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Kayla Keyt Testifies on Family Business and Defendant Caleb Flynn
Kayla Keyt testifies about her family's commercial flooring business, her late sister Ashley, and the financial projections she shared with the defendant, Caleb Flynn.
Game 155: Twins at Angels
First Pitch: 8:38 pm CDTTV: Twins.TVRadio: TIBN / WCCO 830 / The Wolf 102.9 FM / Audacy The kids have been showing out a bit in Anaheim, providing one of the only remaining reasons to watch 2026 Twins baseball as this underwhelming season has normalized itself to fall back in line with preseason projections. Now, […]
Big Ten Rankings and Projections After Week 2
There were several losses by Big Ten teams, and one big win by a Big Ten team last weekend
Big Ten 2026 Bowl Game Projections Tracker
Where are Big Ten teams going to go this winter.
Florida Gators get new bowl destination in SI's latest projections
Sports Illustrated projects Florida to face Wake Forest in the Gator Bowl following UF's upset win over Texas in Week 7.
Season debut shows why Ropes football is a regional contender
Ropes coach Beau Riker isn't concerned about rankings or outside projections, but Friday showed why many think highly of the Eagles.
Boston Celtics season preview: Opening schedule, win projection and everything to know for 2026-27
2026 Tennessee football: Updated record projection after Week 6
Tennessee's strength of schedule and record projection after Arkansas win in Week 6.
Kings' Projected Starting Five Ranked No. 29 in NBA
The Sacramento Kings' quiet offseason has most projections placing the franchise towards the bottom of the Western Conference. But, the team should definitely see improvements with the addition of Darius Acuff Jr. and key players returning to health.
Oklahoma still bowl bound in latest projections from USA TODAY Sports
The Oklahoma Sooners are still bowl bound in USA TODAY Sports latest bowl projections after Week 4.
In Praise of the St Louis Cardinals 2026 Season
Well it’s finally over and on the books for 2026. While the season didn’t end on a very good note, let’s instead talk about what went right. After stripping the roster down to the bolts, old school projections systems and Vegas odds had the Cardinals as one of the worst teams in baseball. Many fans […]
Midseason bowl projections for Duke football
A myriad of bowls and opponents dots the latest bowl projections for Duke and head coach Manny Diaz.
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
2026 Bowl Projections After Week Seven
Hello everyone, and welcome back to our weekly picks of who's in the playoffs and all the bowl games. This past week was circled on calendars since the schedules were revealed, with several top-25 matchups. However, it's doubtful anyone could have predicted what we saw, where five of the top seven teams in the AP …
Bladen Community College to host “So You Want to Start a Small Business” class and preview Pitch It Bladen 2027
The Small Business Center at Bladen Community College invites aspiring entrepreneurs to attend “So You Want to Start a Small Business” on Tuesday, Oct. 13, 2026, from 6:00 p.m. to 8:00 p.m. in Building 14, Room 104. This class will help participants explore what it takes to become an entrepreneur and take the first steps toward turning a business idea into reality.Participants will explore the entrepreneurial mindset and consider whether they have the interests, characteristics, motivation and willingness to take on the challenges of business ownership. The class will encourage attendees to examine their personal goals, expectations, strengths and readiness to pursue entrepreneurship.Attendees will also gain insight into the realities of starting and operating a small business, including the commitment, planning, decision-making and perseverance required to build a successful venture. Whether participants are just beginning to consider business ownership or already have an idea they want to pursue, this class will provide a foundation for determining their next steps.In addition to the class instruction, attendees will receive advance information about the upcoming Pitch It Bladen 2027 Business Competition, including the application form and details about the program. Individuals who are ready to move forward may submit their applications early and have the opportunity to receive advance acceptance into the program.Pitch It Bladen helps aspiring and emerging entrepreneurs develop their business ideas through structured instruction in business planning, financial management, cash-flow projections, marketing and operations. Participants work toward completing a business plan and preparing a business pitch, with the opportunity to compete for cash prizes.Last year's Pitch It Bladen program demonstrated the value of investing in local entrepreneurs by helping participants strengthen their business knowledge, develop their business plans and prepare to present their ideas. The competition showcased the creativity and potential of Bladen County's small-business community and provided participants with practical tools to move their business goals forward.Building on that success, Pitch It Bladen 2027 will provide another opportunity for local entrepreneurs to gain knowledge, build confidence and take meaningful steps toward launching or growing a business.“The Small Business Center wants to help individuals make informed decisions about entrepreneurship before they take the leap into business ownership,” said Theresa Dennison, Small Business Center director, in a press release. “This class gives participants an opportunity to evaluate whether entrepreneurship is right for them while also introducing them to Pitch It Bladen 2027 and the resources available to help them succeed.”Registration: Visit www.ncsbc.net and search for the class by name, or contact the Small Business Center at 910-879-5572 for additional information.
XGIMI Launches AURA 3 Series, Bringing Cinema-Scale Entertainment to the Living Room
/PRNewswire/ -- XGIMI, a global leader in premium smart projection and home entertainment, today announces the official launch of its AURA 3 Series, a new...
Why politicians should pay more attention to the polls (reprise)
Welcome to the 231st edition of The Week in Polls (TWIP), a polling newsletter that always welcomes new readers. So please don’t keep TWIP a secret; share it with your friends and colleagues: Share The Week in Polls With all the stories swirling around Reform, JL Partners and political polling, I am finally tearing myself away from talking about the regulation of polling this week - and instead re-running a previous piece reminding us why the solution to problems with polls isn’t simply to ban or ignore them. Rather, we need them to play a vital role in making our politics - and politicians - better. This is followed by summaries of the latest national voting intention polls, seat projections from MRPs and the most recent party leader ratings. Subscribers who pay for the full edition can also read ten insights from the latest polls and analyses, including: A trio of organisations and a pair of professors have been casting their eyes over the Liberal Democrats ahead of the party’s autumn conference; What impact did the summer heatwave have on views on climate change? and Which wins out between chocolate and cheese? If you are not yet a paid subscriber, you can read all ten by starting a free trial now: Get FREE 7-day trial For more polling news as it comes in ahead of next week’s edition, you can also follow The Week in Polls on Bluesky. Picking up on my doubt last week about whether or not 35% of British train travellers have tried to order a takeaway for delivery to a railway station or carriage, thank you to reader Iain, who has been in touch to say he has done just that… in India. Another quick pair of updates, this time on the controversies around Reform and polling. Politico has a further scoop - “Farage aide caught in donor sting attended Egypt retreat with JL Partners” - and Ian Dunt has written about the problems with polling too: “Seeing the response of many polling experts in the last few weeks suggests that they are nervous about what is happening and keen to mitigate against it. Seeing the response of journalists, which has been basically non-existent, suggests the precise opposite.” My usual reminder as well: please do hit reply if you’ve spotted a poll, focus group or new piece of poll-based research that you think should be in contention for coverage in a future edition. Thank you! And with that, on with the show. How politicians get public opinion wrong I have written before about the benefits that come from widespread availability of high-quality political polling. We need more polls and more good coverage of polls. However, what I’ve not dug into before is the research into how accurately politicians estimate public opinion on issues. Thankfully we have academic research to tell us. First, the bad news: We present results from a study of 866 politicians in four countries.1 Politicians were asked to estimate the percentage of public support for various policy proposals. Comparing more than 10,000 estimations with actual levels of public support, we conclude that politicians are quite inaccurate estimators of people’s preferences. They make large errors and even regularly misperceive what a majority of the voters wants. Politicians are hardly better at estimating public preferences than ordinary citizens. Walgrave, S., Jansen, A., Sevenans, J., Soontjens, K., Pilet, J.B., Brack, N., Varone, F., Helfer, L., Vliegenthart, R., van der Meer, T., Breunig, C., Bailer, S., Sheffer, L. & Loewen, P.J. (2023a), “Inaccurate Politicians: Elected Representatives’ Estimations of Public Opinion in Four Countries”, The Journal of Politics, 85(1): 209-222. The bad news is not quite as bad as that makes it sound because, when asked whether the majority of public opinion was for or against various policies, politicians picked the wrong option ‘only’ 29% of the time. However, this included getting it wrong even when public opinion is far from evenly split on an issue: They do not only get it wrong when the public is divided and hard to read (e.g., when there is a 51%:49% distribution). Seventy percent of the misplacements occur for policies with a relatively clear distribution of at least 60% (dis)agreeing citizens. Moreover, the public scored only slightly worse than politicians, picking the wrong option 2.7 out of 8 times on average, compared with 2.3 times for politicians. Turning to the other measure of accuracy (not which side is in the lead but what the percentage support is for each side), politicians on average were 18 percentage points out in their guesses. Again, this was only slightly better than the public, whose error came in at 21 percentage points.2 Further research, using the same mix of countries, gives a little more comfort about how (in)accurate perceptions are: We show that politicians have a better understanding of public opinion when they think the issue matters to voters. Further, when an issue is personally important to politicians they more accurately estimate their party supporters’ opinions. The results confirm that politicians hold more accurate perceptions of voters’ preferences when they think it is important to do so but not necessarily when the issues actually are important to voters. Butler, C., Walgrave, S., Soontjens, K. & Loewen, P.J. (2024), “Politicians are better at estimating public opinion when they think it is more salient”, Party Politics: 1–13. Even so, it’s not a good picture. The remedy for this? Politicians should spend more time reading the polls. So forward this newsletter to someone you know… Share For a more general argument against banning polls, see my 2024 piece. Is “Let Bartlet Be Bartlet” good advice or not? The latest episode of my Political Fictions podcast heads across the Atlantic for a dip into one of the political TV classics: Mark and Cory talk about a giant of American political drama for the first time this week, as they tackle The West Wing. They talk about Let Bartlet Be Bartlet, the nineteenth episode of series one. In it, Mark wonders if The West Wing is actually the epitome of the “Boris Johnson school of politics”, Cory outmanoeuvres Mark into confirming we will record a Christmas Special about Love, Actually and they debate whether the central message of this episode has been misunderstood. Cory’s email newsletter is Paperback Rioter and Mark has a family of email newsletters. Subscribe to our newsletter for some additional bonus content and to get alerted whenever a new episode comes out. Our theme tune is “Monkeys Spinning Monkeys” by Kevin MacLeod/incompetech.com and licensed under the Creative Commons: By Attribution 4.0 License. You can also listen to our episode on Apple Podcasts, Spotify, the web or YouTube. Elsewhere from me… [ A Lord's Eye View How to fix the problem of money in our politics Welcome to my latest update on work in the House of Lords. This time I am taking a look at how our political system is regulated, and the protections we need to keep democracy safe from becoming simply a contest to see who has the biggest bank account… Read more 5 days ago · 3 likes · 2 comments · Mark Pack ](https://lordseyeview.substack.com/p/how-to-fix-the-problem-of-money-in?utm_source=substack&utm_campaign=post_embed&utm_medium=web&embedding_publication_id=1269283) If you spot a factual error… Borrowing an idea from Stuart Ritchie and others, if you spot a factual error in an edition of this newsletter, I will give you a free 12-month subscription to the paid-for version (or an extra 12 months on your existing one). Factual errors qualify, but grammatical errors or disagreements over interpretation do not, and my decision is final. Messages about both of those are always welcome, though. Voting intention and leadership ratings Here are the latest voting intention polls from different pollsters. It is all pretty static at the moment, with a small and consistent Labour lead in nearly all the polls. The table is also online here, along with explanations about what is included. It is updated regularly throughout the week as new polls are released. Next are the seat projections from MRPs, also sorted by fieldwork dates, listing those which are based on dedicated fieldwork (rather than models based on averages of other polls). Because such MRPs are published infrequently, some of the entries below are quite old. Finally, here is a summary of leadership ratings, with a graph from PollCheck: Detailed numbers from the latest polls are online here, and both that and the graph are updated regularly throughout the week as new data comes out. For historical figures on both voting intention and leader approval stretching back to the 1930s, including Parliamentary by-election polls, see PollBase. Catch up on the previous two editions [ ](https://theweekinpolls.substack.com/p/a-crisis-point-for-political-polling) [ A crisis point for political polling Sep 13 ](https://theweekinpolls.substack.com/p/a-crisis-point-for-political-polling) [ Read full story ](https://theweekinpolls.substack.com/p/a-crisis-point-for-political-polling) [ ](https://theweekinpolls.substack.com/p/extra-questions-about-the-polls-in) [ Extra questions about the polls in Reform’s funding scandal Sep 6 ](https://theweekinpolls.substack.com/p/extra-questions-about-the-polls-in) [ Read full story ](https://theweekinpolls.substack.com/p/extra-questions-about-the-polls-in) My privacy policy and other legal information are available here. Links to purchase books or other items are usually affiliate links which pay a commission for each sale. Quotes from social media messages are occasionally lightly edited for punctuation and clarity. If you are subscribed to other email lists of mine, please note that unsubscribing from this one will not automatically remove you from the others. If you wish to be removed from all my lists, simply reply to this email to let me know. A quintet of Lib Dem polling analyses, and 9 other polling insights you shouldn’t miss The following ten findings from the most recent polls and analyses are only for subscribers who pay for the full edition, but you can sign up for a free trial to read them straight away. Ahead of the start of Liberal Democrat conference, we have a trio of organisations and a pair of professors with pieces out about Ed Davey’s party:
6-Foot-2 Former Broncos Cornerback Back Signs With Bears
Former Denver Broncos cornerback Keidron Smith has found a new NFL home in the NFC with a team garnering Super Bowl projections. The post 6-Foot-2 Former Broncos Cornerback Back Signs With Bears appeared first on HEAVY.
Cleveland Cavaliers season preview: Opening schedule, win projection and what to know for 2026-27
Washington Wizards season preview: Opening schedule, win projection and everything to know for 2026-27
Kings Ranked Last in Latest Future Projection
The Sacramento Kings were ranked last in the latest projections that takes a look at the future for each NBA team.
Portland Trail Blazers season preview: Opening schedule, win projection and what to know for 2026-27
Phoenix Suns season preview: Opening schedule, win projection and what to know for 2026-27
ESPN's bowl projections for Florida remain unchanged after Week 2
After Florida's Week 2 win over Campbell, ESPN's Kyle Bonagura and Mark Schlabach did not change their bowl game prediction for the Gators.
Find your way around Blink Cincinnati with these festival maps
Explore Blink Cincinnati with official festival maps showing art installations, projection sites, parking areas, shuttle routes and key events.
City sales tax builds on upward trend, exceeding budget projections to date
Sales tax revenue continues to trend above expectations in Sioux Falls this year, driven largely by business spending versus consumers.
New WVU Bowl Projection Comes With a Fascinating Twist
The West Virginia Mountaineers have lost consecutive Big 12 games, but one new bowl projection gives fans an interesting reason to keep thinking about what could still be waiting at the end of the season. WVU fell to 3-2 following its 45-42 loss to Iowa State on Oct. 3. Rich Rodriguez’s team is now 0-2 in […] The post New WVU Bowl Projection Comes With a Fascinating Twist appeared first on HEAVY.
Ohio State OL Austin Siereveld Earns Favorable NFL Draft Projection
Ohio State offensive lineman Austin Siereveld has landed a major prediction for the 2027 NFL Draft.
This Chicago prof believes we are living on borrowed time, but it was his controversial life expectancy firm that died
A court fight between Abacus and Coventry puts former UIC professor S. Jay Olshansky’s life expectancy projections and defunct firm under scrutiny.
Tennessee's 2026 record projection, strength of schedule after Week 2
Tennessee football's updated record projection and strength of schedule after Week 2 in 2026.
Three Reasons Bucks Could Exceed Expectations This Season
Everyone has written off Milwaukee after the Giannis trade, but the roster has more ways to win than the projections admit.
Big 12 football bowl projections after Week 5 results
BYU and Utah are the Big 12's CFP contenders after Week 5, while Colorado, TCU and Kansas are left out of bowl projections.
Toronto Raptors season preview: Opening schedule, win projection and what to know for 2026-27
ESPN makes Georgia CFP projection ahead of Alabama game
ESPN projects Georgia football to reach the College Football Playoff ahead of a tough upcoming matchup against Alabama.
The science behind the beauty business
Some of Europe’s industrial champions may be in retreat, but its cosmetics sector remains a global leader, buoyed by healthy demand, recognised brands and a reputation for innovation."The fact is, the science in cosmetics is better here in Europe than anywhere else in the world,” says Pierre Morvan, CEO of Technature, a private label cosmetics manufacturer located near Brest in France’s northwestern Brittany region. “You have to have good science in order to make the difference, and that is why we invest so much in research and innovation.”Across Europe, the beauty and skincare products sector supports an estimated 3.6 million jobs, including 265,000 employed directly in the industry, according to the Cosmetics Europe trade group.. Cosmetics production contributes an estimated €11 billion to the EU economy, and generated €30 billion in export revenue last year, a €400 million rise from 2024.Technature itself has a global footprint, supplying products for 1,500 brands in 65 countries. Its range of skin gels, facial masks, nail treatments and other products include natural ingredients and extracts derived from plants, such as seaweed, that are developed and refined through science-based analysis and testing.While industry projections point to sustained growth for the foreseeable future, driven by emerging economies and wider availability of exclusive brands that were once chiefly sold by high street retailers, the sector is not immune to the impact of geopolitics and trade wars. The Trump Administration’s tariff threats have dented cosmetics exports to the EU industry's largest overseas market. After the European Parliament approved the EU-US Turnberry Agreement in June, setting a 15% levy on many EU goods, the French Federation of Beauty Companies warned that “exports are falling sharply” and urged the EU to negotiate an opt-out for cosmetics.Technature’s CEO flags South Korea as an emerging competitor, partly due to its assertive marketing efforts. “I would have to say I am a little bit scared,” Morvan says, regarding the growth potential of the South Korean cosmetics industry. “This is why science and innovation are so important if Europe is to remain the leader.”With a workforce of 200, including biologists, chemists and other scientists, around 15% of Technature’s staff work in three research and development (R&D) labs. A similar number work in four quality control and assurance facilities, where science plays a crucial in ensuring product safety in a sector that is subject to the European Cosmetics Regulation.Educational exchange between industry and academiaIn recognition of Technature’s research and innovation, Morvan was selected as one of Brest’s ambassadors to Science Comes to Town (SCTT), a European initiative to strengthen communications and understanding between science and society. Brest is one of three coastal cities in the EU-funded programme, alongside Split (in Croatia) and Kiel (in Germany). From 7-11 September, Brest will host the EU TalentOn contest featuring 100 early-career researchers from across Europe.Morvan appreciates the value of engagement with educational and scientific institutions as well as the home community. For instance, Technature collaborates closely with university partners to enhance its in-house R&D. In addition, it invites students to its labs and sends its own researchers to local institutions. "We absolutely want the students to know what the industry is all about,” Morvan says, noting that seeing science in action can help young people “understand that they can do something real with science, to create something with what they are learning.” He says another important benefit: encouraging new generations of young people to consider a career in cosmetics.Community involvement also raises awareness about Technature and the skincare industry as a whole. “The public gains recognition of the innovative company that we are, and this is important for getting new customers,” Morvan says. One of its recent innovations — tiny, colourful cosmetic pearls that release skin moisturisers on application — was showcased at this year’s VivaTech event in Paris.Morvan holds a master's degree from the Brest Business School and studied animal production and biology in Brest at the University of Western Brittany (UBO), an SCTT partner, and at the University of Tours. He got his start in business in 2002, initially working on using seaweed as a raw material in the food industry before transitioning to cosmetics. Morvan has always been interested in connecting science and business, reflecting one the goals of SCTT to enhance public-private collaboration.The invitation to participate in SCTT was unexpected. “It was a surprise to get a call from the city of Brest saying that they wanted me on this programme,” Morvan recalls, adding that officials were drawn by his company’s R&D. “It's not only theory and science fundamentals. Our science is something that is applicable to the global market — and important for the community.”Science|Business, which connects policymakers, academics and industry through its news reporting, analysis and events, is an SCTT partner.
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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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