The deal to take control of TikTok's U.S. business came with an unusual condition, according to people familiar with the matter. The investors — which include Oracle, Abu Dhabi investor MGX, and private-equity firm Silver Lake — "paid the Treasury Department about $2.5 billion when the deal closed in January," reports the Wall Street Journal, "and are set to make several additional payments until hitting the $10 billion total." The $10 billion payment would be nearly unprecedented for a government helping arrange a transaction, historians have said... Investment bankers advising on a typical deal receive fees of less than 1% of the transaction value, and the percentage generally gets smaller as the deal size increases. Bank of America is in line to make some $130 million for advising railroad operator Norfolk Southern on its $71.5 billion sale to Union Pacific, one of the largest fees on record for a single bank on a deal. Administration officials have said the fee is justified given Trump's role in saving TikTok in the U.S. and navigating negotiations with China to get the deal done while addressing the security concerns of lawmakers... The TikTok fee extracted from private-sector investors is the administration's latest transaction involving the nation's largest businesses. Trump took a nearly 10% stake in semiconductor company Intel and has agreed to take a chunk of chip sales to China from Nvidia in exchange for granting export licenses. The administration has also taken equity stakes in other companies and has a say in the operations of U.S. Steel following a "golden share" agreement with Japan's Nippon Steel in its takeover. Reuters notes earlier this month, a lawsuit was filed by investors in two of TikTok's social media rivals, seeking to reverse the approval of the deal. Thanks to long-time Slashdot reader schwit1 for sharing the news.

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California saw its worst drought in 10,000 years between 2012 and 2015, remembers the Washington Post. And yet genetic analyses of California's scarlet monkeyflower "found that many rapidly evolved... allowing them to cope with water scarcity and rebound from decline." "The fact that certain organisms are able to adapt just because of genetics that are already present is a great source of hope," said Daniel Anstett, a plant biologist at Cornell University and lead author on a new study on the issue. "It's one more arrow in the quiver of different ways that populations might be able to survive the massive climate change we're inflicting on the planet." The recovery of [Sequoia National Park's] scarlet monkeyflowers offers rare, real-world evidence of what scientists call "evolutionary rescue," according to the study published Thursday in the journal Science. It suggests that some species may be able to evolve quickly enough to keep up with the accelerating consequences of human-caused warming — essentially saving themselves from extinction. This discovery could help people decide how to distribute limited conservation funds by pinpointing which species have enough genetic diversity to be resilient, ecologists Mark Urban and Laurinne Balstad, who were not involved in the study, wrote in a separate analysis published by Science. "The challenge going forward is to identify when evolutionary rescue is possible, when it is not, and how to rescue those species that cannot rescue themselves," Urban and Balstad wrote.

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"A new study suggests the productivity boost from AI may be far smaller than executives claim," writes Slashdot reader BrianFagioli: According to research cited in Foxit's State of Document Intelligence report, while 89% of executives and 79% of end users say AI tools make them feel more productive, the actual time savings shrink dramatically once people account for reviewing and validating AI-generated output. The survey of 1,000 desk-based workers and 400 executives in the United States and United Kingdom found executives believe AI saves them about 4.6 hours per week, but they spend roughly 4 hours and 20 minutes verifying those results. End users reported a similar pattern, estimating 3.6 hours saved but 3 hours and 50 minutes spent reviewing AI work. Once that "verification burden" is factored in, executives gain just 16 minutes per week, while end users actually lose about 14 minutes.

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