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An anonymous reader quotes a report from Ars Technica: Silicon Valley's AI talent war just reached a compensation milestone that makes even the most legendary scientific achievements of the past look financially modest. When Meta recently offered AI researcher Matt Deitke $250 million over four years (an average of $62.5 million per year)—with potentially $100 million in the first year alone -- it shattered every historical precedent for scientific and technical compensation we can find on record. [Meta CEO Mark Zuckerberg reportedly also offered an unnamed AI engineer $1 billion in compensation to be paid out over several years.] That includes salaries during the development of major scientific milestones of the 20th century. [...] To put these salaries in a historical perspective: J. Robert Oppenheimer, who led the Manhattan Project that ended World War II, earned approximately $10,000 per year in 1943. Adjusted for inflation using the US Government's CPI Inflation Calculator, that's about $190,865 in today's dollars -- roughly what a senior software engineer makes today. The 24-year-old Deitke, who recently dropped out of a PhD program, will earn approximately 327 times what Oppenheimer made while developing the atomic bomb. [...] The Apollo program offers another striking comparison. Neil Armstrong, the first human to walk on the moon, earned about $27,000 annually -- roughly $244,639 in today's money. His crewmates Buzz Aldrin and Michael Collins made even less, earning the equivalent of $168,737 and $155,373, respectively, in today's dollars. Current NASA astronauts earn between $104,898 and $161,141 per year. Meta's AI researcher will make more in three days than Armstrong made in a year for taking "one giant leap for mankind." The report notes that the sums being offered to some of these AI researchers top even the most popular sports athletes. "The New York Times noted that Steph Curry's most recent four-year contract with the Golden State Warriors was $35 million less than Deitke's Meta deal (although soccer superstar Cristiano Ronaldo will make $275 million this year as the highest-paid professional athlete in the world)," reports Ars.

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A Rutgers-led study using advanced computational modeling reveals that expanding solar power by just 15% could reduce U.S. carbon emissions by over 8.5 million metric tons annually, with the greatest benefits concentrated in specific regions like California, Texas, and the Southwest. The study has been published in Science Advances. From the report: The study quantified both immediate and delayed emissions reductions resulting from added solar generation. For example, the researchers found that in California, a 15% increase in solar power at noon was associated with a reduction of 147.18 metric tons of CO2 in the region in the first hour and 16.08 metric tons eight hours later. The researchers said their methods provide a more nuanced understanding of system-level impacts from solar expansion than previous studies, pinpointing where the benefits of increased solar energy adoption could best be realized. In some areas, such as California, Florida, the mid-Atlantic, the Midwest, Texas and the Southwest, small increases in solar were estimated to deliver large CO2 reductions, while in others, such as New England, the central U.S., and Tennessee, impacts were found to be minimal -- even at much larger increases in solar generation. In addition, the researchers said their study demonstrates the significant spillover effects solar adoption has on neighboring regions, highlighting the value of coordinated clean energy efforts. For example, a 15% increase in solar capacity in California was associated with a reduction of 913 and 1,942 metric tons of CO2 emissions per day in the northwest and southwest regions, respectively. "It was rewarding to see how advanced computational modeling can uncover not just the immediate, but also the delayed and far-reaching spillover effects of solar energy adoption," said the lead author Arpita Biswas, an assistant professor with the Department of Computer Science at the Rutgers School of Arts and Sciences. "From a computer science perspective, this study demonstrates the power of harnessing large-scale, high-resolution energy data to generate actionable insights. For policymakers and investors, it offers a roadmap for targeting solar investments where emissions reductions are most impactful and where solar energy infrastructure can yield the highest returns."

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A new paper from Bangor University outlines the "bizarre phenomenon" known as the transparency paradox: that transparency is needed to foster public trust in science, but being transparent about science, medicine and government can also reduce trust. The paper argues that while openness in science is intended to build trust, it can backfire when revealing uncomfortable truths. Philosopher Byron Hyde and author of the study suggests that public trust could be improved not by sugarcoating reality, but by educating people to expect imperfection and understand how science actually works. Phys.org reports: The study revealed that, while transparency about good news increases trust, transparency about bad news, such as conflicts of interest or failed experiments, decreases it. Therefore, one possible solution to the paradox, and a way to increase public trust, is to lie (which Hyde points out is unethical and ultimately unsustainable), by for example making sure bad news is hidden and that there is always only good news to report. Instead, he suggests that a better way forward would be to tackle the root cause of the problem, which he argues is the public overidealising science. People still overwhelmingly believe in the 'storybook image' of a scientist who makes no mistakes, which creates unrealistic expectations. Hyde is calling for a renewed effort to teach the public about scientific norms, which would be done through science education and communication to eliminate the "naive" view of science as infallible. "... most people know that global temperatures are rising, but very few people know how we know that," says Hyde. "Not enough people know that science 'infers to the best explanation' and doesn't definitively 'prove' anything. Too many people think that scientists should be free from biases or conflicts of interest when, in fact, neither of these are possible. If we want the public to trust science to the extent that it's trustworthy, we need to make sure they understand it first." The study has been published in the journal Theory and Society.

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