I hope to write more about some new papers in the literature soon, as well as providing links to some pretty cool physics-related content.  First, though, I want to say something about this preprint, which has people talking.  The article says, in the case of an ensemble of social sciences papers, anyway, that AI-based review is better, in nearly every quantifiable way, than human peer review.  This question of AI for reviewing papers and proposals has been in the air for a bit now, as in this article in Science, this editorial at Nature Nano, and the fact that the present administration has been using AI tools to "review" grants for content that allegedly goes against executive orders. I'm an associate editor at a journal, and I see a large volume of papers and reviews.  (Note that this post reflects my personal views, not an official take by the journal or its publisher.)  It is 100% clear that some reviewers are using AI tools to prepare their reviews, despite clear statements that this is not ok.  There is a distinct format that AI reviews take.  After a summary paragraph, usually there are five specific bullet points, one or two of which tend to zero in on some particular detail or peculiarity in wording of the paper in a way that humans probably wouldn't.  Often the phrasing is somewhat aggressive, with a bit of a "gotcha" tone.  Of course, in any given case, I can't prove AI was used, but if you read enough of these, they stand out.  To be clear:  I'm not talking about people who use AI to clean up grammar.  I'm talking about people feeding articles to an AI tool and asking it to spit out a review. The point of peer review, whether it's for grants or articles, is to get the informed views of the relevant scholarly community about the work.  We want to know what actual practitioners think of the results and their presentation.  Purely AI reviews just do not serve this purpose. Moreover, there are serious confidentiality issues at stake.  Sure, many scientists use preprint archives these days to put up prepublication work, but plenty still do not, especially for very hot topics where people are worried about being scooped.  Running submitted manuscripts or grant proposals through AI tools that can then scrape the content into their training sets is a fundamental violation of the confidentiality of the process.  Imagine someone uploads your manuscript about a machine learning search for a new high temperature superconductor to Gemini to generate a review, and then amazingly SandboxAQ later scoops you on this.  (Not accusing google of anything here, just a hypothetical example.  Feel free to say GPT and Mattergen.)  The math community already worries about this stuff. So:  If you are asked to review a paper or a grant proposal, bear in mind (1) the people doing the asking actually want your feedback, and (2) taking confidential documents and allowing them to be scraped by AI companies is bad.

I’m an Australian father of four, living in the US. Something of a corner case. Nevertheless, getting my kids Australian citizenship by descent, and then Australian passports so we can fly home legally, has kicked off a carnival of errors with a very dark side. Australia is generally thought of as a developed western liberal country with relatively high state capacity. And I have generally found that at least state government services, now administered through centralized offices, have become more efficient over time. Passport applications for children living overseas, however, remain a time machine with a difficult security overhang. Australian …

Researchers created a dataset of photos of thousands of paper-thin slices of a male and female cadaver to create one of the most detailed datasets about the human body.

In a remote corner of the driest state in the country, Anne Heggli's team has been keeping watch over some of Earth’s oldest beings. Since 02012, Heggli’s NevCAN network has recorded conditions at the Nevada Bristlecone Preserve every eight minutes. The result is more than 120 million data points and a high-resolution portrait of how a bristlecone pine thrives. Paleoclimatologist Adam Csank showed how bristlecone microcores reveal the droughts and floods these trees survived long before us, a history that fine-tunes models of what's ahead. Artist and philosopher Jonathon Keats went further. “The most accurate clock,” he said, “is a tree.” His monumental artwork Centuries of the Bristlecone keeps bristlecone time, a clock calibrated to the trees' own growth over millennia. Together, Heggli, Keats and Csank made the case for long science: patient, continuous observation that will help us answer future urgent questions. “Data at this resolution,” Csank said, “is like a Rosetta Stone” for understanding nature’s resilience. At fourteen years young, the bristlecone record is just beginning, Heggli said, but it already holds the key to questions like these: How will bristlecones adapt? What happens when the droughts and floods they've weathered for millennia arrive faster and more frequently? “We can't answer the questions if we're not watching,” said Csank. “We are the stewards of this data,” Heggli concluded. “This is why we need long science.”

Prende y se apaga sola, sale después de hora. CHARLY GARCÍA La máquina de ser feliz I’ve learned to tolerate them, and sometimes even like them, but Zoom meetings are weird. Even in familiar contexts: I have weekly check-ins with … Continue reading →