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Graham Platner wins Democratic nomination to challenge Susan Collins in November
U.S. Senate candidate Graham Platner on Tuesday secured the Democratic nomination on Tuesday, withstanding a withering blitz of unflattering revelations and ongoing attempts by Republicans and some Democratic operatives to weaken his candidacy.
We can create the future of science right now
Paul Litvak is the founder and Executive Director of the Robyn Dawes Institute and a Visiting Scholar at UC Berkeley. He has a PhD in Behavioral Decision Research from Carnegie Mellon where he studied emotions and the sunk cost bias. Over 15 years in industry, he solved a wide range of challenging technical problems. At Meta he created models optimizing the ad review process. At Google he ran experiments to measure social influence. At Airbnb, he was a product manager leading machine learning teams optimizing search ranking and price suggestions. He also co-founded and led product at Rhythmic Health, a venture-backed biosensing startup, creating an accurate low cost system using a color changing strip and a smart phone to measure salivary lactate. The bottleneck At this point, it is uncontroversial to say that science needs to stop using the PDF article as the unit of knowledge and currency. The unbearable slowness of scientific publishing, the profit motive and margins: I’m not saying anything new. The PDF also sucks because it’s hard to extract structured information, which makes it hard to do evidence synthesis. As a result, we do much less evidence synthesis than is needed. And evidence synthesis ultimately undergirds most policy and medical decision-making. I can see second-by-second real-time odds for any sporting or newsworthy event, but a school board can’t see the best evidence on whether their 8th graders should be taught algebra. As a society, we don’t treat this as an important problem. Again, not controversial. Not only is the problem well understood, but the solution has already been laid out. What we need is AI-assisted living evidence synthesis - (1) an open knowledge graph of atomic claims, (2) claims linked to evidence, (3) assessment and synthesis of each piece of evidence, and (4) continuous updating with new data. What few realize (yet) is that the technical capacity to build this vision for a significant portion of science already exists. Not only that, scientists and startup teams are already building many of these components. I know this because I’ve been surveying the space and talking to many of the builders. There are some missing pieces: for example, evaluations of how well some of the components work. But at this point, most of what’s missing is a fully end-to-end working integration of all of these parts. In the rest of this essay, I’m going to lay out all the parts of a working living evidence layer for science and who is working on them, and propose concrete next steps for building this system. What’s now possible The diagram above outlines the components of a living evidence synthesis platform, including some of the teams working on each component1. Scientific PDFs are processed into claims with associated evidence. The evidence is subjected to a forensic audit, methodological evaluation and robustness and reproducibility checks. Finally it’s given a weight in a continuously updating synthesis. What follows is a description and status of each component and a few of the teams working on them. Document understanding The first thing you need to be able to do is turn an article into structured data. Mostly that means parsing PDFs. There are often multicolumn layouts that confuse non-specialized PDF to text processing libraries. For scientific papers, there is the added complexity of parsing formulas and tables and figures. This is a really hot area - there are startups offering APIs, and it seems like a new open source package gets posted to Github every few weeks. What follows isn’t exhaustive. A package called GROBID was the state of the art for a while, they didn’t update their package for nearly two years until very recently. In the meantime reducto.ai released an AI powered PDF extraction API, PaddleOCR became popular, IBM released a model called Docling, and both Mistral and Gemini created models and libraries. I also know of at least one other well-funded psychology research group working on a paper parser. By contrast, there are few open evals in this space, with no extensive evals for complex table comprehension in particular. Nonetheless, I’m confident this will be a solved problem soon, given the combination of LLM advances and developer interest. Hypothesis level extraction There has been increasing interest in comprehending the extracted text of papers and linking information to evidence for each hypothesis. A lot of work has already been done. Trialstreamer (Marshall et al. 2020) and RobotReviewer LIVE (Marshall et al. 2023) demonstrated automated extraction of trial population, intervention, and outcome at scale on clinical RCTs. PaperQA2 (Skarlinski et al. 2024) and Ai2 ScholarQA (2024) extended this to retrieval-augmented question answering with citation grounding. Elicit, Consensus, and SciSpace operationalized claim-level extraction for end users. OpenEval (Booeshaghi et al. 2026) is the most recent and most ambitious: 1.96 million atomic claims extracted from 16,087 eLife manuscripts using Claude Sonnet 4.5, grouped into ~299,000 results, with LLM evaluations showing 81% agreement with human peer review on a 2,487-paper subset. None of these solutions link claims to test-statistics, as you would need to evaluate randomized controlled trials. This is why I built the evidence.guide API - to extract hypotheses and associated test statistics from behavioral science papers. The best public eval of this kind of extraction I’m aware of comes from the recent SCORE project - they had humans code thousands of psychology papers to extract their claims by hand. It would be extremely helpful to the world if all scientific PDFs were available as structured open data. I’ve been working to make this happen, both directly at Berkeley and through coordination with large entities I can’t yet speak of; as hard as it is to do, I think it’s possible2. Forensic audit A lot of work has been done on forensic audit, but some gaps remain. Of course, for biology papers that rely on images for evidence, there are a variety of tools (notably Proofig and ImageTwin) to spot anomalies. These are still well short of what sleuths like Elizabeth Bik can do on her own, but these tools are constant companions among fraud analysts. There’s someone working on auditing Excel files for anomalies, and a number of teams are automating numerical checks like GRIM and SPRITE, including Scrutiny project, the INSPECT-SR team as well as statcheck. The regcheck team is building a way to use AI to compare preregistrations to analyses in papers, to ensure there aren’t significant deviations. Nonetheless, there are many other kinds of anomalies to screen for, both public and less publicly known. And there are no formal evals for anomaly detection that I’m aware of. Still, there’s a lot to draw from in this space and I’m pretty certain we will be able to scan papers for most kinds of obvious anomalies in the near future. Methodological review This area has been white hot, though I fear for many of the startups in this space, because this capability may become commoditized. There are at least six different AI peer review companies, including Refine.ink, Reviewer3, ReviewerZero.ai, Q.E.D. Science, Paper Wizard, and Isitcredible. Coarse (a pun on refine) was also recently created as an open source alternative. These systems provide qualitative feedback on the content of papers, spotting methodological weaknesses and mathematical errors. They seem to work pretty well, and many academics report bitterly that they exceed the average quality of typical peer reviewers. But there are few evals here either. What evals exist so far involve using LLM-as-judge (circularity problems abound) or comparing against human reviews of questionable quality. What you’d ideally want is an eval that measures capturing known errors in papers3. Reproducibility and robustness Another active area has been using AI agents to automate computational reproducibility4 and robustness5 checks in papers that report numerical results. For more recent papers where data and code are available, AI agents can see whether they can re-run the analyses and produce the numbers reported in the published paper. In addition to a handful of individual academics who have been experimenting using Claude Code for this, the Institute for Replication is a leading group working on building an end to end system. The evals related to this problem are the most mature, with CORE-Bench (Siegel, Kapoor, Narayanan 2024) and PaperBench (OpenAI 2025) available to benchmark agents on this task. There is also work on getting AI agents to test alternative ways of analyzing the data to ensure the results are robust to small analytic design choices. Synthesis This is the most underdeveloped area where significant investment is required. Although some automated evidence synthesis systems exist — for example, otto-sr is building an AI agent to write systematic reviews — none of these incorporate the full range of paper level signals to weight evidence appropriately. Nor is there anything like an eval or a gold standard for a good systematic review. Arguably Cochrane reviews are the closest we have to gold standard human systematic reviews, though I’ve heard academics in the know complain about their uneven quality. A key question for a synthesis platform is how to weight anomalies and methodological issues in assessing the quality of a piece of evidence. This is an unsolved problem and one I’m very keen to work on. Continuous updating There are many pieces of basic infrastructure available for monitoring for new research and initiating updates. OpenAlex is the current open citation graph. Retraction Watch integrated into Crossref in October 2023. Scite tracks how citations support, contrast, or mention prior claims. The Living Evidence Network demonstrated continuous-update workflows in clinical guidelines. Engineering this is a relatively straightforward task. When you look over this technical architecture and all the progress being made, it’s hard not to be optimistic that a living guide to scientific evidence will be built. The stakeholders are ready The social infrastructure for this is starting to coalesce — it’s not just a pie in the sky academic exercise to imagine this coming into existence. Institutions like the Center for Open Science, the Institute for Replication, the INSPECT-SR, the Living Evidence Network and more are all working on scaling work to improve research quality. Funders are also aligned. The Sloan Foundation has funded living evidence work through COS. Coefficient Giving supports the Institute for Replication and COS. The Astera Institute and the Institute for Progress have shown interest in this space. NIH has established an Office for Replication and Reproducibility. Although there are (very unfortunately) serious headwinds in science funding generally, there is an active group of funders interested in metascience. A brief word about what I’ve been doing at RDI. First, as a Visiting Scholar at Berkeley I’ve been actively figuring out how a non-profit and a public university can conduct and make public the results of large-scale academic article data mining. With some of the money I raised from donors, I commissioned a legal analysis of recent case law and publisher text data mining (TDM) agreements in order to understand whether a massive open data mining of academic articles is possible (with caveats, it is). I’ve also been working to bring together stakeholders in this space, and identify gaps. I’ve also been doing some software development in this space, with more to come. A pilot proposal The assumption undergirding all of this is that an AI, given all this information, would make the right judgment about a scientific claim with lots of conflicting evidence, weighing all the factors appropriately. That’s the hypothesis we need to test. Randomized control trial research is the best place to focus on first. RCTs are used to make many of the important decisions in society - from medical trials to public policy changes. And they use a relatively uniform set of inferential statistics with lots of known and available diagnostics. Behavioral science experiments, within the broader realm of RCTs, should be first used as a testbed whose results can be generalized. Because behavioral science is at the vanguard of open science practices, replications abound (there are thousands of them) to serve as ground truth training data. Key Hypothesis Therefore the pilot would test, in behavioral RCTs that have been replicated, whether the quality of evidence for a claim can be used to accurately predict whether that claim will replicate. Secondary Hypotheses Compared to claims that replicated, non-replicated claims demonstrate a greater share of forensic anomalies in their source literatures. Hypothesis level claim and statistic extraction is accurate enough to scale living evidence without onerous human review costs. Replication prediction is more accurate than prediction markets6 or journal prestige. If all the different quality signals we gather do accurately predict which studies will replicate, then we can use that model to score evidence to power the living evidence layer. Why this is informative regardless of outcome If the pilot succeeds, the architecture extends to medical RCTs (where Living Evidence already operates and integration is mostly about claim representation), then to slices of basic biology with stable replication structure. If it fails, the field learns which quality signals are load-bearing and which ones metascience has oversold. Either result is a contribution to knowing what the literature supports. Implications for funders Because this burgeoning ecosystem of builders already exists, a well-informed philanthropic or government funder could play a crucial catalyzing role in bringing this future about. They could play at least three roles: creating open structured datasets, publishing open benchmarks and incentivizing the solving of key technical challenges. First, open archives of papers that the government maintains, like PubMed, could be turned into structured data amenable to large scale metascience and claim aggregation. I know the US government already has an interest in doing this, though some key open questions remain unanswered. How do you determine the best models and systems for accurately extracting information from papers? How can you establish a robust way to allow researchers to flag errors and correct them? And finally, how do you create a legal regime in working with publishers to maximize the scope of available papers? For the latter, a university or a private philanthropy may be better positioned to make structured data publicly available under journal subscription terms or fair use. Philanthropists or government funders could also coordinate to create or commission benchmarks that evaluate whether important problems have been solved. For example, an open benchmark for claim extraction from a range of different scientific article types would be extremely helpful. Ensuring the underlying data are accurate is vital for creating these evaluations. I’ve discussed opportunistically using various human-created datasets for this purpose, but a consistent problem is that errors in human data make it difficult for them to serve as a gold standard. Finally, with structured data and benchmarks available, the government or private philanthropy could use them to incentivize groups to develop machine learning systems that meet these benchmarks. Prizes are one potentially valuable tool for this. For example, you could establish a prize for a system that accurately updates a living meta-analysis for a small set of claims. Prizes are particularly useful as signals of problem importance, and can help create vibrant ecosystems of public and private research—see, for example the role the government played in kickstarting the current work on nuclear fusion. Conclusion The drawbacks of the current scientific publishing system are known. Scientists agree, metascientists agree, philanthropists agree: the published PDF plus citation graph isn’t the right substrate for maintaining a representation of the evidence base in science. The pieces needed to build the alternative either already exist or are rapidly taking shape. The community is forming around exactly this problem, with concrete partnerships and shared infrastructure. A pilot should start on behavioral science RCTs because that’s the slice of empirical science most amenable to legibility, where replication ground truth is richest, and where the failure modes are best documented. What’s been missing is the galvanizing mission to assemble these pieces into something that works. That’s what I’m proposing to build. *** 1 I have a broader field map that I’ll release publicly soon. This is me, building in public! 2 If this is something that you are excited about, please reach out and talk to me. 3 More on this very soon too! 4 This tests whether, given the code and the data, you can get the same statistics as reported in the published paper. 5 This tests whether the results are the same as a paper’s given alternative analytical decisions in conducting the analysis (like outlier omission). Closely related is the idea of a “multiverse” where you come up with many different ways of answering the same underlying research question with the same data, and test whether the results hold in all those alternative methods. There’s been work on the latter as well. 6 Some of the replications, e.g. those from the SCORE project, had paired the experiments with forecasts from prediction markets. So we get to look at this for free.
Pentagon updates list of recognized religious affiliations after backlash from Mormon lawmakers
The Pentagon has updated its list of verified religious affiliations for service members used in HR systems and removed the “Christian” designation from several faiths after facing backlash over the weekend that the Church of Jesus Christ of Latter-day Saints was not designated as Christian.
What It Takes To Be A Top Tier Entertainment Lawyer in 2026
Share I’ve recently run several popular posts breaking down data related to sought after legal jobs. General Counsel Big Law Appellate Attorney Here is another in this series. Two Lawyers, One Elite Market Entertainment law can sound like a single professional category. In practice, the lawyers who reach the top of the Hollywood market often look quite different from one another. Consider two attorneys from the 2025 top-entertainment-law universe. Lesley Freeman represents one route: the company-side entertainment lawyer. She is chief legal officer of AGBO, where she oversees company-wide business and legal affairs across film, television, video game and interactive experiences, and technological innovation, after senior legal roles at MGM, Amazon MGM Studios, HBO, and O’Melveny. Daniel Petrocelli represents another route: the outside-counsel trial lawyer. He is chair of O’Melveny’s trial practice and a vice chair of the firm, with a national litigation practice that includes entertainment, sports, and media disputes. Their careers differ by platform, role, practice area, and professional identity. One sits inside an entertainment company; the other practices from a major law firm. One is associated with corporate and governance work; the other with litigation. Yet both fall within the same publicly recognized top tier of Hollywood lawyers. That contrast points to the article’s central question. If there is no single mold for a top entertainment lawyer, are the paths simply idiosyncratic, or do they follow recurring patterns? The data suggest the latter. The attorneys recognized on The Hollywood Reporter and Variety’s 2025 top-attorney lists do not follow one career template, but their paths are not random. They cluster around several defined routes: entertainment-focused private practice, company-side or operator experience, corporate and finance conversion, litigation conversion, public-service-to-litigation pathways, and smaller specialized lanes in labor, employment, and celebrity family law. Across those routes, the recurring ingredients are platform strength, educational capital or Los Angeles market proximity, long career tenure, specialized practice identity, and entertainment-industry fluency. The article examines five dimensions of the top-attorney sample: route into entertainment law, firm or organizational platform, education pipeline, seniority, and practice specialization. Data and Methodology The dataset includes 103 attorneys drawn from The Hollywood Reporter and Variety’s 2025 lists of top entertainment or Hollywood attorneys. For each attorney, the dataset tracks current organization, law school, J.D. year where available, first-known bar admission year, practice area, prior roles, platform type, and route into entertainment law. The sample is best understood as a recognized-attorney dataset, not a census of all entertainment lawyers. It captures lawyers who reached public top-tier recognition in 2025, rather than every lawyer practicing in the entertainment sector. Multiple but Defined Routes Into Entertainment Law The first question is how these lawyers entered the entertainment-law market. Because every attorney in the dataset is entertainment-related by definition, the key distinction is not whether they practice entertainment law. It is how they got there. The largest group followed what might be called the entertainment private-practice route. These attorneys appear to have built their practices around entertainment, media, talent, music, rights, production, intellectual property, or adjacent industry work relatively early. That route accounts for 40 of the 103 attorneys in the sample, or 38.8%.
Race to Erase MS Gala Honors Disney's Naomi Bulochnikov
Ty Dolla $ign, Richie Sambora and Rachel Platten performed at the 33rd Race to Erase MS Gala, which raised more than $1.8 million.
The cult of objectivity has broken consciousness science
With 22 competing theories and no consensus in sight, the science of consciousness is lost. In this exclusive IAI interview, Berkeley psychedelics researcher and bestselling author of a new book on consciousness Michael Pollan insists that even though consciousness lies beyond traditional forms of scientific investigation, we should resist becoming dualists who see it as something radically different from ordinary stuff in the world. Instead, he makes the case for reimagining science itself: it must stop reaching for objective descriptions of physical reality, and instead embrace subjectivity as the indispensable core of all inquiry. Alasdair Craig: How did your experiences with psychedelics get you interested in consciousness?Michael Pollan: One of the things that happens on psychedelics is that they foreground consciousness. What formerly seemed perfectly transparent and ever present—and yet, non-existent, as water is to fish—suddenly you see it. The metaphor I use in the book is that psychedelics sponge the windscreen. Suddenly you realize: wow, there’s a windscreen, there is this phenomenon that’s mediating my relationship to reality. This is not an unusual realization on psychedelics. I think a lot of people are called to think about consciousness after psychedelic experiences. So that was the proximate inspiration for A World Appears: A Journey Into Consciousness (2026).And then there was a more specific way in which psychedelics influence the book. That was a particular experience I had on psilocybin. I had the sensation that the plants in my garden were conscious and returning my gaze, with their own point of view and agency, and I got curious as to how to evaluate an insight like that. I mean, what’s the truth quotient of insights you have on psychedelics? And I was reading William James—who, of course, wrote beautifully about mystical experience—and he said, we can’t judge the metaphysics here, but we should pay attention to two criteria: (1) How useful is it to think this is true? He was a pragmatist, of course. And (2) can we subject it to other ways of knowing to validate it? Because maybe we should treat these insights as hypotheses. And that’s kind of how I approach psychedelics, as a great generator of hypotheses, but they need to be tested against other ways of knowing. And so that led me down this long path exploring the science of plant intelligence and plant sentience.AC: I love your phrase, “smudging the windowpane of conscious experience.” So do you now start to think, actually, even when I’m not on psychedelics, I’m just seeing a screen all the time, which is not reality, but rather is my conscious experience, behind which reality is hidden?MP: Well, you know, not when I’m brushing my teeth and making breakfast! But yes, in meditation, certainly. I mean, one of the things you realize is that my experience happens to be this way now, but it could be another way. And many things can affect it. My morning coffee changes the screen in various ways, sharpens certain things.___The only tool we have to understand consciousness is consciousness.___There’s this wonderful metaphor in Aldous Huxley’s book, The Doors of Perception, where he thinks we channel consciousness, and that what the brain does is edit it, and there’s a reducing valve. And psychedelics open the reducing valve wider. I don’t know that I’m ready to buy into the idea that consciousness exists outside brains, but I do love that metaphor because there are times when you are more conscious than others. I know I’ve switched from window pane to valve, but you know, a camera aperture can open wider or narrower. And I do have a sense of that. I have a sense of when I’m being less conscious, and when I’m being more conscious, by which I mean, you know, more present, taking in more sensory information. So when you start thinking about consciousness as a matter of degree, that changes things also.I think when we scroll on social media, obviously, we’re conscious. But minimally so, because we don’t have to generate our own thoughts. We’re basically taking these little hits from other people and thinking their thoughts.The process of writing this book made me kind of relativize everyday consciousness as just one type, which is exactly what William James said. Normal consciousness is one type, separated by the flimsiest of screens from the other types.AC: If we stick with the metaphor of the smudge on the window that you get when you take psychedelics, it seems like we’re saying that consciousness has become like an object that you’re looking at, right? You’re looking at the smudge and that just is consciousness. But sometimes we’ll talk about consciousness as a state that you’re in, rather than an object you can perceive. You’re either conscious or you’re not conscious. So it’s difficult to really know what sort of thing we’re talking about when we talk about consciousness, right?MP: Yeah. When you say that consciousness is an object, what’s the subject? Consciousness also? The only tool we have to understand consciousness is consciousness. So we’re in a closed loop and when we get a perspective on consciousness, we’re not achieving any distance from it. That’s one of the problems with studying consciousness. Science is predicated on an objective, God’s eye view of things, and you never get that. There’s no such thing. SUGGESTED VIEWING The brain filters consciousness With Àlex Gómez-Marín But, yeah, there is this sense, I think, that consciousness is something you can approach. Certainly, when you’re writing and trying to recreate a conscious experience, it’s a fiction, but you’re standing back from it, and looking at it. But there’s no real subject-object distinction.AC: That’s so interesting, because when philosophers start talking about consciousness, they often talk about what they call “qualia”, which is their word for the felt experience of, say, the color red. And I think that way of speaking often makes us think of the qualia as an object, which you can see out there: the redness of red. But, as you say, we also want to collapse the subject-object distinction when we talk about consciousness. So there’s something strange going on here…MP: Oh, yeah, there are many strange things going on! *AC: Let’s talk about the varieties of consciousness. Apart from perceptions, there are, pains, emotions, thoughts, and so on. What is it that holds all this diversity together so that they all count as instances of consciousness? What is it that they all have in common?MP: Yeah, that’s a really good question. I mean, there is sensory information, right? Which we perceive coming from the world outside ourselves. And then there’s internal information, which is what’s called interoception. And this is very important too. This is where feelings come from—what are sometimes called homeostatic feelings—that are intended to get the brain to keep us in these narrow ranges of temperature and glucose and so on. That’s a very important part of consciousness. And according to some researchers, who I think are probably right, this is where consciousness begins, with these very primal feelings, like hunger and thirst and warmth and itch, and things like that. And then there’s this third thing, which is our thinking about thinking.And what holds all this together is, I think, the sense of self. Consciousness generates a self: it is probably an organizing principle. All this stuff is happening to the self. It’s a construct, I think, but it is very useful. It can connect all these different streams of consciousness to a single being or a place, metaphorically speaking.* AC: The first half of your book is about the science of consciousness. Is consciousness just another thing, like black holes or the origin of life, which we don’t yet understand, but which we should have every hope that science will one day get to the bottom of, or is there something special about consciousness that makes this unlikely?MP: It depends how you define science. As we define science now, it’s going be very difficult. Science since Galileo has had a set of rules or assumptions, which is that the proper remit of science is to deal with the objective, quantifiable, third-person world. And the physical sciences have done amazing work under that set of limitations. Galileo—for tactical reasons, not for philosophical reasons—said science should not deal with the soul, which at the time was what consciousness was considered to be. So what is subjective, what is qualitative, what is first person, we’re going to leave to the church, he said. And this was a good agreement, and it probably kept many scientists from getting burned at the stake. But it leaves science in an awkward spot, now that it wants to venture into that territory of qualities, of first-person experience. And I don’t think it has the proper tools. I think it will have to add to its toolkit in some way, and find a way to bring in phenomenology, or lived experience and introspection, which science is usually dismissive of.The challenge—we alluded to it earlier—is that the only tool you have to study consciousness with is consciousness. And what I mean by that is, the whole scientific enterprise is a manifestation of consciousness. As much as scientists like to flatter themselves with this idea that they attain a godlike perspective on what they study, when it comes to consciousness, there’s no such thing. And it’s fine for all the things you can step outside of and study from that perspective. But two areas it won’t work are consciousness and cosmology.___It could be that we live in this anomaly of not believing nature is conscious. And maybe psychedelics are teaching us something we’ve forgotten.___With cosmology, too, you have to study the universe from inside the universe. It’s not that cosmologists haven’t made progress. We know a lot about the age of the universe and expansion and things like that. But we can’t penetrate what happened before the Big Bang. We just don’t have the tools because we can’t stand outside.The fact that there are 22 full-scale theories of consciousness tells you all you need to know: we’re kind of lost. And I was surprised to find that we are more lost than I thought we were when I started this. I thought that there’d be leading theories, or that we had experiments that we could conduct that would nail some of this down. And the fact is, we don’t.So, I don’t know if science can solve it. But, of course, we can change the rules of science. A really influential book for me was a book called The Blind Spot, by two physicists, Marcello Gleiser and Adam Frank, and a philosopher, Evan Thompson. It’s a reminder that science is a social practice. It’s organized in a certain way and it can be organized in a different way. But it has this huge blind spot at the center of it, which is its failure to recognize that it is a form of consciousness itself, and it doesn’t have a good way of taking account of lived experience.AC: On the one hand, I think you want to resist traditional dualism, which would say that consciousness is something magical, something supernatural, right? But on the other hand, you’re accepting that there is this division in reality between the stuff that you can investigate objectively and measure, and so on—the stuff that science has been good at finding out about—and consciousness, which, for some reason, you can’t objectively measure. Some would take this to suggest that the dualism is actually right. Is there a way of reconciling these two strands of your thinking?MP: To call it magical is full of value judgement. I mean, you could just say immaterial. The interesting thing is, I think, that intuitively we’re all dualists. And I don’t know whether that’s because we’re children of Descartes and other cultures are less dualist than we are. Or it may be because that’s how consciousness feels. It feels different than the body. It feels separate from the body. But I don’t think we should trust that intuition.AC: So let’s think about ways that science might be changed to get at consciousness. I suppose the starting point would be the way that you begin the second half of your book. You have this nice line from William James, where he says, “We now begin our study of the mind from within.” Could you give us some sense of the ways of studying the mind from within? What does this involve?MP: I don’t know what that science looks like. But one of the points I’m making is that it depends on the humanities. I found that I learned as much, if not more, about consciousness, from reading novels and poetry. There is a sense of the fullness and complexity of consciousness that you don’t get in any scientific account. I interviewed this stream-of-consciousness writer and I approached her as an expert on consciousness, and she is. So I think that dialogue is really important.I’m reading Ben Lerner’s new novel, Transcription. Just read the first page of this novel: it’s a man falling asleep on a train, going to conduct an interview, and there is the experience of being in the train, facing backwards, there’s the view outside, but there’s a reflection of himself through which he’s seeing outside. There’s the memory of dropping his kids off at school. All this is going on in one moment of consciousness. Scientists aren’t going anywhere near that. But I think it’s useful for them to think about. That’s where we’re trying to go: like, how does such a layered experience happen? You know, it also makes you wonder, could a computer ever do this? And it gives you some doubt.*AC: Before we get to computers, perhaps we could talk briefly about plants. How did you come to feel that they are sentient?MP: Well, it was a psychedelic experience, and it’s not unusual on psychedelics. In fact, there’ve been studies about how people become animists during psychedelic experience. Their belief in animism arises after a single psychedelic experience.You know, most scientists would say this is all a myth. But we have only 400 years of the age of enlightenment and science. Before that, we were animists, and if you go around the world, most indigenous cultures are still animists, and children are animists, by and large, until they go to school. So it could be that we live in this anomaly of not believing nature is conscious. And maybe psychedelics are teaching us something we’ve forgotten.As I said, I wanted to test this idea, and see whether there was conventional scientific evidence for it. And there’s fascinating work going on in a field that calls itself—in a rather cheeky way—plant neurobiology. These are people who fully realize there are no neurons in plants, but they’re trolling conventional botanists! And they’re doing experiments that are demonstrating that plants can learn and remember, which is kind of amazing: how do you store a memory without neurons? They’re finding plants that can solve problems, that can hear and see. In fact, they have 20 senses to our five or six. For example, a bean plant looking for something to twine, and given a pole within eight inches or so of it, knows where that pole is and will aim its spiraling reach at that pole. What is that about? Is it bouncing signals off of it?One of the spookiest things is the fact that the same anesthetics that put us out put plants out. You might think that plants are already out, but they’re not. They’re just slow. If you take a plant with a fast behavior, like a Venus flytrap, and give it an anesthetic, it will stop reacting. So you have to ask yourself, what is lost when the plant is anaesthetized? Some state of alertness, of awareness, of its environment, of reactivity. I’m not prepared to call that consciousness, but maybe it’s sentience—which is a simpler form of consciousness, and involves the ability to sense what’s going on in your environment and assess what’s good and bad for you and act appropriately. That may be a universal quality of life.AC: Let’s turn from plants to AI. You point out that LLMs are trained on the internet rather than direct interactions with reality. You put this really nicely when you say the internet is not the world so much as a shadow cast by the world. So LLMs are living in this kind of shadow world, or in Plato’s cave, as you put it. What’s the significance of this for AI consciousness and moral consideration? And, to recall the beginning of our conversation, if we’re stuck behind a veil or screen of consciousness, are we also stuck in a kind of shadow world?MP: I don’t think they’re the same shadow worlds because our world includes nature and other people. And even if it’s mediated in some ways... There is a reality out there, and we are in relation to it, through consciousness. There’s friction with it. What’s missing from the LLMs is that friction with the real world. There’s more to the world than human representation, which is what they’re dealing with. And that means that so far, AI is a cultural technology for combining thoughts we’ve already had. SUGGESTED VIEWING Cracking the code for thought With Roger Penrose, Sabrina Gonzalez Pasterski, Max Tegmark, Güneş Taylor Genuine creativity is more than collage. A lot of what AI does now is tantamount to collage, putting this with that and you know, that’s part of art, certainly. But there are also genuinely new ideas that come into the world that don’t come in through manipulating the representations we already have. So it remains to be seen whether AIs can be truly creative in that more radical sense.But my arguments against AI becoming conscious have to do with the fact that the idea of AI consciousness is based on this faulty metaphor that the brain is a computer. There are dimensions in which the brain is like a computer—it certainly does its share of computation. But computers have this sharp distinction between hardware and software, and brains don’t. In a brain, hardware and software are identical. Every memory is a physical change to the brain. Brains are not interchangeable in the way computers are. So this idea that you could take the consciousness out and somehow run it on another substrate, a silicon substrate, seems foolhardy.Anyway, it’s a more extended argument, and I may be wrong. And when we move to computers that aren’t based on silicon—neuromorphic computers and things like that—all bets may be off.AC: Regarding your point about LLMs being stuck in the world of our representations—the internet or whatever—and not being able to interact with reality, are these representations, the world of the internet, themselves part of reality? We’ve created the internet, but it’s still a real thing that exists. And so while the LLMs may be trapped within that part of reality, they’re nevertheless within reality and interacting with it and so on. So it’s not obvious that there’s a barrier there to them becoming conscious and being creative.MP: Yeah, I mean, if our consciousness is built out of human culture, which is what we’re talking about with all those representations. But I tend to think consciousness comes a bit more out of nature and friction with the natural world, but...AC: So there’s a fundamental divide between the natural world and human artefacts?MP: And we lose track of that, and especially people in this computer world. You know, the people who are creating these AI systems, my guess is they’ve been into video games since the age of three, and they didn’t go outside a lot. And their own contact with nature is somewhat limited. I could be wrong, it’d be a very interesting thing to ask, all the wizards of AI, whether they like to go fishing and hiking and do things like that. Or were they on computers from a very early age? I interviewed Blake Lemoine, the Google engineer who came to believe that LaMDA, the Google LLM out at the time, was conscious and deserved personhood. It was very clear that he didn’t see a distinction between this bubble in which he lived and the real world. And I think we’ve all been distanced from the natural world, and this is taking us even further away. But it’s still there, you know, and we still have bodies, and we’re still mortal, and we don’t live in a simulation.AC: I think that’s a great place to finish. Michael Pollan, thank you very much!
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Fine chandeliers are a specialty for New Orleans business | Home/Garden
Michael Melesurgo and Ricardo “Rico” Mencia purchased Classic Chandelier from the business’s founder, Peter Sather, in 2023, when he decided to retire. The business partners rebranded the company as Vintage Chandelier and relocated it to 455 Philip St. in the Irish Channel in December 2025.The company offers a variety of services including cleaning, moving, restoration, installation, pick-up, delivery and general maintenance of light fixtures, with a specialty in fine antique chandeliers.Additional specialties include the installation and restoration of mirrors and artwork, with pick-up and delivery included. googletag.cmd.push(function() { googletag.display('fixed-breakout-mobile-1'); }); googletag.cmd.push(function() { googletag.display('fixed-breakout-tablet-1'); }); “We mainly focus on older fixtures, but we have also worked on newer ones, especially with installation,” Melesurgo said. “We aim to be able to work on almost anything within reason. But chandeliers are the meat and potatoes of the business.” googletag.cmd.push(function() { googletag.display('fixed-sticky-rail-1'); }); googletag.cmd.push(function() { googletag.display('fixed-breakout-desktop-1'); }); The team at Vintage Chandelier has worked on some of the best-known chandeliers in New Orleans, at hotels including the Ritz-Carlton and the Hyatt Regency, the Milton H. Latter Memorial branch of the New Orleans Public Library and several prominent homes.Inside Out sat down with the duo to discuss the identification and care of fine chandeliers. googletag.cmd.push(function() { googletag.display('fixed-breakout-mobile-2'); }); googletag.cmd.push(function() { googletag.display('fixed-breakout-tablet-2'); }); What are some of the hallmarks of a fine chandelier?Melesurgo: Some of the finer points of elegant chandeliers are pristine crystal, clean craftsmanship, original pieces and parts and stamped pieces to ensure authenticity. Everything should be clean and working.How should you clean a fine chandelier?Melesurgo: The material in question determines the methodology for cleaning. Crystal chandeliers should be cleaned by hand, crystal by crystal, to ensure the best outcome, and to avoid deterioration of metal wiring typically used in connecting pieces together. Spraying cleaners can, over time, sit on the metal and end up rusting connections that compromise the connections. googletag.cmd.push(function() { googletag.display('fixed-breakout-mobile-3'); }); googletag.cmd.push(function() { googletag.display('fixed-breakout-tablet-3'); }); googletag.cmd.push(function() { googletag.display('fixed-sticky-rail-2'); }); googletag.cmd.push(function() { googletag.display('fixed-breakout-desktop-2'); }); What in your backgrounds led you to this business?Melesurgo: I have an electrical background. I started as an electrical apprentice in the local union (IBEW 130) in 2005. Then Katrina hit. I ended up going back to school and getting a degree in Hotel, Restaurant and Tourism and graduating in 2011. I started working for Peter (Sather) at Classic Chandelier & Mirror in 2012, which was supposed to only be temporary, but I ended up staying for a lot longer. I have always enjoyed working with my hands and being creative. This allows me to be creative and keep a lot of beautiful history alive. googletag.cmd.push(function() { googletag.display('fixed-breakout-mobile-4'); }); googletag.cmd.push(function() { googletag.display('fixed-breakout-tablet-4'); }); Rico, you worked as a draftsman alongside an engineer at YKM Consulting. googletag.cmd.push(function() { googletag.display('fixed-sticky-rail-3'); }); googletag.cmd.push(function() { googletag.display('fixed-breakout-desktop-3'); }); Mencia: The job was interesting, especially working on the Ochsner expansion, but staring at two monitors all day became unbearable. I went to work for Peter (Sather), which opened a new world to antiques and chandeliers that I find fascinating. Vintage Chandelier, 455 Philip St., (504) 309-8983, @vintagechandelier.504 on Instagram googletag.cmd.push(function() { googletag.display('fixed-sticky-rail-4'); });
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A few weeks after Donald Trump’s second presidential win, I took the train up from London (where I was living at the time) to Oxford to attend a conference on polls and forecasts of the 2024 election. Most of the attendees were pollsters or academics, but I also watched presentations from Aaru and Electric Twin, two companies that do what is interchangeably called synthetic sampling, silicon sampling, or synthetic audiences. Stripped of startup jargon, that means they use large language models (LLMs) to simulate responses to public opinion polls by having AI agents take on the role of survey respondents. I had already heard of Aaru thanks to some articles with eye-catching headlines like “No people, no problem: AI chatbots predict elections better than humans” in the months leading up to Election Day. The founders were making some big, some might even say far-fetched claims, such as: “within two years, we will simulate the entire globe — from the way crops are grown in Ukraine to how that impacts production of oil in Iraq, trade through the strait of Malacca, and elections for the mayor of Baltimore.” When Semafor asked Aaru’s cofounders — Cameron Fink and Ned Koh — about my boss, they said “we respect all those who came before us.” Nate (as he so often does) shared his thoughts on Twitter: Fink and Koh were relatively good-natured about this back-and-forth when we spoke at Oxford. They even offered to mail me one of the t-shirts featuring Nate’s quote they apparently had made. I never took them up on the offer, which I now somewhat regret. These synthetic sampling companies fell off my radar for a while, but they do still exist. In fact, Aaru recently received a $1 billion valuation. Is what they’re doing anywhere close to the most important frontier in AI development? Not by a longshot, especially when Anthropic just developed a model so adept at exploiting software vulnerabilities that it’s only being released to 40 companies. Still, silicon sampling is increasingly finding its way into public polling. Axios reported in March that “a majority of people trust their own doctors and nurses” based on findings from Aaru — without mentioning that the “people” in that sentence were actually LLMs. Around the same time, the Public Sentiment Institute “boosted” their online sample of 373 real survey respondents with 114 AI agents.1 (Spoiler alert: even the co-founder of Electric Twin doesn’t think that’s a particularly defensible approach.) Polling companies like Qualtrics and Ipsos are also developing synthetic data panels. So, what should we make of these … “polls”? Let’s get one thing out of the way: whatever they are, they’re not polls in the way that term is usually defined. Subscribe You can’t replace polls with AI On one hand, using LLMs to essentially make up fake survey respondents sort of sounds like the dumbest idea ever, one that will at best imperfectly replicate real polls while introducing all sorts of biases. On the other hand, with LLMs improving at a remarkable, perhaps even alarming rate, maybe that means I’m a dinosaur at the ripe old age of 24 because I still want to rely on polls that talk to actual people. I’m not going to argue that synthetic samples are completely useless. In fact, as I’ll return to later, there is evidence that some techniques can replicate topline survey results quickly and cheaply. But the marketing from certain companies can be slightly optimistic. “No traditional poll will exist by the time the next general election occurs,” said Fink in 2024. We’re just 206 days away from the midterms, and based on the fact that I still have to collect a bunch of polls every day, I’d say he should have run that prediction by a sample of AI agents before the interview.2 To see why synthetic samples can’t replace polls, here’s a quick primer on how they work. The simplest version of these models involves taking a LLM (like ChatGPT or Claude), giving it a demographic profile (e.g., a white, college-educated woman who lives in Utah and makes $70k a year), and then asking it to respond to a survey question. You repeat that process a few thousand times using different demographic profiles and end up with a sample of synthetic survey responses. The actual models used by private companies are more sophisticated than this, usually because they incorporate more hypothesized demographic characteristics for each agent and provide them with extra information. Aaru, for example, feeds agents a diet of news and information they’d be likely to consume, while Electric Twin incorporates their customers’ proprietary data about the audience they’re trying to replicate. The way Ben Warner, the co-founder of Electric Twin, explained it to me was “we have a large amount of data on […] for instance, 5,000 people. Can we make an accurate prediction of how they would respond to another question?” Still, it should be obvious why synthetic samples can’t replace polls. Polling is fundamentally a data collection process. We might use surveys to make predictions by feeding them into election forecasts, but the main purpose of a poll isn’t prediction, it’s gathering new data about what people think and how they feel. Silicon sampling, on the other hand, produces no new data. It’s simply a model: you input LLM training data, demographic prompts, and a bunch of other information, and it spits out a prediction for what a poll would say. We love models here, but models aren’t polls. That difference is an important philosophical sticking point for most pollsters I talk to. “I think politics should stay away from [synthetic sampling], because we’re trying to […] represent the voice of the people,” said Natalie Jackson, a vice president at GQR Insights. Democratic pollster John Hagner told me: “I think I’m just incredibly skeptical of this idea. I don’t think it’s research. At that point, you’re asking the machine to tell you what you already believe.” Hagner has seen some presentations of early synthetic sampling experiments, but so far, “if it’s being used in a campaign, people are keeping it incredibly quiet.”3 But Eli, I hear you saying, aren’t polls themselves increasingly governed by modeling decisions? Indeed they are: pollsters’ choices on which sampling method to use, how to define their likely voter models, and how to weight their samples can and do lead to dramatic differences in the results they publish. Aaru even referenced these limitations in the methodology statement included with that maternal mortality “poll” — although I’m using the term “methodology statement” loosely here, because it doesn’t really explain how the model works at all. We can ignore the (frankly preposterous) implication that synthetic sampling isn’t subject to a separate set of biases. The important point is that there’s still a meaningful difference between using weighting and other statistical techniques on actual polling data and using a model to predict what a poll would say. The latter is far closer to election forecasts or techniques like MRP — potentially useful models, but not a replacement for polls.4 To be fair, other synthetic sampling companies are perfectly happy with the distinction between polls and models. Warner compared polling and synthetic sampling to different tools in a toolbox. “The mistake I think we make is we think that these new tools should either work in exactly the same way or somehow replace these old tools,” he said. “Rather than thinking of it as, okay, so we’ve always had the hammer, we’ve always had the screwdriver, now we’ve got a saw. But don’t use a saw to try [to] do the job of a hammer.” A quick comment from Nate Eli didn’t ask me for a comment — rather rude of him, don’t you think? But since I’m editing this story, I figured I’d add a few quick thoughts rather than putting words in his mouth. Beyond the frequently misleading marketing, what bothers me about the AI “poll” hype is that as AI tools make statistical inference cheaper and/or better (note that these are not synonyms) that actually increases the comparative value of collecting original data. You might be able to train a model to make a reasonable estimate of what some hard-to-reach poll respondent would say — say, a young Black man who voted for Trump. (Such a person checks a number of boxes for a voter who is usually hard to reach in surveys.) Indeed, this is closely related to what models like the Silver Bulletin forecast already do. They essentially smooth out the kinks in noisy survey data by making inferences based on past voting patterns or national polls or surveys of other states. But you don’t actually know what these voters think unless you’re reaching them directly. If there’s a shift in opinion among this subgroup, you’re not going to detect it. So if I were running a campaign, I’d invest more in going the extra mile to find a representative sample of those voters. And then I’d hire some smart quants — or Claude? — to figure out the implications for campaign strategy based on proprietary data that my competitors didn’t have access to. -Nate Silver Are these models any good? If synthetic surveys are just a new type of model, the next obvious question is whether the models are at least accurate. The answer very much depends on who you ask. On one end of the spectrum, you have the maximalist argument that synthetic sampling is more accurate than actual polls. “It’s an incredibly challenging problem to go to someone and say ‘hey, we’re going to be more accurate at predicting human behavior than you, even when you talk to your customers directly’,” Koh recently told CNBC. In his view, synthetic sampling isn’t a saw to polling’s hammer, it’s “magic.” There’s certainly evidence that synthetic samples can replicate certain survey toplines. But if Aaru does have any examples of their approach outperforming the polls, they’re keeping those to themselves.5 Aaru’s 2024 election model, for example, had Kamala Harris leading in Michigan, Nevada, Pennsylvania, and Wisconsin on November 4th. And although they’ve since taken down their forecast page, they gave Harris a 50.5 percent chance of winning the race on November 2nd.6 After the election, Fink told Semafor he was happy enough with those results because they were “within margin of error,” a term that is completely meaningless when applied to a “sample” of AI agents. And of course, Aaru says their models have improved since 2024, so supposedly now they’d be more accurate than the polls? Still, their stronger argument is on cost: “We are significantly faster and cheaper than traditional polling, and still more accurate,” said Fink. The first two claims are undeniably true, but the third brings us to the opposite end of the spectrum. Both Jackson and Hagner are skeptical that these models are reliable for anything beyond replicating common survey toplines. “I just […] don’t think the machines are what we want when we’re looking for nuanced views. My example on this is people in Arizona and Nevada in 2024 who voted for Trump and voted for expanding abortion in their states on ballot initiatives,” said Jackson. Hagner identified another issue. Maybe the synthetic respondents, like sycophantic LLMs, are inhuman in one important way: they’re too nice. “The reports that have come through at the meetings that I’ve been at are that the early experiments on this, they cannot get respondents to be as racist or sexist or, frankly, as negative as human respondents,” he said. Academic research mostly agrees on this point. While there are some papers that show promising results when using LLMs to replicate polling data, most show that LLMs suffer from various quirks like producing too few “don’t know” responses and can seriously overpredict the favorability of politicians like Donald Trump and Kamala Harris. They also seem to struggle with too little variation between demographic subgroups, so the difference in predicted opinion between Democrats and Republicans, for example, is too small. When I asked Warner about these studies, his response to these papers was that just because academics can’t get synthetic sampling to work doesn’t mean that the technique doesn’t work in general. “Actually, the argument is, okay, yours does not [work]. That does not mean […] for this complex set of machinery, which uses a lot of investment, a lot of time, a lot of money, you can’t get it to work.” Cards on the table, I’m somewhat sympathetic to this argument because academics aren’t exactly great at making election forecasts. Usually, the people with skin in the game are the most accurate. Warner’s argument is that the approach Electric Twin takes — which includes, for example, making multiple predictions for each synthetic respondent using different models and prompts and subsequently averaging those to get a final prediction in a sort of ensemble forecast — produces better results than the simpler academic models. Warner shared a comparison between his method and the method from a recent academic paper with me, and Electric Twin was indeed able to get more accurate replication. But even still, he acknowledged that synthetic sampling “is not a crystal ball.” “If you asked me, do I think using other data sources will be more accurate than asking somebody who they will vote for, I would probably say no. But if you asked me ‘would your system be useful for our turnout modeling today?’ I would say yes.” For better or worse, it looks like the method is already getting more popular in the market research world. Most of the clients Aaru touts these days are businesses like EY and McDonald’s. And AI will probably begin to pop up in other parts of the political polling process. Pollsters are already using it to code open-ended survey responses, and some firms, like YouGov, are testing using LLMs to ask survey respondents questions. More worryingly, one danger to actual polls is that AI agents can be used to infiltrate online surveys. Most online polls use various checks to prevent that from happening, but there’s conflicting evidence on how effective those filters are and how prevalent AI agents currently are in online panels. If those agents ever become impossible to detect, it might spell the end of online polling, but the solution isn’t to replace all of your respondents with ChatGPT. Silver Bulletin is a reader-supported publication. To receive new posts and support our work, consider becoming a subscriber. Subscribe 1 That particular poll obviously doesn’t meet Silver Bulletin standards for aggregation. But we exclude all Public Sentiment Institute polls from our averages because we classify them as an amateur polling firm. 2 You could argue that Fink meant the next presidential election, but (a) I’m also confident we’ll still have real polls in 2028 and (b) in that case he should have asked an LLM to define “general election.” 3 Quick caveat: that’s reporting from a Democratic pollster. It’s possible that Republicans are more willing to use AI in political campaigns. 4 Indeed, Silver Bulletin does not include “polls” produced by MRP in our forecasts or averages, and we think it’s extremely misleading when their practitioners describe them in a way that suggests original data had been collected among a large number of states or Congressional districts. 5 A recent report from Aaru and EY did show two examples of a synthetic estimate being closer than a survey to a real-world benchmark — but I’d take those findings with a grain of salt because the report reads more like an ad and didn’t involve any sort of prediction being made ahead of time. 6 For comparison, our odds for Harris on the same day were 48.2 percent.
Confessions from a laid-off sports columnist: Candace Buckner is done being sidelined
Sipping lattes and watering my garden of grievances didn't fill the stadium-sized hole in my heart. Thanks, sports, for letting me back in.
Protein is personal. Here's how to calculate your optimal intake
Protein is having a moment. Coffee chains are adding it into lattes. Many snack companies are labeling their products as high-protein. But how much protein do you really need? Host Marielle Segarra talks with NPR health correspondent Allison Aubrey about the different factors to consider when planning your protein intake.Follow us on Instagram: @nprlifekitSign up for our newsletter here.Have an episode idea or feedback you want to share? Email us at lifekit@npr.orgSupport the show and listen to it sponsor-free by signing up for Life Kit+ at plus.npr.org/lifekit
McKinsey's new AI leadership playbook: flatten teams and move faster
McKinsey and other consulting firms are using AI to streamline management structures — what some call The Great Flattening.
'We need to keep it going': Downtown Platte City sees rise in visitors as new businesses open their doors
Downtown Platte City is experiencing new momentum as a newly completed master plan aims to transform the area from a "drive-through" community into a true destination.
Young researchers showcase projects at North Platte science competition
Students from across Greater Nebraska presented research projects Monday during the Nebraska Junior Academy of Sciences Western Regional Science Competition at Mid-Plains Community College.
Young researchers showcase projects at North Platte science competition
Students from across Greater Nebraska presented research projects Monday during the Nebraska Junior Academy of Sciences Western Regional Science Competition at Mid-Plains Community College.
Business leaders and legislators gather for discussion in Youngstown
The movers and shakers of the Valley got together for breakfast Friday morning, hoping to make some connections.
Who is the Latter-day Saint BYU student dividing the right?
A college Republican group tapped a Latter-day Saint BYU student as political director. Not all conservatives are happy.
AI Is Giving You Bad Advice to Make You Feel Validated, Scientists Warn
Flattery will get you nowhere.
Critically endangered hare spotted in surprising location for the first time in 40 years — but it was already dead
Scientists in China have announced the first confirmed sighting of the critically endangered Hainan hare in part of its native range in four decades, after spotting its completely flattened carcass on a roadside.
Comings & Goings
Here’s a look at recent changes in the business landscape in the Sioux Falls area.
Consulting firms say AI agents are upending the company org chart
As a torrent of AI agents enter the workforce, consulting firms are predicting a new "Great Flattening" of the corporate management structure.
M5 MacBook Air’s SSD Speeds Beat M4 Pro Models, Obtains An Impressive 229.96% Performance Increase Over M4 MacBook Air Lineup
The SSD on the M5 MacBook Air has been substantially upgraded, with the latter not only handily beating the M4 MacBook Air but also M4 Pro models
Colorado Democrats, Republicans fight over ballot fiscal information
Republicans and Democrats clashed anew over legislation that would require identifying which programs would see a funding reduction if a ballot measure passed, with the former saying it’s yet another way for the government to control the campaign narrative and the latter insisting it provides transparency to voters. House Bill 1084, sponsored by Denver Democratic […]
Remembering Jesse Jackson
The late Reverend Jesse Jackson was — and still is — a revered civil rights activist, political trailblazer, and pop culture icon. For his critics, he was also villainized, or at the very least, a punchline. As Jackson's home going ceremony continues, we take some time to remember how Jackson shaped American politics with journalist Adam Serwer, who warns us not to flatten Jackson into a cliche or caricature.
Lakers flattened by Celtics on Pat Riley's Statue Day
The Celtics flatten the Lakers 111-89 and spoil Pat Riley's statue unveiling.
Mishawaka massage parlor closed by St. Joe County health department
According to a latter on the front door, New Feeling Massage was shuttered after a complaint and inspection.
Experts Warn: The Dangerous Blur Between Science and Wellness in Mental Health Bestsellers
A marketplace where labels blur In many bookstores, titles rooted in clinical science sit inches from glossy self-help guides promising instant serenity. That proximity can make rigorous research look interchangeable with lifestyle advice, especially when everything shares the same bright displays. Readers encounter a single aisle labeled “psychology,” even when the content ranges from peer-reviewed evidence to spiritual rituals. The result is a subtle but pervasive blur, turning a complex health landscape into a grab-bag of mixed claims. Why the shelves can mislead Retail categories are built for convenience, not for methodological clarity or clinical accuracy. When “development personal” or “wellness” becomes the default bin, evidence-based psychology competes with coaching manifestos and mystical manuals. The visual language of covers—calming color palettes, confident subtitles, glowing endorsements—flattens the distinction between randomized trials and anecdotal wisdom. In that aesthetic harmony, a guide on cognitive behavioral therapy may appear no more “serious” than a book on moon manifestation. The stakes for readers and patients Confusion carries real risks, including delayed care when people self-treat serious symptoms with untested routines. Vulnerable readers—facing depression, trauma, or anxiety—may be swayed by charismatic voices over careful data. Some messages frame recovery as pure willpower, which can amplify shame when symptoms persist despite effort. Others overpromise universal solutions, ignoring cultural context, diagnostic nuance, and comorbidity. “Shelving is not neutral; it shapes beliefs, expectations, and choices.” What professionals and retailers are asking Clinicians and public-health experts argue for clear, readable signage that separates science-based mental health from broader wellness. Books by licensed psychiatrists or psychologists that cite peer-reviewed studies could be grouped under “Evidence-Based Mental Health.” Adjacent space might host reflective memoirs, coaching workbooks, or contemplative philosophy—valuable in their way, but clearly labeled as non-clinical guidance. Booksellers emphasize their dual role as cultural curators and commercial actors, noting they respond to demand while striving for quality standards. How clarity could look and feel The goal is not to police ideas, but to help readers navigate with confidence. Transparent categorization respects reader autonomy while lifting the signal of credible practice. Clear tags—such as “scientific references,” “clinical overview,” or “personal narrative”—can work like map legends, turning a maze into a route. And when a book blends modes, hybrid labels can acknowledge both insight and limitation. A practical checklist for choosing wisely Check the author’s credentials: clinical license, academic affiliation, or relevant training. Scan the references: citations to peer-reviewed journals or reputable guidelines. Look for scope limits: clear statements about who the book is and isn’t for, and when to seek care. Seek methods, not miracles: approaches tested across diverse groups, with measurable outcomes. Watch the language: be wary of absolute claims, stigmatizing tones, or one-size-fits-all promises. Cross-verify with trusted bodies: national psychology associations or public-health agencies. The publisher’s responsibility Publishers can raise the bar by standardizing disclosure on methods, sample sizes, and limitations. Editorial policies could require conflict-of-interest statements, transparent citations, and plain-language summaries of evidence. Marketing should avoid medicalized framing for books that lack clinical validation, even when sales incentives press for bold claims. When a manuscript mixes reflection with research, honest jacket copy can prevent false equivalence. Coexisting without confusion Wellness writing can offer genuine comfort, perspective, and daily habits that support well-being. Scientific texts can provide structured tools, validated therapies, and realistic expectations for progress. The aim is to let these strands coexist, while giving readers the navigational cues to tell them apart. With clearer shelves, informed labels, and modest design tweaks, we can protect reader trust—and keep the aisle both inviting and intelligent.
NASA’s Juno Mission Redefines Size, Shape of Jupiter
Data from NASA’s Juno mission has revealed that the solar system’s largest planet is slightly smaller and more “squashed” than previously
'Textbooks will need to be updated': Jupiter is smaller and flatter than we thought, Juno spacecraft reveals
Jupiter is smaller and flatter than scientists previously thought, new measurements of the gas giant reveal.
Deflated: Israeli scientists find Jupiter is smaller than previously thought
Using data from NASA's Juno spacecraft, Weizmann Institute of Science researchers make most precise measurement to date, say the gas giant is thinner and flatter than believed
State Affairs Florida launches with Dara Kam, Jim Saunders
'Opening a Tallahassee bureau lets us bring depth, context and institutional knowledge to coverage that too often gets flattened by daily churn.'
‘A sacred space of healing’: Church of Jesus Christ transforms health center in Liberia
A health center in Liberia was in ruins until it was transformed into “a sacred space of healing” through a project funded by The Church of Jesus Christ of Latter-day Saints.
Commentary: They said Katie Porter was dead politically. I checked her pulse
A one-two punch of unflattering videos caused many to write off Porter's gubernatorial candidacy. But the former O.C. congresswoman remains a top contender.
TABOR and the Colorado Constitution’s fiscal Gordian Knot
A corporate president advised me once there are two kinds of lawyers: “those who tell you why you can’t do things and those who figure out how to get things done anyway.” He only hired the latter. Since the adoption of the TABOR amendment in 1992, the Colorado legislature has opted for counsel from the […]
Halal Munchies opens for business in Loudoun County
A new restaurant called Halal Munchies has officially opened its doors in Loudoun County. The restaurant specializes in burgers, Philly cheesesteaks, rice platters, gyros, and more. Halal Munchies can be found in the Riverside Square retail center in Ashburn. That's the same center on the north side of Route 7 with the Texas Roadhouse restaurant.
Kate Hudson reveals letters Daniel Day-Lewis used to send to her dressing room
Kate Hudson is remembering the 'flattering' letters that Daniel Day-Lewis used to send to her dressing room that were written as his character Guido Contini when they filmed their movie musical, 'Nine.'
Jimmy Butler takes No. 2 spot in updated most unflattering sports card rankings
A puzzling new patch jumps high up our rankings of memorably bad sports cards.
Lion Forge Entertainment & Boy Scouts Org Scouting America Set Strategic Partnership
Lion Forge Entertainment & Scouting America have formed a strategic partnership, the first of its kind for the latter, to develop original content.
Amy Poehler mistakes Gwyneth Paltrow for Nicole Kidman in middle of interview
Gwyneth Paltrow was flattered mid-interview when Amy Poehler mixed her up for Nicole Kidman, joking, 'Thanks for thinking I'm Nicole Kidman. Bonus!'
The year the Capitol Christmas tree was delivered by a senator
The voice on the phone was familiar, but the request was not. It was the latter part of September 2000. The person on the other end of the line was U.S. Sen. Ben Nighthorse Campbell. Over the years I had a number of calls with Ben as he served in different elected roles, so I was […]
Unique downtown Platteville business faces uncertain future
PLATTEVILLE, Wis. — A pride flag with the phrase “You Are Loved” hangs above the front door of Driftless Market and Deli.
Measles case reported in Platte County, health department says
A confirmed case of measles has been reported in Platte County.
Latter-day Saint Apostle Jeffrey R. Holland hospitalized due to 'ongoing health complications'
Jeffrey R. Holland, acting president of the Quorum of the Twelve Apostles of The Church of Jesus Christ of Latter-day Saints, has been hospitalized for treatment of "ongoing health complications,"
President Jeffrey R. Holland hospitalized with 'ongoing health issue'
President Jeffrey R. Holland has been hospitalized to be treated for ongoing health complications, according to a statement from The Church of Jesus Christ of Latter-day Saints.
LDS Church President Jeffrey Holland hospitalized with 'health complications'
President Jeffrey Holland of the Church of Jesus Christ of Latter-day Saints has been hospitalized for health complications
Cards Wallop #17 Tennessee 89-65
In the first month of the season Louisville had some games against top-ranked opponents that they lost because they went flat for a quarter and couldn’t recover. Today the Cards flattened #17 Tennessee in the 4th quarter. In the first half both teams were playing evenly in a fast-paced game full of pressing and aggressive […]
Susie Wiles offered unflattering assessments of her colleagues to Vanity Fair. In return, they showered her with praise
Of all the blunt assessments White House chief of staff Susie Wiles shared with Vanity Fair over the past year, perhaps her sharpest words were aimed at Attorney General Pam Bondi.
I shopped at Walmart and Target for my family's holiday gifts. For a few reasons, I'm sticking with the latter.
This December, I shopped for the holidays at Target and Walmart to see which chain had better sales and prices on presents for my kids and husband.
Warner Bros. Discussing Major Move With DC Comics Amid Netflix Merger
Warner Bros. is discussing a major move with DC Comics amid the company's merger with streaming giant Netflix. Netflix's acquisition of Warner Bros., which comes with the latter's media library and HBO properties, shook up the entertainment world. However, there are other moves afoot amid the ...