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China, Russia Deepen Arctic Ties as Japan, Iceland Boost Science Cooperation
Russia floats a rival Arctic framework while Japan and Iceland, marking 70 years of diplomatic ties, lean on polar research to deepen cooperation.
A Bizarre Plastic-Eating Enzyme Has a Second Talent That Worries Scientists
Plastic can fool nature’s cleanup crew, but one bacterial enzyme knows exactly where to bite.
The humble one-celled alga that helped scientists win the Nobel prize
Chlamydomonas and its light-sensing protein help show how memories, feelings and behaviour form in our brains
America's butterflies fell 22%, and scientists say it's an early warning sign
"[Be] really cognizant of what chemicals and materials you are using outdoors and indoors."
A 1960 Science Paper Set Doomsday for Friday, Nov. 13, 2026, and Its Population Math Held Up for Three Decades
A 1960 Science paper predicted doomsday on Nov. 13, 2026. There is no threat, but its population equation beat most forecasts until about 1993.
Science Hill advances as four local teams fall in state volleyball tournament
Five local teams began their bids for state volleyball titles Tuesday in Murfreesboro, with Science Hill earning a five-set win to advance to the Class 3-A semi
Ukrainian science part of European security architecture
Ukrainian scientists are already contributing to the development of a new security architecture, including by helping build a drone ecosystem. — Ukrinform.
Zero Republican political science professors found at 4 major Pennsylvania universities, research finds
ANALYSIS: Democrat professors outnumber Republican colleagues 28 to 1 in Pennsylvania political science departments Professors registered as Democrats outnumber colleagues registered as Republicans by…
This History/Science Quiz Is So Simple That There's No Reason You Shouldn't Pass
Test your knowledge of science and history!
Extratropical Cyclone Whips Past Iceland
The powerful low-pressure system formed over the North Atlantic out of the remnants of Hurricane Isaias.
Exploring tactile senses with the Orlando Science Center
Watch to see if meteorologist Victoria Wisniewski can guess what is in these stereognostic boxes
Student-produced film captures Ireland sports experience | UNC Hussman School of Journalism and Media
The documentary created by a UNC Hussman School of Journalism and Media team premieres on campus Oct. 22 and Oct. 23. — This story, written by UNC Hussman alumnus Michael Lananna ’14, was originally published at unc.edu. — Carolina senior Anna Laible came up with the idea about a year ago. At the annual UNC Sports and Entertainment Summit, the journalism student walked up to then-athletic director Bubba Cunningham and took a chance. “Hi, Bubba, I’m not sure if you remember me, but I’m part of the student broadcast team from the Olympics,” Laible told him. “I have this idea to do an Ireland documentary on the football team.” Encouraged by the enthusiastic response to the proposal, Laible and a team of students from the UNC Hussman School of Journalism and Media worked diligently to turn that vision into reality. In August, Laible and seven peers traveled to Dublin, Ireland, with the Carolina football team and women’s soccer team. Equipped with video cameras, the student journalists covered both teams during their international games — both wins — and filmed scenes throughout Dublin, interviewing Irish locals, Tar Heel fans and key Carolina figures who helped make the trip possible. Back home, Laible’s team put the finishing touches on the documentary, with its first screening at 6:30 p.m. Oct. 22-23 in Carroll Hall room 111. The project is the latest in a long line of sports documentaries produced under the guidance of C.A. Tuggle, John H. Stembler Jr. Distinguished Professor. Since the 2008 Beijing Olympics, Tuggle and the Hussman school have sent journalism students to cover each of the Summer Games, and Tuggle’s students have also produced documentaries on Carolina teams that win national championships. But this Ireland excursion presented a new kind of opportunity. “This trip is really unique,” Tuggle said. “Bubba liked the idea, so we started working on it, and it’s all because Anna was forward-thinking and assertive.” Laible’s team worked to create a holistic depiction of the Dublin trip, billed as “Much More Than a Game.” The documentary’s 12 chapters cover Irish culture, music, trips to the Guiness Storehouse and the myriad connections between Tar Heels and Ireland. “Our main focus was to make sure we gave a whole encompassing idea of what this experience was like,” Laible said. “We wanted to show not just the student-athletes, but other students, other Carolina fans, Carolina alumni, the music and really incorporate that all in the documentary.” Joining Laible in Dublin were juniors Emily Brietz, Cooper Hall, Eliza Jennings and Katherine McCullough and seniors Molly Malek, May Proctor and Merrily Tew. Those students also traveled to Milan for the 2026 Olympic Winter Games in February. Those kinds of opportunities wouldn’t be possible without the support of UNC Hussman and, in the case of the Ireland trip, the Carolina athletic department. UNC Hussman students create Ireland trip documentary. (Submitted photo) “Never in a million years did I think I would have the opportunity to go to the Olympics or to the Aer Lingus College Football Classic, and now I’m even being presented with potential opportunities go to the Super Bowl,” said Malek, who served in a leadership role with Laible in Dublin. “I think that Carolina does a terrific job of connecting us to these opportunities that almost no other university does. This is a university where you have the opportunity to have an interdisciplinary education and to learn and experience a lot of things all at once.” With the support of UNC Hussman, Tuggle and fellow students like Malek, Laible turned a spur-of-the-moment idea into a documentary. When the film screens, Laible said she’s not quite sure what emotions to expect. “I’m a little worried that I might cry — not that crying is a bad thing,” Laible said, laughing. “But I’m really grateful for so many people helping, and I’m excited for everyone to see it.”
UAB opens Shelby Biosciences Research Building to advance health
UAB has opened the Shelby Biosciences Research Building, an eight-story facility named after former U.S. Sen. Richard Shelby, aimed at supporting health research and creating new jobs.
Lombardo check rejected as evidence during Fiore hearing
A Nevada judicial discipline panel rejected Gov. Joe Lombardo’s $5,000 check as evidence in proceedings against suspended Pahrump Justice of the Peace Michele Fiore.
Moment of Science: New electric current test measures coffee quality without tasting
Getting a clue about the perfect brew! Here's how new research could make sure your morning pick-me-up is "not your average Joe". ☕
25% Of Middle Schoolers Proficient In ELA, Science; 18% In Math
According to a recent presentation by district leaders, who described those numbers as “steady progress” and a small improvement from previous years.
Scientists Just Discovered That Earth’s Core Is Leaking, and It Has Been for Billions of Years
A new study suggests ancient hydrogen trapped deep inside Earth has been slowly escaping into the mantle for billions of years.
Union Colony Prep vs. Aurora Science & Tech: Colorado High School Girls Volleyball, Oct. 21, 2026
Union Colony Prep at Aurora Science & Tech, Colorado high school girls volleyball, Oct. 21, 2026, 4:30 PM. Records, rankings, rosters and head-to-head.
How to teach graph skills in science lessons
Translate graph skills into a science context with these teacher-tested tips
New Richland Lab Could Transform How Scientists Study Microbes and Boost Regional Jobs
The BriefGroundbreaking held Tuesday: PNNL officially began construction on the M2PC lab, a 30,800-square-foot facility funded by the U.S. Department of Energy's Office of Science that will study soil microbes to improve crop productivity and develop new biotechnology applications. The facility will be open to researchers from around the nation and the world.Research timelines could shrink dramatically: The facility's automation and AI capabilities could reduce experiments that currently take six months to just 72 hours, allowing scientists to explore more possibilities faster than ever before.New jobs coming to the Tri-Cities: The project is expected to create positions for automation engineers, AI experts, roboticists, technicians, and skilled craftspeople, with the facility opening in 2029.RICHLAND, Wash. — Pacific Northwest National Laboratory broke ground Tuesday on a first-of-its-kind facility that could accelerate scientific discoveries about the microscopic organisms living in soil—organisms that may hold the key to growing more food and developing new energy technologies.The Microbial Molecular Phenotyping Capability, or M2PC, represents a significant investment in automation and artificial intelligence to speed up research that traditionally takes years to complete. The 30,800-square-foot facility will house more than 100 connected automated instruments designed to study microbes at a pace and scale never before possible.Reshaping Agriculture's FutureThe M2PC facility will not put a new tool directly into a farmer's hands tomorrow morning, but it is actively reshaping the commercial pipeline to solve agriculture's biggest headache with biologicals: inconsistent field performance. For years, PNNL researchers have explored how microbes work and how they might help produce useful materials, advance energy technologies, and address challenges involving critical materials and minerals. But those experiments have been limited by what researchers could accomplish by hand."They can be used to provide nutrients to a plant so that the plant would grow more. So, like increasing your crop productivity, for example," said Douglas Mans, PNNL's Associate Laboratory Director for Integrated Discovery Sciences.PNNL's own research shows soil microbes can help plants access nutrients and withstand drought—benefits that could prove crucial as farmers face growing environmental pressures. The M2PC facility will allow scientists to identify and optimize useful microbes faster than ever before, accelerating the development of biological solutions that actually work consistently in the field.What Makes M2PC UniqueThe Microbial Molecular Phenotyping Capability differs from traditional research labs because it operates as a first-of-its-kind, AI-enabled autonomous laboratory designed to shrink experimental timelines from years down to months or weeks. The M2PC lab will connect more than 100 automated instruments to grow microbes, prepare samples, measure their behavior, and link observations to the molecular processes behind them. Artificial intelligence will help analyze results and guide the next experiments, allowing scientists to explore more questions faster.Deb Gracio, PNNL Director, emphasized the transformative potential during Tuesday's groundbreaking ceremony: "Research that has taken years will become possible in months and hopefully in weeks."That acceleration is already being demonstrated. PNNL's smaller automated lab, called the Anaerobic Microbial Phenotyping Platform or AMP2, completed three experimental cycles in just 72 hours—a process that normally would have taken about six months."That normally would have taken us about six months … and we were able to do that in 72 hours," Mans said.The AMP2 laboratory is not being closed or replaced. Instead, the current 1,800-square-foot laboratory serves as an active prototype and precursor for the much larger M2PC facility. AMP2 will continue operating as a separate lab designed to run anaerobic experiments—those conducted in the absence of oxygen—while M2PC will focus on aerobic research.Broader Applications Beyond AgricultureWhile improving crop productivity is one important application, the M2PC facility is designed to support research into multiple areas critical to national priorities. The lab will advance research into biofuels, manufacturing materials, and energy technologies. It will also help researchers understand how microbes respond to environmental changes and how to design biological systems for biotechnology applications.As a flagship component of the Department of Energy's Genesis Mission, M2PC represents a significant investment in using artificial intelligence and automation to accelerate U.S. scientific discovery. Dorothy Koch, Associate Director of the DOE Office of Science Biological and Environmental Research program, highlighted the facility's importance during the groundbreaking."M2PC will accelerate biological discovery and design," Koch said, noting that the facility is expected to conduct a minimum of 500 strain experiments per week, 100 microbiome experiments per week, and take a million measurements per month.Economic Opportunity for the RegionBeyond the scientific breakthroughs, the M2PC project represents significant economic opportunity for the Tri-Cities region. The facility will require hiring automation engineers, AI experts, technicians skilled in operating robotics, and specialized craftspeople to build and maintain the sophisticated equipment."We're anticipating that type of hiring," Mans said when asked about job creation.PNNL has already begun recruiting talent nationally and internationally for positions related to the smaller AMP2 lab, bringing automation engineers from cities like Boston and San Francisco to work in the region. The M2PC facility is expected to accelerate that trend."This capability won't really exist anywhere else in the world," Mans said, suggesting the facility could become a draw for scientific talent seeking to work on cutting-edge biotechnology research.Timeline and Next StepsThe M2PC facility is expected to open in 2029. Between now and then, construction crews will level and prepare the ground, while the building takes shape. Simultaneously, Ginkgo Bio Works, the automation contractor, will build the facility's automation components off-site so they can be installed as the building is completed.In the interim, PNNL researchers and the broader scientific community will begin planning the first experiments to be conducted in the facility, ensuring research is lined up and ready to begin as soon as the doors open.The groundbreaking ceremony included representatives from the Department of Energy, PNNL leadership, and elected officials at the federal, state, and local levels, underscoring the project's significance to the region and the nation's biotechnology future. News The U.S. Department of Energy Secretary tours Pacific Northwest National Laboratory Dan Hanson, Apple Valley News Now News Beyond DNA: Scientists Explore New Frontiers in Biology Research Dan Hanson, Apple Valley News Now News TRIDEC optimistic that Hanford, PNNL will see funding in national budget Robert Desaulniers News Big picture science: monitoring the Yakima River Basin News PNNL research could shape the future of fighting fentanyl COPYRIGHT 2026 BY APPLE VALLEY NEWS NOW. ALL RIGHTS RESERVED. THIS MATERIAL MAY NOT BE PUBLISHED, BROADCAST, REWRITTEN OR REDISTRIBUTED.
Scientists Use Ancient Rains to Map the Possible Origin Life on Mars
Billions of years ago, rain may have helped shape where the chemistry of life could begin on Mars. A new study maps how formaldehyde, an important prebiotic molecule, may have reached the surface. This map could help guide future missions searching for signs of past life on Mars.
Germophobe Primates Want to Avoid Getting Sick, Too
Some monkeys become significantly more cautious about food sources that appear contaminated after experiencing deadly outbreaks of disease.
Monkeys also avoid germs after viral outbreaks
Macaques who survived the spread of a deadly disease were more wary of potentially contaminated food.
Google.org awards $36m to 17 AI science teams | ETIH EdTech News
ETIH edtech news covers Google.org's $36 million commitment to 17 AI for Science projects, including research at the University of Cambridge and MIT. The selected organizations will advance work across climate, clean energy and healthcare, with optional access to Google's six-month accelerator.
Rule breaking by just a few people can be contagious
People are more likely to mimic — or even surpass — rule breakers than rule followers, a study finds. But real-world consequences may keep people in line.
Roman sarcophagus inside Westminster Abbey originally held a different body
A case of coffin swapping may explain the mysterious medieval burial.
Museum of Science and Industry Begins South Portico Renovation as North Entrance Plans Draw Scrutiny
The Griffin Museum of Science and Industry (MSI) on October 13 broke ground on a $22 million renovation to reopen its historic south entrance. The project is part of a broader effort to expand access to the Jackson Park landmark, even as preservation advocates criticize a separate proposal for a massive new north entrance. The...
State Volleyball Photo Gallery – Summit vs. Science Hill, Class AAA First Round
The Summit High School volleyball team suffered a 20-25, 25-27, 25-19, 25-21, 16-14 loss against Science Hill in the first round of the Class AAA state tournament on Tuesday, Oct.
Midway Physics Day brings science to life for nearly 2,000 students at the State Fair
WACH WACHFox provides coverage of news, sports, weather and local events in the Columbia, South Carolina area, including Lexington, Elgin, Cayce, Chapin, Peak, Blythewood, Newberry, Camden, Mulberry, Sumter, Eastover, Aiken, and Orangeburg, SC.
40 Years of Superconductor Science Just Got Turned Upside Down by a Stunning Discovery
A material that carries electricity without resistance may be held back by its own structure, challenging 40 years of assumptions about copper-based superconductors.
TTUHSC School of Nursing Expands Access to Maternal and Child Healthcare in Lubbock
The Texas Tech University Health Sciences Center (TTUHSC) School of Nursing celebrated the opening of Grand Expectations Health Center with a ribbon-cutting ceremony and open house today.
Is Mold in Coffee a Real Problem? Here Is What the Science Says Before You Panic
Is mold in your morning coffee actually a problem? Food scientists say probably not and here is why.
Is Mold in Coffee a Real Problem? Here Is What the Science Says Before You Panic
Is mold in your morning coffee actually a problem? Food scientists say probably not and here is why.
UC Davis may develop new Lake Tahoe science and community hub. Here’s where
The university has entered into a partnership with Placer County to explore a new project at three underutilized county properties.
Southwest Art Gallery & Science Center to host annual fundraising gala with natural elements theme
This year's gala, themed "Elements of Inspiration," will invite guests to wear attire inspired by natural and scientific elements while supporting arts and science education.
Several S&T researchers among top 2% cited scientists in their fields
A total of 94 current and former researchers affiliated with Missouri S&T are among the world’s top 2% most-cited scientists recognized either for their career-long impact or for their 2025 metrics, according to a Stanford University analysis of the Elsevier Data Repository....Continue Reading Several S&T researchers among top 2% cited scientists in their fields
When I was 8 years old, Carl Sagan showed me the universe I want you to see
I have always tried to pattern my interactions with my program audiences like Carl might have done. Every chance I get to do that is one more opportunity I have to spark someone else’s interest in science.
OpenAI acquires startup Orchestra Bio to beef up its biotech business
OpenAI says it's adding Orchestra's team and technology to work on Rosalind, its AI model for life sciences research, and to its related Rosalind Workbench tool, a harness that aims to help researchers plan experiments and analyze results.
Political science, history student connects hometown roots to DC policy work
Dawson Glogau gained hands-on experience in policy research and advocacy during a summer internship in Washington, D.C., through the Liberal Arts Semester in Washington Program.
Political science, history student connects hometown roots to DC policy work
Dawson Glogau gained hands-on experience in policy research and advocacy during a summer internship in Washington, D.C., through the Liberal Arts Semester in Washington Program.
NASA Study Refines Projections for Thwaites Glacier
Antarctica’s Thwaites Glacier could contribute more to sea level rise by the end of the century than some previous estimates. In some model simulations, the glacier’s contribution was as much as twice current projections.
INOVIO Announces Favorable Judgment in Litigation with VGXI, Inc. and GeneOne Life Science
/PRNewswire/ -- INOVIO Pharmaceuticals, Inc. (Nasdaq: INO), a biotechnology company focused on developing and commercializing DNA medicines to help treat and...
Halloween fun with a slice of science
Halloween can be many things: spooky, enchanting, fun, creative, mysterious and…scientific? That last word is what Walking Mountains Science Center hopes to bring to light when kids and families attend Fright at the Museum on...
Scientists Find 46,000-Year-Old Bone Fragments in a Cave, Leading to Groundbreaking Discovery
Six ancient bone fragments found in a Spanish cave belonged to a male Neanderthal, and their well-preserved DNA could reveal new details about his life
18:83 Speaker Series: Dr. Jenkins and The Mischievous Greyhound
Dr. Marjorie Jenkins turned career story into tale about 'finding her pack' at UND and School of Medicine & Health Sciences.
Renovated Brook Farmhouse now home to Mohonk Preserve’s science programs
A natural history...
Roper Mountain Science Center star returns to Greenville skyline
The Roper Mountain Science Center star has returned to its pedestal.
Roeper alum returns to educate after long career in science
BIRMINGHAM — Shannon Cass-Calay, 1988 graduate of The Roeper School, said it was always a life goal to return to the school as an educator.
NMSU professors collaborate on $1.2 million NASA grant
American third grade classrooms are filled with natural-born scientists – children obsessed with asking why and treating the world as an open-ended laboratory. But as they cross the threshold into...
Going with the Flow - College of Arts and Sciences
Scott Gifford studies the microscopic organisms that shape water quality, ecosystems, and Earth’s climate.
Dream and mind-wandering reports could offer hints about mental health
Dreams and mind-wandering have long fascinated psychologists and researchers studying the human mind. This is partly because these experiences offer glimpses into people's inner lives, emotions, past ...
The Center for Addiction Science and Innovation Holds First Outreach Event
The Center for Addiction Science and Innovation brought addiction science research out of the lab and onto the UConn Storrs campus with their outreach event.
WHS Students Create Women in Science and Engineering Club
Two students have founded the Women in Science and Engineering (WISE) Club at Westfield High School.
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.
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