In the largest gathering of 2026 gubernatorial candidates to date, seven Democrats vying to lead California courted labor leaders on Monday, vowing to support pro-union agreements on housing and infrastructure projects, regulation of artificial intelligence, and government funding for university research. Throughout most of the hourlong event, the hundreds of union members inside the Sacramento hotel ballroom embraced the pro-labor pledges and speeches that dominated the candidates' remarks, though some boos rose from the crowd when former Los Angeles Mayor Antonio Villaraigosa strayed from the other Democrats on stage. Villaraigosa was the only candidate to raise objections when asked if he would support providing state unemployment benefits to striking workers, saying it would depend on the nature and length of the labor action. Gov. Gavin Newsom in 2023 vetoed a bill that would have provided that coverage, saying it would make the state's unemployment trust fund "vulnerable to insolvency." The Monday night event was part of a legislative conference held by the California Federation of Labor Unions and the State Building and Construction Trades Council of California, two of the most influential labor organizations in the state capital.

WIRED has been writing about Elon Musk--he of the electric cars, space rockets, tunnel-boring machines, implantable brain interfaces, Mars mission, and internet shitposting--for a long time. And yet the most shocking part of his two-hour interview with Republican presidential nominee Donald Trump, broadcast live on X earlier this week, may just have been what Musk didn't say. It happened around the 50-minute mark, during a very Trumpian discussion of gas and electricity prices. They were up nationally, Trump said, but "when that comes down and [sic] we're going to drill, baby, drill." And Musk, he of the--I'm going to say it again--electric cars and "saving the world" schtick, didn't pipe up until a full two minutes later, when he suggested that Trump set up a "government efficiency commission" to curb government spending.

Once in orbit, MethaneSAT's software and spectrometers, which measure different wavelengths of light to detect methane, will pinpoint both concentrated locations for methane plumes as well as the broader areas where the gases diffuse and spread. It will also use Google's image detection algorithms to create the first comprehensive, global map of the oil and gas industry's infrastructure, like pump jacks and storage tanks, where leaks most commonly occur. "Once those maps are lined up, we expect people will be able to have a far better understanding of the types of machinery that contribute most to methane leaks," says Yael Maguire, who leads geo-sustainability efforts at Google. This tool could solve a significant stumbling block for methane researchers, according to Rob Jackson, professor of Earth system science at Stanford. There are millions of oil and gas operations around the world, and information about where many of these facilities are located is tightly guarded, and where available, expensive to access.

Climate change is the defining issue of our time, and we are at a defining moment. Various interest groups, social movement organizations, and individuals engage in collective action on this issue on social media. In addition, issue advocacy campaigns on social media often arise in response to ongoing societal concerns, especially those faced by energy industries. Our goal in this paper is to analyze how those industries, their advocacy group, and climate advocacy group use social media to influence the narrative on climate change. In this work, we propose a minimally supervised model soup [57] approach combined with messaging themes to identify the stances of climate ads on Facebook. Finally, we release our stance dataset, model, and set of themes related to climate campaigns for future work on opinion mining and the automatic detection of climate change stances.

Despite the widespread diffusion of renewable energy, oil and gas are among the highly valued commodities in the energy sector. However, commodity cycles, capital planning challenges, and increasing operational risk have propelled the oil and gas industry to make more intelligent and efficient decisions. In a 2018 Ernst & Young (EY) survey, Artificial Intelligence (AI)/Machine Learning (ML) didn't even rank in the top five technologies used by seven global oil and gas supermajors (Figure 1). Further, they feel that in the coming years, technologies like robotic process automation (RPA) (25%) and advanced analytics (25%), but not AI/ML, will have the most significant and positive effect on their businesses. AI/ML have enormous potential in the oil and gas industry, and by not considering it, leaders in the sector risk being blindsided. It can help reduce costs, add capacity and capability, speed decision-making, and improve quality while managing risk.

As the world increasingly turns to renewable energy sources to power our homes and businesses, the need for high-performance computing (HPC) and artificial intelligence (AI) is also increasing. HPC and AI are used to model and predict complex phenomena, like weather patterns and climate change, as well as to optimize the design of renewable energy systems. The demand for HPC and AI is therefore increasing in many industries that are critical to the transition to a low-carbon economy. In addition, a great deal of research and development (R&D) has been put into play using these technologies, which are leading to breakthroughs that promise to change the way people live and work. With supercomputing technology in the limelight and companies focusing on enhancing their data centers' performance, it's easy to get caught up in the hype surrounding the new computer systems that boast high computing power. But a lot of people aren't sure where all of this is going or why it's such a big deal.

A powerful once-in-a-decade winter storm in February resulted in the near total collapse of Texas' power grid, resulting in residential and commercial areas suffering days-long blackouts, which led to at least 57 deaths and billions of dollars in property damage across the state's 254 counties. In addition, some Texans who did have power are facing overcharges of about $16 billion for electricity consumed during the weeklong crisis, according to a watchdog for the Electric Reliability Council of Texas (ERCOT), the quasi-governmental entity that oversees the Lone Star State's power grid. While debates as to the root causes of the grid's failure are likely to go on for months if not years, some energy experts contend that a potential solution exists that could have alleviated some of the worst effects of the power shutdown – the introduction of artificial intelligence (AI) into the management of the grid. Artificial Intelligence is loosely defined as the use of computer systems to process large volumes of data in order to perform tasks that normally require human intelligence, such as visual perception, speech recognition and decision-making. Although AI technology has been embraced by a number of other economic sectors, such as retail and insurance industries, the operators of the U.S. power grid have been slower to adopt it.

Oft cited as the blow that is knocking the wind out of the services business, AI has flexed its disruptive muscle. While Uber's advanced algorithms have produced efficiencies in ride sharing and differential pricing that have proved difficult for traditional taxi fleets to compete against, AirBnB is using advanced AI to find the perfect match between host and guest, creating an experience that will shine in comparison to high cost hotel rooms. But AI is more than a disruptive force that will displace businesses or replace workers – the technology is moving mainstream to provide decision support in an increasingly broad range of traditional sectors. A good example of this mainstreet extension of AI can be found in the experience of Vancouver-based Goldcorp Inc., which is using IBM's Watson to optimize exploration. Goldcorp is one of the largest gold mining operations in the world; however, mining in general is characterized as a'high risk, high reward' activity in which ore discovery can have a significant impact on profitability.

The winning team of MOL Group's Freshhh 2015 competition truly learned the value of hard work. "Just ask Siri," the first-place winner of the competition in which students from across the globe compete in technology and business strategy simulations related to the oil and gas industry was made up of three students from the University of Economics, Prague and Czech Technical University in Prague, Czech Republic. MOL Group experts are a part of the game development, so they make sure tasks are aligned with real-life situations, said Zdravka Demeter Bubalo, HR vice president of MOL Group. The top teams are invited to compete in the Live Final and present case studies connected to recent industry trends and issues. This strategy allows MOL Group to find the best global talent to join the company.

MOL Group announced yesterday the winners of the Freshhh 2015 competition, which sees students from all over the world compete in technology and business strategy simulations related to the oil and gas industry. 'Just Ask Siri', consisting of three students from the Prague University of Economics and the Czech Technical University, was awarded first place, with Hungary's'Oil's Creed' and Slovenia's'Decore' teams placing in second and third respectively. All three teams will now be given the opportunity to join MOL Group's graduate recruitment and development program. MOL Group HR Vice President Zdravka Demeter Bubalo commented in a company statement: "We congratulate the top three teams for winning the Freshhh competition 2015. I would like to thank all participants for their endless efforts during the competition. It is incredible to see how young students work with such difficult real-life cases and always find new solutions. The outstanding results from the participants and number of applications are showing us once more that we are heading in the right direction in order to attract top talents of the oil and gas industry."