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OpenAI CEO Sam Altman has defended the resource-intensive use of AI by comparing it to all the energyand foodthat humans require, sparking a wave of backlash across social media. That comparison, experts in climate and tech spaces say, is misguided, downplays the climate risks associated with AI, and illustrates the disconnect between tech CEOs and the rest of society. Altmans comments came while speaking to the Indian Express at the India AI Impact summit. The outlet asked him to address some of the common criticisms of AI, including the amount of energy and water the technology requires. One of the things that is always unfair in this comparison is people talk about how much energy it takes to train an AI model relative to how much it costs a human to do one inference query, Altman says. But it also takes a lot of energy to train a human, he continues. It takes like 20 years of life, and all of the food you eat during that time, before you get smart. And not only that, it took the very widespread evolution of the 100 billion people who have ever lived. When considering the energy needed to train a human, Altman claims in the interview that AI has “probably already caught up to humans in terms of energy efficiency. Misguided comparison But the tech CEO’s blunt comparison is misguided, says Sasha Luccioni, climate lead of the AI platform Hugging Face. On a fundamental level, humans and AI models don’t use energy and natural resources in the same manner, and comparing the two makes no sense, she says in an email to Fast Company. AI models are trained on human data, Luccioni points out, so if comparing the two, you should also take into account the time and resources that went into writing the books and creating the data used to train AI models. To Luccioni, Altmans comments illustrate a “fundamental disconnect” between Big Tech leaders and broader society. These billionaires have built their fortunes on exploiting human knowledge and the earth’s natural resources, and continue taking both for granted while getting richer by the day, she adds. Fast Company reached out to OpenAI for comment. AI’s water and energy use Altmans comparison has drawn particular ire from those in the climate space, including Michael Mann, a climatologist and coauthor, with scientist Peter Hotez, of the 2025 book Science Under Siege: How to Fight the Five Most Powerful Forces That Threaten Our World. Indeed, the CEO’s statements tie into the very themes of the book. According to Mann, the book argues that forces like plutocrats, pros, petrostates, phonies, and the press promote anti-science rhetoric, which then hampers humanity’s ability to tackle everything from pandemics to the climate crisis. Exact calculations about AIs water and energy use vary, but many experts have raised alarms about its enormous power and resource needs. A 2026 report from Global Water Intelligence projects that water demand from the AI-driven New Economy will surge 129% by 2050, putting even more pressure on strained utility systems alongside climate threats. The International Energy Agency has likewise projected that total data center consumption, driven by AI, will double by 2030. Though Altman dismissed concerns over AI’s water use, he did say that energy consumption is a concern, and that because the “world is using so much AI . . . we need to move toward nuclear or wind and solar very quickly.” So far, the AI boom has led to an increase in natural gas power plants, even though it’s cheaper to build and run new clean energy projects. Longtermism and techno-utopianism According to Mann, Altman’s comments reek of controversial and potentially dangerous viewpoints that he says are common among tech executives, like longtermism and techno-utopianism. Longtermism promotes the idea that positively influencing the long-term future is a key moral imperative; its a belief that has been linked to the effective altruism movement. Looking long-term would suggest caring about climate change, because the effects of sustained fossil fuel emissions will have disastrous impacts on humans for years to come. But “longtermists” dont tend to regard climate change as an existential risk. Instead, they focus on threats that they say technology can solve. Techno utopianism, similarly, is a belief that technological advances are the way to achieve a perfect future society. As Mann sees it, Altman along with other tech CEOs promote an idea that society should focus on the benefits of AI and other technologies while “implicitly downplaying the risks and threats posed in the immediate term, including the climate crisis.” There is, as I would remind Altman and his ilk, no economy on a dead planet, Mann adds.
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As AI use continues to grow, so is frustration with the technology. From strange responses that don’t make any sense to learning curves to how its implemented at work, there’s no shortage of AI quirks to get used to. However, how users are responding to those annoyances is vastly different. According to a new report from Adobe Acrobat and Firefly, frustrations are not few. In fact, of the 1,008 AI users survey, 91% said they have abandoned generative AI tasks in favor of non-AI methods over said emotion. Mostly, that’s because writing quality AI prompts is a key strategy in effectively using the tool, but it’s not always totally intuitive. There’s a definite learning curve when it comes to writing prompts that lead to the best output. However, most users have a breaking point. For example, when it comes to using AI tools that generate images, respondents said they expect a quality result after four attempts. By the seventh try, most simply give up. For text tasks, users aren’t quite so patient. When it comes to prompting AI to write emails or social media posts, users want a solid response after two attempts and give up altogether by the fourth. Some users do more than just give up on writing prompts, however. Some users actually take to yelling at the technology. When it comes to responding in anger, the response is fairly gendered: Men are overwhelmingly more likely to scold AI. Per the report, men said they shouted at the technology in all caps 80% more often than women, believing it may somehow help to improve the result. Meanwhile, the trend of being polite to AI is more common in certain industries. Those in finance and banking reported using pleasantries like “please” 43% of the time. Similarly, those who work in education, transportation, and logistics did so 42%. Creative arts and healthcare workers only did so at 38% and 36%, respectively. Interestingly, regardless of the fact that men are more prone to yelling at AI, they also seem oozing with confidence at their ability to use the technology well. Per the report, men were 15% more confident in their prompting abilities than women. However, their confidence did not match their genuine skill level: The prompts were only better 5% of the time.. Confidence aside, per the report, some helpful strategies to keeping frustrations at bay and getting better results include breaking the tasks into steps, saving your strongest prompts to reuse, fact-checking and giving solid examples. Unfortunately, pleasantries won’t help with better output. Likewise, neither will yelling at it. (Sorry, guys.)
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Want more housing market stories from Lance Lamberts ResiClub in your inbox? Subscribe to the ResiClub newsletter. Based on our analysis of the Zillow Home Value Index, U.S. home prices are up just +0.2% year-over-year between January 2025 and January 2026. That marks a deceleration from the +2.6% growth rate a year earlierthough national price growth has recently stabilized, ticking a tad higher from a low of -0.01% in August 2025. In the first half of 2025, the number of major metro area housing markets seeing year-over-year declines climbed. That count has since pretty much stopped ticking up. 31 of the nations 300 largest housing markets (i.e., 10% of markets) had a falling year-over-year reading in the Jan. 2024 to Jan. 2025 window. 42 of the nations 300 largest housing markets (i.e., 14% of markets) had a falling year-over-year reading in the Feb. 2024 to Feb. 2025 window. 60 of the nations 300 largest housing markets (i.e., 20% of markets) had a falling year-over-year reading in the March 2024 to March 2025 window. 80 of the nations 300 largest housing markets (i.e., 27% of markets) had a falling year-over-year reading in the April 2024 to April 2025 window. 96 of the nations 300 largest housing markets (i.e., 32% of markets) had a falling year-over-year reading in the May 2024 to May 2025 window. 110 of the nations 300 largest housing markets (i.e., 36% of markets) had a falling year-over-year reading in the June 2024 to June 2025 window. 105 of the nations 300 largest housing markets (i.e., 36% of markets) had a falling year-over-year reading in the July 2024 to July 2025 window. 109 of the nations 300 largest housing markets (i.e., 35% of markets) had a falling year-over-year reading in the Aug. 2024 to Aug. 2025 window. 105 of the nations 300 largest housing markets (i.e., 35% of markets) had a falling year-over-year reading in the Sept. 2024 to Sept. 2025 window. 105 of the nations 300 largest housing markets (i.e., 35% of markets) had a falling year-over-year reading in the Oct. 2024 to Oct. 2025 window. 98 of the nations 300 largest housing markets (i.e., 33% of markets) had a falling year-over-year reading in the Nov. 2024 to Nov. 2025 window. 106 of the nations 300 largest housing markets (i.e., 35% of markets) had a falling year-over-year reading in the Dec. 2024 to Dec. 2025 window. 100 of the nations 300 largest housing markets (i.e., 33% of markets) had a falling year-over-year reading in the Jan. 2025 to Jan. 2026 window. As you can see above, in the first half of 2025, there was a notable increase in the number of housing markets slipping into year-over-year price declines as the supplydemand equilibrium (as measured by inventory) shifted more quickly toward homebuyers. Over the past seven months, however, the list of declining markets has begun to stabilize and inventory growth has also decelerated. Home prices are still climbing a little year-over-year in many regions where active inventory remains well below pre-pandemic 2019 levels, such as pockets of the Northeast and Midwest. In contrast, some pockets in states like Texas, Florida, and Coloradowhere active inventory exceeds pre-pandemic 2019 levels by a solid clipare seeing modest home price pullbacks or flat pricing. Click here for an interactive version of the chart below Many of the housing markets seeing the most softness, where homebuyers have gained the most leverage, are primarily located in Sun Belt regions, particularly the Gulf Coast and Mountain West. Many of these areas saw even greater price surges during the Pandemic Housing Boom, with home price growth outpacing local income levels. As pandemic-driven domestic migration slowed and mortgage rates rose in 2022, markets like Tampa and Austin faced challenges, relying on local income levels to support frothy home prices. That Sun Belt softening was further compounded by an abundance of new home supply in the Sun Belt. Builders are often willing to lower prices or offer affordability incentives to maintain sales, which also has a cooling effect on the resale market. As a result, some buyers who might have previously opted for existing homes are instead choosing new construction with more attractive dealswhich added further upward pressure to resale inventory growth over the past few years. window.addEventListener("message",function(a){if(void 0!==a.data["datawrapper-height"]){var e=document.querySelectorAll("iframe");for(var t in a.data["datawrapper-height"])for(var r,i=0;r=e[i];i++)if(r.contentWindow===a.source){var d=a.data["datawrapper-height"][t]+"px";r.style.height=d}}}); Of course, while 100 of the nations 300 largest metro area housing markets are seeing year-over-year home price declines, another 200 are seeing year-over-year home price increases. Where are home prices still up on a year-over-year basis? See the map below. window.addEventListener("message",function(a){if(void 0!==a.data["datawrapper-height"]){var e=document.querySelectorAll("iframe");for(var t in a.data["datawrapper-height"])for(var r,i=0;r=e[i];i++)if(r.contentWindow===a.source){var d=a.data["datawrapper-height"][t]+"px";r.style.height=d}}}); Below is a historical chart showing the year-over-year change in home prices across the 50 largest metro housing markets, with the yellow line representing the national aggregate, dating back to 2000. While the range [see chart above] between the strongest and weakest metro area housing markets right now is fairly normal historically speaking, the bifurcation (i.e., direction) itselfthe share of markets with rising home prices versus those with falling pricesis wider than normal, given that national appreciation has stabilized into a softer market with growth barely above +0.0%. And the longer some markets remain in the rising camp while others stay in the falling camp, the wider the gulf can become between the relatively more resilient markets and the weaker ones. For example, home prices in the Hartford, CT metro area are now +21.2% above their 2022 peak, while home prices in the Austin, TX metro area sit -27.8% below their 2022 peak. Some of that bifurcation boils down to mean reversion, with many of the outright home price declines occurring in markets that overheated further during the Pandemic Housing Boom. Note: For the historical chart below, we analyzed the 200 largest markets rather than the 300 used above, as some markets ranked 201 to 300 lack complete data going back to 2000. When weighted by population (not visualized), the housing market appears slightly weaker than the chart below suggestswhich aligns with the fact that, among just the 50 largest housing markets, 25 (roughly 50%) are currently posting negative year-over-year price growth, and nationally aggregated home prices are up just +0.2% year-over-year using the Zillow Home Value Index.
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