SCROLL NEWS / DISCOVERY
Search headlines
Find the stories shaping the conversation.
Results for " Mena " 263 found 🔀 AI-powered Shuffle
Dennis The Menace
Click here to view this article from TheDerrick.com.
Xeris adds longtime biotech exec to its board
The move to bring Menassie Taddese on comes amid reports that the Chicago-based rare disease and endocrinology drug company is being considered for acquisition.
Towards Integrated Climate, Migration and Health Action in the MENA Region
Analysis in English on World about Climate Change and Environment and Protection and Human Rights; published on 3 Nov 2026 by IOM
Lakers predicted to trade for $150M high-intensity defensive menace to pair with Luka Doncic
The Los Angeles Lakers are slowly becoming a tough team to beat. They could get even tougher by getting this defensive pest in a potential deal.
Belief in ghosts and magic linked to faith and trust in science, study finds
A new study suggests that Americans who believe in God while placing strong trust in science and reason may be more likely to believe in ghosts, curses and other supernatural phenomena.
The Menacing MAGA Way to Remake European Politics
The U.S. is trying to micromanage allied governments to an unprecedented degree.
Best Celebrity Halloween Costumes: Kim Kardashian as North West, Paris Hilton as Britney Spears and More
Halloween and Hollywood go hand in hand, especially given that most costumes draw inspiration from entertainment. From iconic movie characters to musicians to pop culture phenomena, the costume refere...
Cleetus McFarland to run 2027 ARCA schedule with Richard Childress
Cleetus McFarland will drive the No. 33 car full-time for Richard Childress Racing during the 2027 ARCA Menards Series season.
Halloween maze is 'phenomenal' business for Caverswall Creamery
Caverswall Creamery says it gets thousands of visitors visiting its Halloween scare maze.
I've lived the dream of 'Wicker' 4DX, and it was phenomenal
What if this was one of the best theatrical experiences of my life?
One of LA’s most dangerous areas could add ‘entertainment zones’ with public drinking under new proposal
Similar entertainment zones are are active in Santa Monica's Third Street Promenade and Culver City.
A golden age of science is coming
It’s almost hard to remember, but just a few years ago, a lot of very smart people thought that science was in terminal decline. Respected researchers were writing papers with titles like “Are Ideas Getting Harder to Find?”, “Papers and patents are becoming less disruptive over time”, and “Slowed canonical progress in large fields of science”. In 1996, science writer John Horgan even published a book called The End Of Science: Facing The Limits Of Knowledge In The Twilight Of The Scientific Age. The fundamental idea was that the Universe only has so many insights to discover, and that we’ve picked the low-hanging fruit. It was the idea that Joseph-Louis Lagrange expressed when he said that “we cannot find more than once a system of the world to establish.” As the big ideas and the simple ideas get mined out, we’re forced to throw ever more brains at the mysteries of nature just to keep scientific progress going at a fraction of its old pace: It looked like science was hitting a wall. Then along came AI. It’s far too early to tell how much AI will eventually speed up the growth of total factor productivity. But already we can see signs of a speedup in science. Anthropic Founder Jack Clark assembled some of the hopeful data points in a recent lecture: [ Dror Poleg@drorpoleg "If you pick different parts of science, you see the same pattern show up: Progress is accelerating, and it has started to accelerate in the last two years." Jack Clark @jackclarkSF I’m speaking at the IMF in an hour about the singularity and why I believe it has begun and the choices we'll need to make. Watch live here: https://t.co/Hj9HzcXx5h 6:08 PM · Oct 18, 2026 · 21.2K Views 2 Replies · 10 Reposts · 123 Likes ](https://x.com/drorpoleg/status/2111882070376980529) Anthropic is accelerating its investment into drug discovery, and is already announcing some impressive preliminary results: [ BioTender@Junioryu136689 BREAKING: Anthropic unveils early results from six Claude-powered drug development collaborations. • 70% shorter CAR-T signaling domain • ~35,000 antibody designs • >10× tighter antibody binding • 89% less batch-record review time Still largely preclinical. Anthropic @AnthropicAI Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own. In doing so, we’ve learned much more about how Claude can support the many stages of 9:43 PM · Oct 27, 2026 · 11.2K Views 3 Replies · 24 Reposts · 205 Likes ](https://x.com/Junioryu136689/status/2115197821150495150) Claude also appears to be enabling rapid progress toward a treatment for food allergies. OpenAI, meanwhile, announced a possible breakthrough treatment for neurodegenerative disease. Meanwhile, Google Cloud Chief Scientist Pushmeet Kohli has a list of recent scientific advances that have been enabled by its new Gemini model, including breakthroughs in nuclear fusion reactor design, rare disease research, and quantum computing: [ Pushmeet Kohli@pushmeet Gemini 4 Argon is a step change in model performance. In recent weeks, it has had a transformative impact on the Science projects in our team at @GoogleDeepMind and our external collaborators, and helped make a number of remarkable advances across scientific disciplines. 🧵👇 4:47 PM · Oct 13, 2026 · 36.5K Views 8 Replies · 41 Reposts · 497 Likes ](https://x.com/pushmeet/status/2110049807385702623) But as cool as these stories sound, they’re just very minor, preliminary efforts. There are a number of reasons to think that AI is going to propel us into a golden age of scientific discovery. That age might not last forever — AI might still run into diminishing returns eventually. But the next few decades are probably going to be an absolutely amazing time for human science. The number of “effective researchers” is no longer limited The most important input into science is scientists themselves. Until this year, that meant human brains — talented, highly trained human brains. The number of trained human brains could be increased by sending more people to grad school, but only to a point — the smartest people tend to be sent into the hardest research fields first, and if you 10x the number of researchers, the average quality will go down. This constraint was already starting to bite, as Ekerdt and Wu argued in 2024: We argue that a substantial portion of the downward historical trend in U.S. research productivity is a composition effect resulting from self-selection in researcher ability and the dramatic expansion of the research sector…[W]e find that this composition effect has lowered average researcher ability by between 37% and 53%[.] And of course, low fertility was making the problem worse, because fewer children meant fewer people who were able to become future scientists. AI just blows up this constraint completely. If an AI agent can function as an autonomous researcher, there’s no constraint on the number of researchers in the world — you can just build more of them, by building more computer chips and data centers that enable the running of more AI agents. Whether or not massive hordes of agents can collaborate to solve individual problems much faster, increasing the number of agents allows them to tackle many different research questions in parallel. What’s more, these AI “researchers” can be trained incredibly quickly compared to human beings. A human scientist takes decades to train, and more years to reach the frontier of their research field by diligent reading and conversation. This is the “burden of knowledge”, and it’s commonly believed to be one reason ideas have been getting harder to find — by the time human scientists can get up to speed, they’re often so old that their ideas are no longer novel. AI just annihilates this constraint — it can assimilate the entire literature and reach the frontier of research extremely quickly, and it can also tell human scientists where the frontier lies without forcing them to discover that for themselves. It can also pivot to new research directions more easily than humans can. And there’s also a self-reinforcing economic cycle here. Because scientific advances enable higher GDP, they enable more resources to be invested into the creation of yet more electronic “scientists”. Now that doesn’t mean the amount of scientific research goes to infinity — there may still be some essential bottleneck task that human researchers are still needed to perform. There are some indications that AI’s progress on open-ended conceptual research tasks is slower than in other dimensions, and it may be that humans are still needed to provide some of this long-term conceptual thinking. I’d bet against this being true for much longer, but it might be true for a long time. Even in this most “pessimistic” case, though, the amount of effective capital that scientists can use to leverage their work just went up by a lot. AI eliminates the theory bottleneck Science proceeds by an iterative process of theory and experiment. The theory part of that cycle is typically short, but non-trivial — it took a couple of years after the blackbody radiation spectrum was observed for Max Planck to come up with the quantum hypothesis to explain it, and decades longer before quantum theory as we now know it was created. It took about a year for Watson and Crick to figure out the shape of DNA after the requisite data was gathered. AI will basically eliminate the theory bottleneck entirely — or at least shorten the turnaround time between experiment and theory by an order of magnitude. AI is an absolute beast at math. Recently, an OpenAI model solved some of the most important open problems in computer science, math, and theoretical physics, and no one even batted an eyebrow because that sort of triumph is becoming increasingly commonplace. One of those solutions was a proof that the Standard Model of Particle Physics could be mathematically well-defined — a problem that human theorists had so far been unable to tackle. Not all research relies equally on theory, but understanding novel experimental results almost always involves some important component of either mathematical or spatial reasoning. That part of the task has now been made much, much faster. And on top of that, science is now open to a greater number of humans who aren’t naturally good at theorizing. AI can read the whole literature Much of the work of human scientists involves reading and understanding endless amounts of papers and going to endless conferences and seminars. The purpose of that work is to understand the existing scientific literature. Understanding the literature allows scientists to do the following things: Come up with new ideas for hypotheses to test Avoid doing research that someone else has already done Synthesize approaches from different areas or fields AI can reduce this effort to almost zero. Consider this excerpt from OpenAI’s blog post about their new research into neurodegenerative disease: The team divided the analysis among thousands of AI agents powered by GPT‑Rosalind, an approach we call distributed biological reasoning. The agents examined a whole-brain CRISPR atlas…a dataset showing how gene disruptions affect different types of cells across the mouse brain. Each agent investigated a gene disruption, analyzed cellular responses, searched scientific literature, and proposed explanations for the results. Their reports were combined into a reasoning atlas linking genes, cellular effects, relevant publications, and possible biological mechanisms. The research team estimated that comparable human analysis and literature review, conducted one perturbation at a time, would take months to a year. The agents reproduced findings from human analyses while uncovering additional leads. Their assessments of novelty and scientific value also aligned with judgments from blinded human experts. These findings help prioritize further experiments needed to test the proposed biological mechanisms. Some of these insights point to new leads for understanding brain disease. [emphasis mine] This is one case in which parallel work by a large number of agents really does make a huge difference: [ Haider.@haider1 this is actually insane openai deployed thousands of GPT-Rosalind agents to analyze millions of mouse brain cells in 32 minutes, work that could take human researchers months to a year also the agents uncovered new leads for brain diseases like Alzheimer's and Parkinson's OpenAI @OpenAI GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration? DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in 2:41 PM · Oct 21, 2026 · 51.5K Views 26 Replies · 95 Reposts · 1.26K Likes ](https://x.com/haider1/status/2112917197903540516) Not only does instantaneous literature review vastly speed up the research process, but it allows AI to make novel conceptual leaps from combining approaches from wildly different fields of research. AI regularly does this in math research, combining results, approaches, and theorems from far-flung places that no human mathematician would have thought to combine. It can do it in science, too. Much of scientific innovation, historically, has been “recombinant” innovation — scientists applying insights from one field to another. With AI, essentially all research is now cross-disciplinary — AI can read not just the literature on a particular subject, but the literature on a million other subjects that might have produced useful techniques or insights for the problem at hand. Superscience So far, all of the factors I’ve listed are ways that AI can speed up science as it’s already done. I’ve basically described how AI can send gigantic hordes of superhumanly fast, superhumanly well-read, superhumanly mathematically gifted researchers to re-accelerate scientific discovery. But it’s also possible that AI will enable types of discovery — and ways of understanding the natural world — that no network of humans, no matter how large or how brilliant it was or how long it had to work, would ever be able to discover. In a post back in July, I wrote about how that might work: What if there are lots of…aspects of the Universe that [are] too complex to understand in terms of simple laws, but not so complex that they just dissolve into unknowable chaos? It’s possible that we can reliably control these complex phenomena with AI, even if we never reduce them to the kind of principles that we can teach a grad student in a textbook… Another way of saying this is that there may be laws of the universe that humans can’t understand but AI can. I call these “cloud laws” — causal regularities that can be exploited by technology, but which are too diffuse and complex for an individual human being to either intuit or communicate… Perhaps social sciences like economics, sociology, and political science obey similarly complex regularities, and AI can help us find them. Perhaps there are physical processes — plasma, or topological materials, or aerial turbulence, etc. — that obey cloud laws instead of chaos?… [H]uman collaboration is bottlenecked — it’s limited by our ability to intuit patterns at an individual level, and to communicate these patterns from one individual to another. AI, being a computer, just doesn’t have this sort of limitation; it can work with vast, diffuse patterns without having to break them into pieces or simplify them in order to compress them into the tiny pipelines of person-to-person explanation… If much of the Universe turns out to be ruled by cloud laws, we could be on the precipice of a scientific renaissance. In order to discover cloud laws, AI will need huge amounts of data about the natural world. AI figured out human speech by assimilating essentially all of the text humans have ever written. If it’s going to figure out hidden patterns in biology, neuroscience, materials science, etc., it’s going to need similarly massive amounts of data from physical instruments. That data will be far, far more than humans — individually or collectively — would be able to parse, label, characterize, or model. But AI was built to do this. If scientists simply build huge arrays of sensors to measure complex phenomena like the brain, the cell, the economy, etc., they may be able to feed this flood of data to AI directly and bypass human cognitive intermediation entirely. AI would then learn about the world directly, and it might learn things that humans never could. This “superscience”, if you want to call it that, would actually go beyond the kind of science humans have done heretofore. Many of the technologies it yielded would be beyond human comprehension — indistinguishable from magic. But to the AIs, they would make perfect scientific sense. In any case, it seems clear that the scientific slowdown that threatened human progress will now be delayed — at least for a while. Unless humans have somehow found most of the actual exploitable regularities in our Universe, we’re about to enter a new golden age of science. Subscribe Share
Brewers Win First World Series with Game 5 Victory
After 56 seasons of waiting, the Milwaukee Brewers are World Series champions for the first time in their history. They finished off the Tampa Bay Rays with a 4-1 victory in Game 5 at Tropicana Field on Wednesday night. Riding a phenomenal start from ace Jacob Misiorowski, Milwaukee followed their recipe of timely hitting and …
Phantom Blade Zero PC Performance Benchmarks – Fast-Paced Wuxia That Looks Phenomenal In Path Tracing & Boosted By NVIDIA RTX Tech
Phantom Blade Zero is out now on PC, offering increased graphics fidelity through NVIDIA's DLSS 4.5 technology, Path Tracing, and much more.
Prominent political figures are campaigning nationwide, what about in Wisconsin?
WLUK FOX 11 is your source for Balanced News and Severe Weather Coverage for Appleton, Shawano, Sturgeon Bay, Kewaunee, Two Rivers, New London, Bonduel, Pulaski, Suamico, Menasha, Neenah, Shiocton, Ashwaubenon, Algoma, Mishicot and Wrightstown.
Sports Equinox on Tap With MLB, NFL, NBA, WNBA and NHL All in Play at the Same Time Monday Night
If you love sports, Oct. 26, 2026, will be tough to beat. Five professional leagues in North America are in action at the same time on Monday night, a phenomena known as a sports equinox. Major League Baseball and the NFL will compete for the most viewers while the NBA, WNBA and NHL give their ...
Man arrested on“ Miami Vice ‘85 ”set after allegedly brandishing a butcher knife
Alex Perez was arrested and subsequently charged with menacing and criminal possession of a weapon.
‘Miami Vice ’85’ set allegedly menaced by man brandishing a butcher knife
‘Miami Vice ‘85’ filming took a menacing turn on Oct. 23, when a man allegedly brandished a knife on the Brooklyn set of the Michael B. Jordan and Austin Butler film. The man has since been arrested and charged.
Q+A: How this private equity group raised $1.3 billion investing in fr
Doug Kennealey, co-founder of Princeton Equity Group, said franchises are "phenomenal" and "cash-rich" business models. The firm secured $1.3 billion in two months for its most recent fund.
5 things to know about The Promenade at Sunset Walk's Trunk-or-Treat
For the 7th year, an Osceola County entertainment destination rocks out its trunk-or-treat festivities, free of charge.
In Madison Opera’s first-ever ‘Norma,’ ‘the melodies are phenomenal’
Madison Opera presents Vincenzo Bellini’s bel canto masterpiece on Oct. 30 and Nov. 1 in Overture Hall to open its 2026-27 season.
Dennis The Menace
Click here to view this article from TheDerrick.com.
Tracking tsunamis triggered by extreme weather
As much of Western Europe faced record-breaking temperatures and extended drought this summer, Croatia experienced another weather event that could also set a worrisome precedent.Over the course of two weeks, a series of meteorological tsunamis (meteotsunamis) struck Croatia’s Adriatic coast, alarming both residents and tourists. Social media posts showed flooded seaside promenades and people walking through knee-deep water. Fortunately, no deaths or major damage were reported.In a world where natural disasters seem to be increasing, meteotsunamis — tsunamis caused by rapid weather changes – rarely make headline news. But warming sea temperatures and changing atmospheric conditions may help explain why these phenomena could become more common, especially in shallower seas and inland lakes with wide coastal shelves.“We have definitely become more aware of them, and there have been a lot more reports of these events in the last 10 years,” says Jadranka Šepić, an associate professor of environmental physics at the University of Split whose research focuses on efforts to track meteotsunamis in real time. She is also one of Croatia’s ambassadors for Science Comes to Town (SCTT), a European Commission-funded programme aimed at making research more accessible to the public.Šepić sees two possible reasons for the apparent increase in meteotsunamis. One is that photos and videos shared on social media are providing more empirical evidence, while rising air and sea temperatures could also play a role. The geophysicist “cannot say with certainty” that warming is a contributing factor because research is still ongoing. “But I can say that previously in Croatia we might have had one exceptionally strong event every 10 or 15 years, and one strong event every five years, and within 15 days this summer we had five strong events,” Šepić notes. “This is not typical.”‘A fist against the sea surface’Unlike tsunamis that are triggered by underwater earthquakes or volcanoes, meteotsunamis are caused by sudden changes in atmospheric pressure combined with other rapidly developing weather events, such as thunderstorms. The effect “is like pushing a fist against the sea surface,” Šepić explains. The resulting oscillation intensifies as it reaches shallower water, and “can be far more destructive than a wind-driven wave because meteotsunamis are accompanied by very strong currents than can penetrate much deeper inland.” The meteotsunami, she continues, “then behaves the same as a tsunami — they slow down and grow as the sea shallows, and then grow further in places like harbours due to further shallowing and narrowing. When they come ashore, they can be very destructive — taking everything with them out to sea and then taking it back.”Croatian research institutions have tracked such sea oscillations since the 1930s because the relatively shallow Adriatic Sea is prone to meteotsunamis. The strongest recorded so far was in June 1978, according to the Adriatic Meteotsunami Catalogue, which is supported by the European Research Council (ERC), Croatian Science Foundation and the country’s leading research institutions. During that event, six-metre-high waves flooded the coastal town of Vela Luka on Korčula Island, causing major damage.Other meteotsunami “hotspots” in Europe include the Mediterranean Sea as well the Atlantic coastal shelves off France, Portugal and Spain. In June 2006, a meteotsunami with five-metre-high waves swept through the harbour of Ciutadella in Spain’s Balearic Islands, causing widespread damage to boats. Several less powerful events were reported in the Balearics and off the coast of Spain this summer, leading to some beach closures.Forecasting is challenging because of how quickly meteotsunamis can develop and their uncertain trajectory. Šepić is involved in two ERC-funded research projects — SHExtreme and MeD-Track — aimed in part at strengthening monitoring and real-time data collection. Access to accurate and immediate information is essential for early-warning systems.Early exposure to meteotsunamisŠepić first learned about meteotsunamis from her parents while growing up in Croatia. She later had the opportunity to investigate these events during her master and doctoral studies in geophysics at the University of Zagreb. The geophysicist has also conducted research at the Institute of Oceanography and Fisheries in Split, the University of the Balearic Islands in Palma de Mallorca and the Institute of Ocean Science in the Canadian province of British Columbia.Projects like SCTT are important to raise awareness about research and inspiring young people to pursue studies and careers in science, notes Šepić. She credits her colleagues at the University of Split and the Institute of Oceanography and Fisheries for their community outreach and engagement in the European project, which includes partner universities and institutions in Brest (France) and Kiel (Germany). As an example of town-gown collaboration, Šepić highlights her own university’s ‘Oceanographers on the Island’ programme. This initiative offers workshops and hands-on learning for children living on numerous Croatian islands.“It is a great privilege for Split to be involved in a project like Science Comes to Town, which is the first of its kind in the European Union," Šepić says. As for encouraging new generations of scientists, “This is a great effort, and I hope that we will see an effect in a few years.”Science|Business, which connects policymakers, academics and industry through its news reporting, analysis and events, is an SCTT partner.
OHIO researchers Faiz Rahman, Savas Kaya receive $550,000 NSF award for next-generation nanolithography
Nanoscale and Quantum Phenomena Institute (NQPI) members Dr. Faiz Rahman and Dr. Savas Kaya recently received a new U.S. National Science Foundation award for their research.
Sundar Pichai: Google’s Frontier Imperative, Compute Scarcity Dilemmas, Future AI Products and Businesses
Alphabet CEO Sundar Pichai has little patience for doubts about Google’s willingness or capacity to compete at the frontier of AI. His company’s latest Gemini 4 Argon model — long-promised and recently delivered — beats OpenAI and Anthropic’s latest public models on coding, math, science, and knowledge-work benchmarks and has placed Google’s AI back among the world’s best. Amid chatter that Google was fine with good-enough lightweight ‘Flash’ models, Pichai pushed back hard against any suggestion that company is limiting its research ambitions. “We won’t do it any other way,” he told me in a Big Technology Podcast interview recorded this week at Google’s Mountain View headquarters. Pursuing cutting-edge research is costly for Google, requiring compute and chips that otherwise could be sold at a high markup by its cloud business. But Pichai said allocating resources to frontier AI development is “ground zero” for Google. “Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development,” Pichai told me. In our conversation, we discussed Argon (which Pichai says processed three times as many tokens as Gemini 3 in the 72 hours after launch), AI’s role in developing better models, the AI interface of the future, competition with OpenAI, Google’s partnerships with Anthropic and Apple, data centers in space, and the nature of his optimism. You can read the full conversation, lightly edited for length and clarity, below, or listen to it on Apple Podcasts, Spotify, YouTube, or your podcast app of choice. Alex Kantrowitz: Google is back at the frontier with Gemini 4 Argon, which beats OpenAI’s and Anthropic’s public models on benchmarks spanning coding, math, science, and knowledge work. The conventional wisdom was that Google had given up on the frontier to focus on fast, good-enough models for its products. That was wrong? Sundar Pichai: Very wrong. Look, we are so committed to being at the frontier. It’s in our DNA. We won’t do it any other way. We’ve been thinking about the AI frontier for well over a decade now. The frontier is very dynamic. It’s very competitive. It’s very exciting. I couldn’t be more pleased with how Argon has come together. We took our time with it. We made sure we tested it safely and deployed it carefully. We took a bit longer than our other models, given its capabilities. Across the board, be it for agentic work, knowledge work, coding, creative tasks, Argon is one of the really good frontier models. The first 72 hours since we launched, it’s almost up to 25 trillion tokens used, which is about three times what Gemini 3.0 had in the first 72 hours. And we are capacity constrained as we are serving it. Excited, but there are always areas….. You know, the frontier is very dynamic, and you have to keep evolving the models. There are areas which we can see we need to improve as well. We’ll be at work on all of that as well. Which areas? On any given model, Argon would be across the board better at everything if you just look even two months back. But the space is so evolving. Even on coding, for example, there are pockets where we know we need to do better, and there’s clear feedback. We’ll make it better. The argument for standard models is that they’re already good enough to build great products, with the frontier valuable only for certain tasks. Meta built Muse with good models rather than the best, and Google could put standard models into Maps, Gmail, and Search. Why isn’t that sufficient? It’s definitely not how I have thought about it at all. We are deeply committed to driving the state of the art and actually pushing where this technology can go, all the way from transformers. That’s a journey we’ve been on. You will see us continue to do that. When you’re at the frontier, you get an earlier look into the emerging capabilities, earlier than others, which helps you better prepare for the future. We are fortunate to have a wide set of opportunities across consumer and enterprise. Some of our cloud customers, for sure, want the model at the frontier. The frontier models will be better at developing the next set of models in an era of recursive self-improvement. I would argue it matters there. Internally, we have definitely seen a steep point of inflection by deploying Argon to our developers. It definitely tackles problems which our previous models could not do. Being at the frontier puts you at the innovation frontier and helps you drive that as well. There is room for models of all sizes and capabilities. That’s why we did Flash, Flash-Lite, etc. I agree with you that you can develop very good product experiences with not necessarily the most frontier model, because they tend to be slower and more expensive too. But we care about the Pareto frontier, and we’re committed to doing all of that. You said developing frontier models gives you a look at what’s coming. What do you see on the horizon? What makes this moment so exciting is you build something which you think is a culmination of months of work, and you put it out. You already see clear headroom ahead. We’ve all been working on these agentic, long-horizon capabilities, but clearly the frontier is going to have multiple of these agents working together to do things. That’s an example of an exciting paradigm underway. It’s also clear to me that users, both in consumer and enterprise, will have access to some multi-agent framework for them, working all the time doing things. It feels like a moment of infinite possibilities. Sergey Brin said one of Argon’s core innovations was relying more on the model to help develop the model. Yet incidents involving OpenAI’s bots breaking containment and Google’s bots accessing a site they shouldn’t have suggest these systems still aren’t perfectly aligned. Isn’t there reasonable cause for concern about accelerating toward recursive self-improvement? There are three parts to your question. Let’s first talk about RSI itself. You’re right, Sergey mentioned RSI being a critical contributor as we are developing Argon. But to be very clear, today, in a continuum, we are pretty far from the end state of RSI or something like that. The right way to describe it is you have RSI loops along with AI researchers in various aspects of model development. You almost have agents helping AI researchers in some automated way work together to build these models. It’s good to at least understand where we are today, and it’s super exciting. I expect that continuum to keep making progress as we go into next year. The second question is around safety. Security comes from defense in depth. You’re talking about alignment, obviously. We all are doing a lot of work to make sure the models are as aligned as possible. But it’s an active area of research, and there are clear gaps. That’s not the only thing we rely on. You have the work you do on alignment, but beyond that, we put a lot of effort into real-time monitoring as these models are working. Making sure you have good telemetry into what’s happening so that you can intervene in real time if you see unexpected behaviors. How you do that, the architecture with which you do that, how you make sure it’s all sandboxed and isolated in a way that it can continue doing its job during real-time monitoring — these are all areas of investment. Obviously, when we deploy these models, giving customers, enterprises, control, both with real-time monitoring, but their ability to decide where they deploy, what type of data which models ever have access to, etc. All that work is very, very important, and we are doing a lot of that. As an industry, we need to constantly up our game and take the time to do all this stuff, including dedicating the compute required to make sure you can safely deploy these models. The third part is: Is it all enough? This is why there are a lot of conversations in the industry, and I think it’s reasonable to be worried. The right way to approach something you worry about is early on thinking about what more we can do. As an industry, you’re definitely seeing increased levels of work on alignment, testing for safety, etc., as we deploy these models. The next step would be developing better standards so there are cross-industry standards of how we do these things, including the ability to evaluate using independent evaluators. If you look at areas like financial controls, we have accounting standards, we have independent auditors. Those are all the next natural steps for us as an industry to work toward, and regulation will end up playing a role as we go through all of that as well. Google pursues both language models and world models, while some other AI companies like OpenAI have focused more heavily on LLMs as the path to AGI. Why is world-model research important to you? As humans, you obviously perceive the world around you, and you’re taking all those inputs. Making sure these models are able to understand the laws of physics, simulate the world in high fidelity. All that, I think, are key enabling blocks for intelligence. We are working across all possible applications of this. Take an area like robotics. It’s not an accident: If you look at embodied reasoning benchmarks, Argon is state of the art. That all comes from our experience building world models. Inherently, I would expect there will be architectures which will converge all of this in the future. But for us, we view this as, today, this jagged frontier that is intelligence. We want to be at the frontier of all the possible approaches, and that will help us both drive better research, better insights, and develop a much better AGI model, is how we think about it. Some people argue Google should focus on selling its computing resources rather than using them for AI research. Cloud wants to sell compute at a high markup, while researchers need a very big computer to build the best models. How do you balance those demands? Ground zero for us is making sure we are investing in the compute that’s needed to be at the AI frontier. In 2015, I set the company to be AI-first. AI is that key horizontal ingredient across everything we do, all the way from Search to Cloud to Waymo. That is ground zero for us, making sure both for research and developing the models that we have enough compute needed. Beyond that, we have these independent businesses which each have their own long-range plans. They’re using those long-range plans to project forward, and we plan for compute for all of them. The cloud team, they have a business and they have a projection and they have demand signals. They have committed contracts. With that help, we can plan on a long-term compute trajectory for them. We’re fortunate to have this wide set of opportunities. There’s no company in the world which isn’t making trade-offs at any given moment in time. But the first principles we operate on is making sure we have enough compute to invest in the frontier, and that’s non-negotiable, and everything else works on top. Remember, we are building our own compute, our own data centers. There are long lead times. The compute we have today is a function of decisions I made in 2024. Even if you think back to a year from today, last year the agentic coding takeoff hadn’t happened. Today, obviously, when you sit and look at anything, everyone is short—not just us, other companies—and everyone wishes you had two times what you had planned for. That comes with the territory. At any given moment in time, we are planning for what we would need two to three years out in the future. You’re going to find some decisions you make may look suboptimal two years out, depending on where the state of the art is. I don’t spend too much time thinking about it. The way I think about compute allocation is making sure Google DeepMind, both for research and frontier model development, is cutting edge in terms of compute access. After that, we plan for all our businesses. It’s great we can provide our compute to other people too, like we have done. It allows us to scale that up, get real tests for it in the widest application set possible, test it in the real world, and make sure we are at the cutting edge of technology at every layer of our AI stack as well. Ben Horowitz relayed on a podcast that Andy Jassy had said compute was sold out until 2028. Are you seeing the same thing? If today a customer is coming out and asking us for compute in ’27, that is incredibly difficult to do. Even last year we went out and leased some short-term compute to accommodate some customers and help them out. But yes, we are all dealing with similar timelines. Every major technology shift seems to involve overbuilding, from railroads to fiber. Do you think that’s happening here? It depends on the time frames you’re looking at. This level of build, if I take a long enough time frame, it makes complete sense to me. We are at early stages of the most consequential technology ever, and this is not like fiber. It’s not dark. We are using it. We are capacity constrained on a daily basis. The applications, the underlying technology is improving rapidly. But running a company, the way I work through the moment is you look at your demand signals. You look at your committed revenue opportunities that you’re getting in the form of contracts. You balance that with the underlying technical capability, or internally you balance how we are using it internally, the model trajectories. Based on all that, you take a disciplined approach—a confident, aggressive, but disciplined approach—to plan out compute. But when you talk about the broader economy as a whole, you’re having people operate with various levels of risk. I focus on what I can control as a company and plan through it. If your question is, can there be an overbuild? Yes, because you can have some constrained components. Remember, what matters is a set of everything you need to build out that compute. Memory, electricity, electricians…. Land. Like 2,000 components or more. You could get constrained at some point. There could be things which cause bottlenecks, and then you could have overbuilds. There could be external shocks to the economy. There are macro risks. All that is possible at any given time. But am I confident that the compute we are planning for, we will have uses for it given enough time? Absolutely, yes. I was in the room when you said AI would be as profound as fire and electricity. If you believe that, shouldn’t you give researchers the biggest possible computer, even at the expense of today’s cloud profits? We’re all doing some form of that. Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development. What you’re seeing is true already. But you want to be thoughtful. Even our AI researchers have some constraints, which are also good. That’s what inspires creativity. That’s what helps you come up with a more efficient algorithmic breakthrough, maybe to use less memory. What we are committed to is to invest what’s needed to stay at the frontier. OpenAI President Greg Brockman told me a few months ago that the ideal AI product might have no interface at all—just as natural as conversation. What do you think the interface looks like in the age of AI? Computing historically has been humans adapting to computing. With AI, it’ll be the other way around. The technology will adapt seamlessly to how humans live and go about their day-to-day life. You want to be able to speak to that AI when you want to. It has context. It can be persistently running somewhere, give you continuity. You’re not dealing with a lot of complexity. It’s natural. All that makes sense to me. That doesn’t mean it won’t have any interface, however. Nowadays, even on my phone, Gemini voice models are so good. I can just press the microphone button. I can just ramble. That’s why we call it Rambler. I can ramble. It intelligently corrects with my personal context. Even my friends’ names, weird names, it gets it right, even if it first guesses it wrong. It’s amazing. I’m not going in, backspacing, editing once I finish saying it. It’s remarkable how good it’s gotten. But there are going to be moments you will need an interface. You may want to entertain yourself. You may want to watch a video. You may ask your AI to create something, and you want to watch it, consume it. The way I think about it is, you want it to be as seamless and as natural as possible, and that you are not doing the hard work adapting to whatever the interface is. The technology is adapting to how you’re working at any given moment in time. When I asked Sam Altman about competition from Google, he argued that OpenAI was building AI-native products and implied Google was bolting AI onto existing ones. Do you accept that framing, and can a “bolt-on” compete with an AI-native product? First of all, it’s a very dynamic moment. We are all pushing each other. OpenAI has pushed us as a company too. This is not just we are doing something to them. Far from it. Yes, Google went into its own version of a code red too. In the AI moment, all of us have to respond with varying levels of urgency at any given moment in time. We are constantly building new products as well. Gemini was built from the ground up as a product—the Gemini app I’m talking about. Or tomorrow, as all of us are adapting to agents, are you bolting agents onto ChatGPT, or are they building it natively? How would you think about that? You can always put these questions back. I don’t think of it that way. I think of it as you want to build world-class product experiences that are AI-native and they are winning. Some of it is adapting products, some of it is rethinking new experiences. They will all be part of how you approach this moment. How do you expect to make money from these AI interfaces? If an agent recommends a product and I buy it, should it take a cut of the sale, even if that’s disclosed? I’m going to put enterprise aside. Consumers are going to increasingly value this technology. Take software developers today. Developers are willing to pay for these coding models because it really helps make them more productive. Nobody would want to code the way they were coding three years ago, or even the same time last year. When you’re delivering value, there’s value to be had. I’ve never seen examples where consumer products really scale to billions of users, where people are using it intensely, and haven’t had monetization to go along with it. If you’re providing value to people, there is inherent value to be had. The nature of it may change. You’re asking a scenario in which agents are doing stuff for you. At the end of the day, you will have commercial needs. The agents need to fulfill those commercial needs. The providers on the other side are going to see value in that. There’s going to be some mechanism by which it gets fleshed out. That’s what an efficient system does. But what matters is that you’re building those world-class consumer experiences. I promised myself one product feature request: Can you make Gemini-powered search in Gmail as good as searching Gmail through ChatGPT? What’s going on here? One of the exciting things we announced recently is the unified Gemini agent for enterprise, and we’re bringing that to consumers. These are persistent agents which run 24/7 in the cloud. We’re spinning up a micro VM effectively for every query, and from the runtime, the harness, the model—it’s all a headless service. It’ll work everywhere, and it has your context with you. You can address this agent whether you’re in Workspace, in Search, in Gemini. Agents are going to drive this unification from a customer experience, which people are looking for. When you have a broad product portfolio and you’re moving forward fast, there are always areas where you’re moving forward faster than some other areas. That’s valid feedback. But we are putting a lot of time and effort into making sure, as we build out our agentic experience, that unification and that capability works well across all these services. People have asked where Google’s equivalent of Muse or Dots is. Do you anticipate creating a new product to compete with them? Our goal with Gemini is to be a personal, proactive, and powerful assistant. That’s what we are working toward. You saw us describe the early versions of it at Google I/O this year with Spark. Effectively, already, if you open the Gemini app as a Pro or an Ultra user, you see Chat and Task, and they start giving you that agentic experience. With Argon now, that capability is dramatically accelerated. What we announced recently in our enterprise event, we are bringing that to consumers as well. Soon in Gemini, you will be able to ask something, and it’s a continuum. You don’t need to think about whether you’re asking a chat or an agentic task. It’ll just automatically do the right thing, and it can work persistently in the background securely and get things done for you. Already, empirically, when I look at what’s coming into Gemini in our app, last year you would have tagged them and most of them would have been chats. But a steadily growing percentage is already agentic tasks in Gemini. Yes, we are going to bring personal agents to our consumers. It’ll work in the Gemini app. It’ll work in Google Search. It’ll work in Gmail. You can address it, call it, etc. We want to make sure we’re getting it right. It’ll be powered by Argon, and we are very excited to bring it to our users. Google has invested and committed tens of billions of dollars to Anthropic. What do you see in Dario Amodei that makes you want such a deep investment and partnership? Very early on, when we looked at the founding team of Anthropic, it was very clear to us this was a world-class team which was involved in some of the earliest GPT models. We were quickly able to assess that they would be at the frontier. We’ve always tried to identify and partner with companies which would be at the cutting edge of technology. We’ve done that with SpaceX. We’ve done that with Anthropic. That’s what we saw, and we had a chance to partner. Is your partnership with Apple to license Gemini for Siri expanding, contracting, or standing still? For both us and Apple, that partnership was about translating the capabilities of AI into better experiences for users. I thought Apple has done a phenomenal job of incorporating—they customize these models and build it into Siri—and it’s been great to see the reception. We are committed to doing more. You’re going to do more with them? There’s nothing specific to comment, but it’s a partnership. It’s working well. What have you learned so far about the feasibility of data centers in space? It’s a very exciting project. Projects like this remind me—I still recall that moment in the desert for the DARPA Grand Challenge, watching the Stanley car compete in it, which ended up being the basis for Waymo. With all these technologies, you’re at a moment in time where it looks a bit like sci-fi, but 10 to 20 years down the line, it’s actually working in a meaningful way. I feel the same in space. We’ve always believed in betting big on these technologies. Quantum has been a great example of it. We’re probably 10 years into the journey. Waymo, we are almost 20 years into the journey. Space, we are two to three years into the journey. It’s clear to me that it’s an approach which will make a lot of sense in the future. Being in sub-synchronous orbits with 24/7 access to the most abundant form of energy we have access to will make a lot of sense for this exponential increase in compute that we are going to need. Having said that, this is a challenging project. The team has disciplined milestones. It was a super exciting milestone to send the TPUs up to space. Sometime, as we are speaking, we are expecting a “hello world” moment from them. I look forward to seeing that happen, and we’ll continue investing here too. You previously said 25% of the code written within Google was written by AI. What’s the number today? That number in our world today is meaningless in the sense that every part of what we now touch is influenced by AI deeply. What we are tracking with Argon, for example, it’s been a point of inflection. People are using Argon to really go tackle complex projects, including projects which affect millions of lines of code. In the four weeks since we have launched Argon, we have seen a 30% increase in CLs, and more importantly, almost a similar increase—a one-third decrease in rollbacks. People are writing code more productively and better code with it. We are tracking it with newer metrics now. How are you dealing with opposition to data centers? If you can’t build in the U.S. the way you want to, where else do you go? We’re very committed to building our data centers very responsibly. When I look at our largest data centers in some of the communities where we have been the longest, I visit them, I talk to people. There are people who come and tell us their kids have gone to college because of our investments in these communities, and we’ve grown in those communities. To me, this is about doing it right. Engaging with the communities early, doing it transparently. We are committed to making sure we are bringing incremental power, and we cover 100% of the cost of our power needs for these projects. It’s understanding the impact on neighborhoods and making sure you’re working thoroughly to address them. Done rightly, you can continue making progress. But we are constantly taking feedback into account. I do worry not everyone operates the same way. People have been surprised by data centers showing up in their backyard. Those are all important. As an industry, we should continue to do better. But part of the reason, in a 20-year time frame, we are thinking about things like data centers in space is making sure we are able to put these data centers where maybe the trade-offs will be different. What unproven area of AI is Google working hardest to crack? Is it continual learning—getting models to keep updating after release—or something else? There are multiple parallel paths. You saw with Argon we have a million output tokens. With our Gemini models early on, we had a one-million context window on the input side. These are all examples of breakthroughs we are constantly working on. How do you think about synthetic data? How do you think about continual learning? How do you think about more efficient architectures? We do dedicate a meaningful percentage of our compute to these research bets too. It always goes hand in hand, including our world models. Those are all bets we are placing. Sometimes, as part of these bets, there are ideas that emerge which just make their way into the mainline models. Maybe we don’t fully talk about it, but we have multiple steps in these areas. Working in technology requires optimism that building something will improve the world, but those bets can leave real consequences when they fail. I recently returned to a town in El Salvador where enthusiasm for Bitcoin had given way to unfinished construction and something resembling a ghost town. How do you maintain the optimism you spoke about in your Stanford commencement address while accounting for those risks? I genuinely have a deep conviction that improving technology and improving access to technology makes people’s lives better. It’s been my personal experience in my life, out of which comes that deep conviction, optimism. But with that, I’ve always felt humanity’s journey is always about working hard to harness that technology to make it work well for society. The optimism is not an optimism that you just build whatever you want, whenever. You work hard to make sure you’re building technology in the service of humanity, to make the human condition better. That’s got to be the defining goal as we are approaching it. With that framework, I’m very, very optimistic. We are in very early stages of the kind of progress that we are going to see on many areas. We’re all talking about areas like healthcare. A lot of the progress is ahead. The ability to make things in a fundamentally cheaper way on many things where things have been getting expensive for a long, long time, discovering new materials, etc., which really bend the curve—it’s tough to step today and understand the impact of all that, but they’re going to be very profound. I’m very optimistic, but we have to be rightfully concerned about all the ways this technology can go wrong. Sundar, I know you don’t do many of these. Thank you. Thanks, Alex. Appreciate it.
The Romans Hires Burson’s Sam Buckett To Lead MENA Sports & Entertainment Offering
The agency is launching a dedicated sports and entertainment division in the region, building on existing work for Abu Dhabi Grand Prix organiser Ethara.
Mice cause ‘imminent health hazard closure’ at Westminster movie theater
AMC Westminster Promenade 24 was reinspected on Monday and allowed to reopen, Jefferson County Public Health records show.
The Romans Brings Sports & Entertainment Offering to MENA
The Romans brings its globally award-winning Sports & Entertainment offering to MENA, appoints Sam Buckett as managing director
This Week: Politics 101, 20th Street Bikeway, Muni Trivia
Here is a list of events this week. Monday/Tonight! SF Politics 101 with Joel Engardio. Learn how local politics shaped San Francisco. Monday/tonight, October 19, 5:30-6:45 p.m. SPUR Urban Center, 654 Mission Street, S.F. Wednesday 20th Street Protected Bikeway Ribbon Cutting. The Oakland Department of Transportation, city officials, Bike East Bay and other community partners will celebrate the completion of the 19th Street BART to Lake Merritt Urban Greenway. Wednesday, October 21, 1:30 p.m. 400 Thomas L Berkley Way, Oakland. Thursday 2026 Silver SPUR Awards. This SPUR event brings together elected officials and business, civic, and philanthropic leaders to celebrate four individuals and their contributions. Thursday, October 22, 4-7:30 p.m. Blue Shield of California Theater at YBCA, 700 Howard Street, S.F. Get tickets here. Friday Woman and Non-Binary Morning Ride. Join the San Francisco Bicycle Coalition for a socially distanced bike ride for women and nonbinary cyclists. Friday, October 23, 7:15-8:45 a.m. McLaren Lodge, 501 Stanyan Street, S.F. Friday Muni Trivia Night. Bring your friends or come solo and make some new ones. Friday, October 23, 7:30 p.m. Standard Deviant Brewing, Pier 70, suite 195, 1070 Maryland Street, S.F. RSVP here. Saturday Fifth Annual Firefighter Family Ride. Join SFFD, SF Safe Routes to School, and the SF Bicycle Coalition for a fun, low-stress bike ride through one of the city’s most beautiful routes. Saturday, October 24, 10:30 a.m.-1 p.m. Panhandle Park Blacktop (Fell & Ashbury) to JFK Promenade (Whale’s Tail). Sunday Canvas for No on Prop G. Join the San Francisco Bicycle Coalition to canvas for No on ‘G’ to save Sunset Dunes Park. Sunday, October 25, 10 a.m.-12 p.m. Marina Blvd & Laguna Street, S.F. Got an event we should know about? Drop us a line.
NQPI welcomes Professor Michael Held, strengthening connections between molecular biology and nanoscale materials research
The Nanoscale and Quantum Phenomena Institute (NQPI) at Ohio University welcomes Professor Michael Held as its newest faculty member.
Discovering the Science of Fall
By Lynn Michelsen, Crossroads at Big Creek -- The changing season makes October an ideal time to explore the outdoors and observe these natural phenomena firsthand.
Anakin Skywalker actor Jake Lloyd shares rare message to ‘Star Wars’ fans alongside fellow child star from prequels
Jake Lloyd, who starred as Anakin Skywalker in 1999’s ‘The Phantom Menace,’ shares rare message to ‘Star Wars’ fans alongside fellow child star from prequels, Daniel Logan.
Computational Models as Liminal Models in Neuroscience, a Cognitive Science Speaker Series Presentation | Events
Speaker: Danielle Williams, Ph.D. Title: Computational Models as Liminal Models in Neuroscience Short Bio: Danielle is a philosopher of mind and science whose research examines the role of computation in our theories and explanations of the mind and brain. Her work brings together philosophy of mind, cognitive science, neuroscience, and artificial intelligence, with particular interests in computational theories of mind, computational modeling, and the relationship between different explanatory and modeling strategies in the mind sciences. She also investigates philosophical questions raised by contemporary AI, including the nature of opacity in computational models and its implications for explanation in cognitive science. Alongside this work, she is a historian of cognitive science and AI, examining how the development of computer technology has shaped our conceptions and models of the mind and brain. Abstract: Scientists rely on various types of models to make sense of their phenomena of interest. This has led philosophers to take up a range of semantic, ontological, and epistemological questions about how models represent, what kinds of things models are, what we learn from models, and how they explain. One type of model that has been of particular interest to philosophers is the computational model. Computational models are commonplace in the mind sciences in general and neuroscience in particular, with many asking how computational modeling can help us understand the nervous system and its contribution to cognition and behavior. These questions are particularly pressing in neuroscience, as computational models have become a dominant framework for making sense of cognition. Thus, old questions about model-based science have re-emerged within the context of neuroscience, with many philosophers looking to established frameworks to understand how computational models represent, explain, and contribute to theory development in neuroscience. These established frameworks, however, characterize computational models as a homogeneous type which cannot capture actual modeling practices in neuroscience. In this talk, I argue that computational models in neuroscience are best typed as a kind of liminal model, a type I introduce to capture how the status of a computational model is determined by the epistemic context in which it is deployed. Indeed, the category to which a computational model belongs shifts according to the role it plays within a given context. ASL-English interpreters have been requested. Light refreshments will be provided.
Kaley Cuoco and Tom Pelphrey welcome second baby girl: ‘Welcome to our family youngest queen!’
The couple named their daughter Philomena Carmine Bobby Pelphrey.
Daldrop Opens for Business in Southern Oswego County
$10 Million Facility in the L. Michael Treadwell Oswego County Industrial Park marks the largest expansion outside of Germany in the company’s 73-year history By Stefan Yablonski [caption id=attachment_11076 align=alignright width=450] Daldrop SBB CEO Jens Daldrop addresses attendees at the 2025 groundbreaking for the project. Daldrop also chairs the advisory board of Germany-based Daldrop Group.[/caption] A new era of cleanroom technology is underway in Central New York. The Daldrop Group’s advanced manufacturing facility and U.S. headquarters is physically built within the L. Michael Treadwell Oswego County Industrial Park. This industrial park is located in the town of Schroeppel. It marks the largest expansion outside of Germany in the company’s 73-year history. Daldrop SBB is based in Neckartailfingen, Germany. It is a global supplier of cleanroom technology, primarily to the pharmaceutical industry. It designs and builds advanced cleanroom environments for the pharmaceutical, biotechnology and medical technology industries. It nvested $10 million in the new project. “We broke ground in 2025; we were under construction all winter. We just opened this spring, early spring,” said Benjamin Morrow, operations manager and control. The company consolidated sites in Salina and DeWitt into the industrial park in Schroeppel, Morrow added. “The next move here is to maximize every square inch of this facility and then we are already looking at the expansion. So, it is more capital investment on equipment — definitely higher-end automation in additional equipment so we can produce more components and then to support the ever-growing base in North America,” Morrow continued. “We are the headquarters for service, maintenance and spare parts. So as Daldrop has more and more installations, they need more and more service, maintenance and spare parts. So that will come out of this facility as well — it already is.” “As a global leader in GMP (global manufacturing support) pharmaceutical cleanrooms for decades, I am very proud to bring manufacturing jobs to Upstate New York,” said Mike Sullivan, president of Daldrop US operations. Key to choosing Southern Oswego County [caption id=attachment_11077 align=alignright width=450] Daldrop SBB at the L. Michael Treadwell Oswego County Industrial Park when the company announced the start of construction.[/caption] Sullivan said that the selection of the Schroeppel industrial park was mainly due to the help of Operation Oswego County and two people in the organization. “Prior to being purchased by Daldrop International from the Stuttgart region of Germany, Vince Bongio was a founding partner in SBB Inc. as well as our head of engineering. We based out of Syracuse due to Vince’s skills in HVAC and the manufacturing capabilities found in Syracuse,” said Sullivan. Bongio moved to Syracuse from California in the 1970s to work in Carrier’s Industrial Division of Large-Scale Petrochemical Refrigeration. Next, he advanced to General Electric’s TV Tube Plant where he got into cleanrooms ,leading to his role of head of engineering for Clestra Cleanrooms where he met Sullivan, their New England distributor. “Vince Bongio is a phenomenal engineer. Formerly of Carrier, he grew up in California and went to Cal Poly,” Sullivan explained. “Carrier hired him right out of college and he moved to Syracuse. He is the reason we are in Syracuse today. He is retiring this year. We are very proud and his legacy is having brought Daldrop to Syracuse.” In 2000, Sullivan, Bazinet, Bongio Inc (SBB) was formed with engineering and manufacturing, based in Syracuse, and sales and construction based in Massachusetts as it is today. “SBB Inc. started in Syracuse. I had a design–build contracting firm out of Massachusetts that was primarily doing all the new technologies coming out of MIT,” Sullivan said. “I started a manufacturing side. A big thing for cleanrooms is the HVAC. Most cleanroom suppliers are architecturally focused people. The strength in Syracuse is HVAC. So, SBB developed with me running sales and construction out of Massachusetts and manufacturing out of Syracuse.” “Daldrop wanted to have a relationship in the States and of those who approached us, they were the only ones who really understood HVAC. So, we were the right fit for them. We did a joint venture focused out of Massachusetts from 2012 to 2018 leveraging their technologies,” Sullivan explained. “The commitment was if we brought their product to the States, we would do that if they built it here. “The pieces that had to be in place to make the investment, they wanted to acquire us, we were great with that. If you looked at business recommendations the general guidance was to build in a low labor area — something like North Carolina — but Syracuse had a strong background in HVAC and we chose Syracuse and Oswego County to be our headquarters in the States. So, it is built off of history, technology and the existing supply chain — bringing jobs back to the area.” During the initial discussions with Daldrop about coming to the U.S., SBB agreed to sell under the conditions Daldrop would manufacture in the U.S. There are many areas that offer incentives and economic packages, but the strength of HVAC expertise and skilled manufacturing was a big part of the discussions for site selection. Coming home [caption id=attachment_11078 align=alignright width=451] Construction moves forward in March at the L. Michael Treadwell Oswego County Industrial Park.[/caption] The second key person to building in Oswego County is Ben Morrow, Sullivan added. “Ben has been working with Daldrop SBB for more than 12 years and has advanced to COO of manufacturing and engineering. Ben grew up in Phoenix, so building a factory for the Germany company in Phoenix is a strong success for both his community and the appreciation of Ben’s skills as a team leader,” Sullivan said. “I went to high school in Phoenix. So, this is like full circle for me. It’s a small world,” Morrow said. “I hadn’t been back to Phoenix since graduation. This is one of the properties that John Trimble of C&S, he is the former president of C&S, he just retired, suggested. He and I were very good personal friends. John was from Mexico and I was from Phoenix. We knew each other from high school. And the architect of this building, Ed Smart of smartDESIGN Architecture in Batavia — I went to high school with him. So, this was a project that’s full circle a coming home kind of thing. The three of us knew each other — kind of like it was meant to be. Very serendipitous.” Schroeppel was one option for Daldrop to consider; the original intent was just to get a warehouse to store some product, he added. The facility is Daldrop’s largest outside of their native country. Total payroll at the facility will be approximately $2.4 million once fully staffed. “Here is 32,000 square feet and we plan to expand and put in an additional 10,000 square feet,” Morrow said. “We have 17.5 acres. We can put at least three more facilities here, just on this property. The master plan submitted for the current building is the first of possible three buildings on the campus.” “If we can find the right people and advance the production according to the plan, we should be able to grow for the next decade. One of the first jobs we filled was our new HR manager, with a primary focus posting and filling new positions,” Sullivan said. Stop the exodus, start hiring [caption id=attachment_11080 align=alignright width=452] Principals at the local Daldrop SBB headquarters, from left: Ben Morrow, Mike Sullivan and Jens Daldrop.[/caption] “I have been coming to Syracuse for 30 years. One of the things I had a hard time watching was the exodus of factories. One of the toughest things is to watch it with my partners’ kids who had to move away for jobs. It is important for us to give opportunity where people’s kids don’t have to leave the area to get work,” Sullivan said. “My responsibility is to find people who have skill sets that want to work and then I have to build opportunity for that work to happen. “After years of watching companies and Vince’s three sons all move out of the areas to get jobs, it is important to us to provide opportunities for the Syracuse region and help grow our company. We have been hiring for our new factory and will continue for the next few years.” “We are hiring and will continue to hire. Currently we have about 19 on staff right now,” Morrow said. “We expect to grow that by about 10 to 15 in the next 12 to 18 months or so. We are at 19 currently — one in the wings. It’s been great being able to hire locally. All these folks that we’ve been hiring, they all live within a few miles from here.” “We hired someone this past week (end of August). She grew up in the area, raised a family and is working down in Florida. She just took a job with us so she can move back and be with her family. We will be moving her back and she should be starting in October. We are very happy to see this happen,” Sullivan said. “I feel strongly about having a spot for the kids to not have to move out of the area. It is better to have people moving into the area.” Currently, Daldrop SBB has openings for finance manager, COO of construction and delivery, as well as mechanical, electrical designers and Revit modelers, construction managers, commissioning agents and many other skills that are needed. Along with Daldrop’s reputation in life science cleanrooms, there is a strong history in semiconductor, electronics, glass, photonics, aerospace and other markets. This may be helpful with any new technologies building in the market such as the Micron expansion and the support network, Sullivan said. “We acquired this property and closed on it two months before any announcement from Micron. It is serendipitous that they’re right down the street from us,” Morrow added. “Everybody started thinking ‘you guys are supporting Micron.’ We were here first. That is not a goal of ours. We may or may not … they are talking to us; it is an opportunity.” The long run [caption id=attachment_11079 align=alignright width=450] Benjamin Morrow, operations manager and control at Daldlrop, speaks during a recent ribbon-cutting event in Schroeppel.[/caption] “Long term, we will expand the Phoenix facility,” Sullivan said. “We built our facility with a campus approach. Sustainability is big. We designed our rooms to be more sustainable. Our building has no gas lines for heat. We put geothermal wells in the ground. We put heat pumps in for heating and cooling out of those wells and we put a large layer of solar panels up on the roof. We worked with National Grid for metering. Our building is a high efficiency model. We upgraded all the instillation and the glass filtering. So, it is a very green building. We will have a very minimal carbon footprint. It also adheres to LEED (Leadership in Energy and Environmental Design) construction standards.” “We are a bunch of HVAC engineers. We did a large scale geothermal and spent the money up front because we knew it made sense in the business sense in the environmental sense and sustainability,” Morrow said. “We have insulated metal panels on walls and roof; we are an envelope from the exterior.” Daldrop, as a global player, has a strong culture of sustainability that is found in all its products including the new facility. The building has been designed with (sixteen) 400-foot deep geothermal wells, high efficiency construction methods, approximately 70 kilowatt solar photovoltaic panels, electric vehicle chargers and 26% recycled content. “Daldrop thinks of long-term investing,” Sullivan said. “On the roof, photovoltaic panels supplement our power. Over half the energy that I use is coming from the sun. We have chargers up front for employee electric vehicles. This place is built to last. This slab that we are walking on, normal buildings are four inches, some go to six inches, we are nine inches all the way through — except where the heavy equipment is — that is 10 to 12 inches thick, solid concrete. It allows us to reconfigure for whatever type of equipment we want to bring in,” Morrow said. “We are authorized by Underwriters Laboratory to self-certify so we don’t need to have an inspector come out and recertify. We get audited often, but we certify our own electronics. The control system in this building is rather high-end. Our thermostat in every room is zoned, independent. We analyze the data; incorporate it with our solar panels.” “There is a lot of competition for people to work. It’s not just about how much salary they are going to make — it’s about the work environment, the ability for stability. We want to make sure our employees have the best environment to work in,” Morrow added. Similarities “One of the reasons I believe why Daldrop chose this area, Phoenix in particular, is because it is a village, a river-based village. Neckartailfingen in Germany where Daldrop is based is also a river-based village, manufacturing community. So, there is a lot of similarities — that smalltown feel,” Morrow said. “We have a lot of connections through multiple employees that lead back to Carrier, also. Everything came together, the timing everything.” “We are thankful for all the economic development support. Everyone has been helping make this happen. So, keep it up, it is working, that is all I got to say, Sullivan said. “If you look at historical industrial manufacturing, this region has skills that have been un-utilized. The northern industrial region has a lot of skills that if we can tap before they go away, we can leverage them. That is what we are trying to do. You’d be surprised at the supply chain left behind from Carrier — that supply chain is still there.” “Operation Oswego County has been fantastic,” Morrow added. “I can’t say enough good things about that group.” What Is Cleanroom Technology Cleanroom technology is a system of specialized engineering, filtration and operational controls used to maintain an extremely low concentration of airborne particles, microbes and chemical vapors. How It Works • Air Filtration: Uses HEPA or ULPA filters to remove 99.97% of tiny particles down to 0.3 microns. • Airflow Control: Directs air in a steady, unidirectional (laminar) or filtered turbulent pattern to push dust away from work areas. • Environmental Regulation: Maintains precise control over temperature, humidity and positive air pressure to block outside air leaks. • Specialized Attire: Requires personnel to wear full-body garments (“bunny suits”), gloves and masks to stop human shedding
'Aladdin' star Mena Massoud teases 'Daniel' sequel after box office success
Mena Massoud is hopeful audiences haven t seen the last of the biblical prophet Daniel on the big screen, as the 35-year-old actor and producer says the success of Daniel The Fiery Furnace has opened
Dennis The Menace
Click here to view this article from TheDerrick.com.
*POSTPONED* Behind the Science with Paleontologist and Curator of Dinosauria Dr. Matthew Carrano
***Due to speaker illness, this event has been postponed. A new date will be announced in two weeks. If you registered for this program, please check your email for more information. We apologize for the inconvenience.*** Is the 21st Century the real Age of Dinosaurs? Today, more paleontologists are discovering more dinosaur fossils from more places in the world than ever before. Our understanding of these amazing creatures has leapt forward while their popularity has surged. Museums sit at the junction of these phenomena. The Smithsonian has been a center for dinosaur research for more than a century, and its collections include many iconic and scientifically important specimens. Today, Smithsonian researchers continue to discover new dinosaurs, but they are also uncovering more information about the ones we already know and love. New techniques and approaches allow them to investigate aspects of dinosaur biology, ecology, and evolution in ways that would have been inconceivable to early paleontologists. The result is an ever-improving understanding of dinosaurs as living, breathing, and thriving animals. This month, go behind the science with paleontologist Dr. Matthew Carrano, Curator of Dinosauria at the National Museum of Natural History as he discusses new discoveries at home and abroad, in the field and in the museum. Registration is encouraged. Space is filled on a first come first served basis. ---------------- About the Series: Behind the Science A monthly after-hours series featuring NMNH scientists and researchers Each month, join the National Museum of Natural History for the new series, Behind the Science, where NMNH researchers share insights into their latest discoveries and explore the fascinating questions driving their work—from the origins of life to the future of our planet. Come learn what’s happening behind the scenes and how science shapes our understanding of the natural world. Programs take place in Q?rius, the Coralyn W. Whitney Science Education Center. Topics and speakers announced on a rolling basis, but save the dates now!
Soule favored to start alongside Dybala and Malen vs Real
Gian Piero Gasperini won’t limit the quality of his players out of fear of Real Madrid. Los Blancos have a team of phenomenal players, but the Giallorossi coach has no intention of focusing solely o...
Voters are connecting the dots — and it’s bad news for Republicans
Of all the dynamics threatening the GOP this year, the most menacing may be the connection voters are drawing between their economic frustrations and GOP policies.
The Midterm Elections Won't Keep Trump From College Football on Saturday. A Hurricane Might
WASHINGTON (AP) — The midterm elections are looming and the first hurricane of the Atlantic Season is menacing the Gulf Coast. But President Donald Trump is really, really hoping the weather doesn’t stop him from going to another big college football game — this one in Alabama on Saturday night.
URI astrophysics student earns coveted Association for Computing Machinery’s SIGHPC fellowship
KINGSTON, R.I. – Oct. 6, 2026 – Ever since she was young, Genevieve Payne has always had a deep interest in nature and understanding hidden systems and patterns within it, hoping to one day study some of the universe’s most extreme and least-understood phenomena. This interest developed into a focus on gravitational wave and high-energy […]
WHO sounds alarm on critical funding gap for health response in Yemen
Dr Syed Jaffar Hussain greets children outside their family tent at Al-Firdous camp. Photo credits: WHO YemenAden, Yemen — 6 October 2026: As the conflict in Yemen escalates and needs continue to grow, the World...
Todd Promenade returns on Saturday, Nov. 7
TODD — The Todd CommUnity Dance organizers are pleased to announce the second Todd Promenade event, featuring an afternoon of square dance calling, flatfoot dance, and playing music for dances
Inside the Trump administration’s UFO hunt
In 2022, the Pentagon took part in the first congressional hearing in more than a half-century to focus on military reports of unexplained phenomena.
Rajasthan Royals star creates history, surpasses Chris Gayle for highest T20 score
Lhuan-dre Pretorius has made T20 cricket history with his phenomenal score of 188 runs off 79 balls while playing for the Titans against the Knights. This feat breaks Chris Gayle's former record of 175 runs, showcasing Pretorius's exceptional talent as he maintained a striking rate of 237.97. His recent century for South Africa further underscores his remarkable consistency and prowess on the field.
Radial Entertainment Launches 'Paranormal Chronicles' FAST Channel
Radial Entertainment Oct. 1 launched Paranormal Chronicles, a premium FAST channel programmed for fans of paranormal investigations, documented hauntings, unexplained phenomena and mystery-driven true crime. Debuting in time for the Halloween viewing window, the channel is available for free on Google TV Freeplay, LG Channels, Plex, The Roku Channel, Dish TV, Bonusview and Sling Freestream … Continue reading "Radial Entertainment Launches ‘Paranormal Chronicles’ FAST Channel"
King County Public Health investigating cryptosporidiosis outbreak at McMenamins’ Bothell pool
The parasitic outbreak ties back to someone swimming in McMenamins' Anderson School pool, according to King County Public Health.
Small Signals, Big Effects: Why Symbolic Policies Matter for Climate Politics -
In the APSA Public Scholarship Program, graduate students in political science produce summaries of new research in the American Political Science Review. This piece, written by Ximena Caló, covers the new article by Theodore Tallent, [...]
Small Signals, Big Effects: Why Symbolic Policies Matter for Climate Politics -
In the APSA Public Scholarship Program, graduate students in political science produce summaries of new research in the American Political Science Review. This piece, written by Ximena Caló, covers the new article by Theodore Tallent, [...]
Chicago Bears Midweek Musings: Phenomenal
Check out @gridironborn’s midweek musings, including thoughts on Case Keenum, Bears defense, Ben Johnson and more.
Marine veteran’s coffee business gives back to those who served
Operation Coffee, based in Menasha, donates to veteran charities
Marine veteran's coffee business gives back to those who served
Operation Coffee, based in Menasha, donates to veteran charities
CPS cited mother’s mental health as 'safety factor' before Mechanicville killings
WRGB CBS 6 provides local news, weather forecasts, traffic updates, notices of events and items of interest in the community, sports and entertainment programming for Albany, New York and nearby towns and communities in the Capital City area, including Cohoes, Watervliet, Colonie, Bethlehem, Guilderland, New Scotland, Coeymans, Green Island, Knox, Berne, Westerlo, Rensselaerville, Colonie, Menands, Green Island, Ravena, Altamont, Voorheesville.
Behind the Science with Paleontologist and Curator of Dinosauria Dr. Matthew Carrano
Is the 21st Century the real Age of Dinosaurs? Today, more paleontologists are discovering more dinosaur fossils from more places in the world than ever before. Our understanding of these amazing creatures has leapt forward while their popularity has surged. Museums sit at the junction of these phenomena. The Smithsonian has been a center for dinosaur research for more than a century, and its collections include many iconic and scientifically important specimens. Today, Smithsonian researchers continue to discover new dinosaurs, but they are also uncovering more information about the ones we already know and love. New techniques and approaches allow them to investigate aspects of dinosaur biology, ecology, and evolution in ways that would have been inconceivable to early paleontologists. The result is an ever-improving understanding of dinosaurs as living, breathing, and thriving animals. This month, go behind the science with paleontologist Dr. Matthew Carrano, Curator of Dinosauria at the National Museum of Natural History as he discusses new discoveries at home and abroad, in the field and in the museum. Registration is encouraged. Space is filled on a first come first served basis. ---------------- About the Series: Behind the Science A monthly after-hours series featuring NMNH scientists and researchers Each month, join the National Museum of Natural History for the new series, Behind the Science, where NMNH researchers share insights into their latest discoveries and explore the fascinating questions driving their work—from the origins of life to the future of our planet. Come learn what’s happening behind the scenes and how science shapes our understanding of the natural world. Programs take place in Q?rius, the Coralyn W. Whitney Science Education Center. Topics and speakers announced on a rolling basis, but save the dates now!
At an angry time, the business of rage retreats is booming
Kristina McMenamin’s rage retreats started small. The events, called RAGEher, were 12-person affairs in Chicago. The attendees, all women, opened their arms wide in a vacant retail space McMenamin had
Second-half strikes give Ballymena win over Ports
Second-half strikes from Finley Thorndike and Igor Rutkowski give Ballymena a 2-0 win over Portadown.
All-clown ‘Godspell’ with comedy stars? ‘You Had to Be There’
The 1972 Toronto engagement of Broadway’s phenomenally popular hippie musical “Godspell” is an unlikely subject for a contemporary documentary. Especially when there is no video.
JPMorgan's Neukirchen on India Payments Business
Max Neukirchen, Global Co-Head of Payments at JPMorgan, discusses the business opportunities in India's merchant payments sector. He speaks with Menaka Doshi at the sidelines of the JPMorgan India Conference in Mumbai.
Trump used to slam China. Here's why he's now rolling out the red carpet for Xi
When Donald Trump ran for office a decade ago, he called China a menace to the U.S. economy
Trump used to slam China. Here’s why he’s now rolling out the red carpet for Xi
When Donald Trump ran for office a decade ago, he called China a menace to the U.S. economy.
RBS women draw at LASK
Goalless away draw LASK 0-0 FC Red Bull Salzburg WomenAfter a recent slump in results in the ADMIRAL Women's Bundesliga, our team got back to picking up points, playing out a goalless draw against LA...
Sorkin says 'The Social Reckoning' was not not an easy green light
During an appearance on "The Interview" podcast, Director Aaron Sorkin called Meta "phenomenally powerful company with limitless resources."
'A Talent for Murder' review: Alden Ehrenreich gives sexy menace in this Patricia Highsmith-inspired thriller
All hail Helen Mirren, who is perfectly cast as an iconically vicious dame.
Liverpool make contact to sign phenomenal German super talent
Liverpool have made contact to sign an incredibly talented German player. When Jurgen Klopp took over a decade ago, there was this perception that he was going to bring in a lot of German players.Klop...
High-resolution dataset tracks health impacts of urban heat stress
Heat stress is a leading cause of weather-related deaths and can be especially dangerous in cities where phenomena like urban heat islands drive temperatures higher than surrounding rural areas.
Wow, attacker confirms Liverpool have signed a sensational player
Liverpool have signed a phenomenal attacker, he just confirmed it. It's been a roller coaster of the transfer window throughout the summer. Looking back on it, two weeks later most supporters will be ...
What Does the Science of Climate Change Really Look Like?
Editor’s Note: This is the second in a three-part series on how the Right should think about environmental and climate policy. Read Chris Barnard on Reclaiming Environmental Policy from the Left. More than a decade ago, the world’s governments negotiated and signed the Paris Climate Agreement, committing to hold global warming well below 2 degrees Celsius. In the following years, climate had immense cultural power. Greta Thunberg emerged. Fortune 500 companies established net-zero plans. The U.S. got the Inflation Reduction Act. Then the pendulum swung back. President Donald Trump returned to the Oval Office, speaking of green energy as a “scam” and carbon footprints as a “hoax” and on all matters of international policy emphasizing bilateral engagement and power over globalism and cooperation. The technology companies that had been at the forefront of net-zero pledges and green leadership discovered the importance of all-of-the-above power to their visions for artificial intelligence and began quietly postponing or removing their targets. On the left side of the political spectrum, rising concerns about inflation and cost pushed climate lower down in the stated priorities of voters and stump speeches of politicians. The moment is ripe for a reset on the politics of climate change and for conservatives especially to chart a course that acknowledges and addresses the real challenges in plausible ways. So what should we think about climate change as we enter a post-peak climate era? If it is neither an apocalypse nor a hoax, what will hold up as a durable view of climate change? And how does it project onto the concerns and priorities of the right-of-center’s emerging coalition? New to Commonplace_? Subscribe below to get the magazine in your inbox._ Subscribe A Solid Foundation As the politics and economics of climate careened over the past ten years, the physics carried on regardless. In 2015, the year the Paris Climate Agreement was adopted, the world emitted 41.2 gigatonnes of carbon dioxide. By 2025, emissions had risen only 2.4%, to 42.2 gigatonnes, because falling emissions from land use offset increasing emissions from fossil fuels. But slow growth in annual emissions is not rapid decline, let alone net-zero, so carbon dioxide kept accumulating in the atmosphere, going from 399 to 426 parts per million. Global temperature kept rising too, from about 1.1 degrees Celsius above the 1850–1900 average in 2015, to 1.4 degrees above it in 2025. None of this should surprise anyone. Even most prominent skeptics, like the authors of the 2025 report commissioned by the Trump administration’s Department of Energy, accept the basic physics. Carbon dioxide added to the atmosphere at industrial volumes accumulates and traps heat that would otherwise escape to space. That heat warms the upper ocean and increases temperatures at the surface. Increased ocean heat and melting of land ice cause sea levels to rise. Changes in the climate become noticeable to us as subtle shifts in temperature and precipitation, seasons arriving early or late, changes in the surrounding ecosystem, and weather extremes. The much more meaningful debate is not about whether these things are happening, but about what it all means for human societies. (While it is a proxy measure of overall risk, no one experiences global surface temperature.) This debate invokes at least three interesting questions: how much today’s warming is showing up in regional climate trends, how much more warming we should anticipate, and how extreme weather events can be understood in the context of climate change. Recent scientific advances give us new insights into each of these, but there is still much to learn. This is the context in which the next generation of conservative leaders will be the first to deal with significant climate change as a fact, not a forecast. It will be with them for their entire careers. Our evolving scientific picture of climate change will come from weather and climate records stretching further into the past, new kinds of observations in the present, better modeling tools for the future, and simply more time to observe the emergence of climate signals and their tangible effects on ecosystems and communities in the United States and around the world. The policy landscape will be shaped by not only the impacts of changes in the climate, but also by the ways in which societies respond and by the emergence of new technologies for both altering the trajectory of emissions and adapting to new climate realities. Global climate records now show the fingerprints of warming in different phenomena around much of the world. The IPCC, in its most recent assessment report, documents warming trends over all land regions, even as natural variability adds substantial variance to local trends. And the highest temperature extremes have become more intense and frequent, almost everywhere, since the 1950s. Scientists are highly confident that these changes are attributable to human influence. But confidence in detecting trends and attributing them to human influence degrades across heavy precipitation events; drought trends are heterogeneous and not attributable to human activity with great confidence. For hurricanes, tornadoes, and other severe storms there is even less confidence in trends or their relationship to climate change. In general, a fair summary of the evidence is that for well-observed phenomena, like surface temperature or heavy rainfall, with a clear relationship to warming, our multidecadal observations are consistent with human influence overcoming natural variability over long time periods and extremes increasing. For regions that are sampled more sparsely, or phenomena with a higher noise-to-signal ratio, we will need to observe them longer to understand the magnitude of the climate signal or improve dynamical understanding using models and observations together. But for Climate For those who can’t wait, we also have new techniques that attempt to understand the role climate change has in influencing particular extreme events. When the climate is changing and disaster strikes, it is natural to ask whether that disaster was somehow “caused” by climate change. For scientists and policymakers acting in good faith, answering that question helps develop a more accurate picture of the problem, how it may be getting worse, and what preparations we should be making to respond to it. It may, at some point, give some weight to how liability is assigned by courts or adaptation funding is distributed by society. But how we ask this question is extremely important. It is easy to get the analysis wrong by discounting the role that meteorology plays. As meteorologist Theodore Shepherd explained in a clear 2016 review of climate attribution methods, “if a weather or climate event is truly extreme in the present climate, then perforce it requires unusual meteorological conditions, which means that climate change is at most a contributing factor.” Share Scientists have two ways to probe climate as a contributing factor, both of which have entered media coverage of extreme weather events. One asks a probabilistic question: How much more likely is a particular event (e.g., a temperature record over a particular area) amid global warming? The answer involves using historical records and computer simulations to estimate the likelihood of such an event in both a changed and a preindustrial climate. The findings are less about the specific event, and more about events of that nature. The other question is: How has the changed climate affected the specific event in question? Here, scientists try to understand what a similar event would have looked like in the preindustrial climate. This is sometimes called the storyline approach, where the story is the specific meteorological details of the event. These methods offer ways to test the intuition of scientists about real weather extremes. In late June and early July of 2021, a persistent high-pressure ridge, or heat dome, set up over the Pacific Northwest and an extraordinary heat wave affected the area from Oregon to British Columbia. For six days, it shattered temperature records across the region and hundreds died from heat-related causes, in an area where such high, and persistently high, temperatures were well outside of experience and many live without air conditioning. Scientists have studied its connection to climate change using multiple approaches. This specific event was created by a rare combination of meteorological factors, a strong high-pressure ridge created the conditions for extreme heat, which occurred on top of higher average temperatures in the region from global warming. Probabilistic analyses showed that climate change increased the likelihood of such an event by at least 8-fold to more than 100-fold. One standout example found that such an event had effectively zero probability of occurring in the preindustrial climate. The enormous range in these assessments reflects how hard it is to estimate probabilities of events at the tail of the historical record. Estimates of the effect on the temperature of the event are more clustered. A recent review paper documents how multiple methodologies have found a positive influence, roughly 1-2 degrees Celsius of an anomaly that exceeded 15 degrees, of climate change on the temperature magnitude of the event. Multiple studies have investigated and found some positive influence of climate change in other extreme events. Attribution studies found climate likely increased the heavy rainfall that accompanied Hurricane Helene in North Carolina and surrounding regions in 2024. The extensive fires that struck Los Angeles in 2025 illustrate how the causal chain can become messy, though. Studies do detect a positive influence of climate on the event’s likelihood, but while climate change likely contributed to underlying aridity, it would not have played a role in the heavy winds or land practices that preceded disaster. These event attribution studies will become more common for extreme, or damaging, weather events. They can be produced quickly, and often are reported before peer review. As the Pacific Northwest heatwave example shows, when multiple methods converge on a positive attribution, the finding should probably carry some weight even if you have to be careful about accepting the results from a single study. I expect that as climate change proceeds and the climate thus departs further from a preindustrial counterfactual, the influence will become more detectable across a variety of extreme events and more easily identified. This will be used to cast blame, but can also be used to inform how communities and society adapt to ongoing change. We May Still Be Surprised One positive development, insofar as less climate change is better, has been that our central estimates for future climate change should probably be revised downward. Mostly, that is because the high-end warmings that scientists regularly analyzed about ten to 20 years ago, driven by high emissions throughout the twenty-first century, now appear to be somewhere between unlikely and impossible. At one time, the upper end of mainstream climate projections extended well into 4 to 6 degrees Celsius of warming by the end of this century, which, models suggest, would have wrought enormous real-world damage. Current energy and policy trends now point toward 2.5 or 3 degrees. Damages and risks are commonly modeled as increasing steeply with more warming, so this is already a better-than-previously-expected outcome for the climate (which is independent of the physical response to emissions). But we should maintain a wide range for plausible outcomes and prepare for the possibility of being surprised. Emissions trajectories are subject to deep uncertainty, the physical climate response is still developing, and whatever change occurs in the climate will then be mediated through unpredictable economic, social, and political institutions. Over the past decade, the pace of warming surprised some keen observers and appeared to accelerate, though not yet outside the range of expectation provided by climate models. The reasons for that apparent acceleration are being actively studied (as was the apparent pause in warming from 1998 to 2012), but no single driver has emerged. Some blame it on the El Niño, variability which would have no bearing on climate. Some think it is a result of factories in East Asia and global shipping fleets cutting aerosol emissions, which in the strongest version of the argument would indicate higher climate sensitivity to carbon-dioxide emissions. Others are more measured, not yet ready to draw solid conclusions as to whether climate projections require revision. We will have to see. Long-Term Thinking Climate change asks us to think over long time scales. But the pace of human-driven warming is compressing a large global change into a century. Changing weather patterns and extreme events are already causing adjustment costs and damages and will do more. Adaptation will help, but it is not free. For some communities, these costs will erode livelihoods and well-being, and may force migration. Are we prepared for large-scale managed retreats in the United States? Thankfully, American wealth, geographical diversity, and moderate climates may leave us better prepared than many around the world. But wealthy countries can still suffer serious disruption from narrowly concentrated costs, even if they appear entirely manageable in aggregate. Readers of Commonplace are familiar with the challenges of rapidly adapting to economic forces. The displacement that came from the China Shock is barely perceptible in aggregate GDP and employment data, but it affected millions of people and those people were far less mobile than economic models tended to assume. Deindustrialization rippled through the nation with enormous effects for not only our economic vitality, but also our national security. The forces surrounding climate change may not be so different; the world gets richer and must accept some diffuse costs. Those may be modest overall, but cause all manner of unpredictable effects with which policymakers must cope. In the case of the China Shock, our faith in a growing pie served us poorly. We’ll need to do better on climate. Leave a comment