses under 12 different policy scenarios, which included both carbon pricing schemes and regulatory standards.


At CES 2022, Tech Companies Tried to Pitch Climate Sustainability as Fun and Exciting

TIME - Tech

Between presentations launching new PC processors and candy-colored refrigerators at last week's CES, companies at the annual tech industry jamboree made a lot of big, flashy proclamations about climate change, some more serious than others, and most seeming to include at least one stock video clip of trees, solar panels and children frolicking in grassy meadows or on pristine beaches. General Motors unveiled a new zero-emission pickup truck and dropped hints about new EV models to come, while Panasonic, which calculated that it released 110 million tons of CO2 per year and accounted for 1% of global electricity consumption, reiterated a pledge to decarbonize its operations by 2030 and promised to make its products more efficient. LG--which has pledged carbon neutrality by 2030, and to use fully renewable power by 2050--rolled out glass-fronted refrigerators (to avoid wasting energy while you look inside) and washing machines that use AI to shorten wash cycles. Samsung, whose CO2 emissions actually rose in 2020, and which has faced controversy over its reliance on coal energy, offered promises like devices that would use less standby power, which some environmentalists criticized as greenwashing. A version of this story first appeared in the Climate is Everything newsletter. To sign up, click here.


Survey at Fukushima No. 1 reactor container halted

The Japan Times

Tokyo Electric Power Company Holdings Inc. halted its investigation of the inside of the containment vessel of the No. 1 reactor at its stricken Fukushima No. 1 nuclear power plant on Wednesday. The move came after an issue was found during preparation work for the display of data such as radiation levels from dosimeters inside underwater robots to be used in the survey. The preparations began at noon the same day and were halted around two hours later. Tepco said that it will resume the survey once measures to resolve the issue are taken. In the survey, which will continue until around August, Tepco aims to take pictures of melted nuclear fuel debris and other deposits using six types of underwater robots to record their locations and thickness in water that has accumulated at the bottom of the containment vessel.


A "New Nobel" -- Computer Scientist Wins $1 Million Artificial Intelligence Prize

#artificialintelligence

Whether protecting against surges on electric networks, locating designs amongst previous criminal offenses, or even improving sources in the treatment of significantly bad people, Duke University computer system expert Cynthia Rudin desires expert system (AI) to reveal its own job. When it is actually creating choices that profoundly impact individuals's lifestyles, particularly. " I would like to give thanks to AAAI and also Squirrel AI for making this honor that I understand will definitely be actually a game-changer for the area," Rudin pointed out. "To possess a'Nobel Prize' for artificial intelligence to assist culture creates it ultimately crystal clear undeniably that this subject matter -- AI help the advantage for community -- is really significant." Dark container designs are actually the contrast of Rudin's straightforward codes.


AI Studies the Plasma Edge To Make Fusion Energy Possible

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To make fusion energy a viable resource for the world's energy grid, researchers need to understand the turbulent motion of plasmas: a mix of ions and electrons swirling around in reactor vessels. The plasma particles, following magnetic field lines in toroidal chambers known as tokamaks, must be confined long enough for fusion devices to produce significant gains in net energy, a challenge when the hot edge of the plasma (over 1 million degrees Celsius) is just centimeters away from the much cooler solid walls of the vessel. Abhilash Mathews, a PhD candidate in the Department of Nuclear Science and Engineering working at MIT's Plasma Science and Fusion Center (PSFC), believes this plasma edge to be a particularly rich source of unanswered questions. A turbulent boundary, it is central to understanding plasma confinement, fueling, and the potentially damaging heat fluxes that can strike material surfaces -- factors that impact fusion reactor designs. To better understand edge conditions, scientists focus on modeling turbulence at this boundary using numerical simulations that will help predict the plasma's behavior.