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HKS Architects’ new project is a campground designed with both sustainability and accessible luxury in mind.
The architecture firm HKS is known for its innovative, climate-informed approach to large-scale architectural projects, from an award-winning stadium in California to a yacht club in Saudi Arabia to a bioscience lab in Singapore.The practice is also committed to research, landing on Fast Company’s 200 most innovative companies for designing air filtration systems in a luxury condo building in Dallas.
The group’s latest project, AutoCamp Joshua Tree, is just outside its namesake national park in southern California, about one hour from Palm Springs and two hours from Los Angeles. The glamping hotspot embodies HKS’s philosophy by keeping guests cool — literally and figuratively — using design strategies to manage the desert heat.
I spoke to Michael Strohmer, who leads the firm’s hotel practice, about how they tried to maximize shade and minimize environmental impact. Our conversation has been edited for length and clarity.
What is the general architectural approach for HKS?
HKS’s approach to hospitality is to start by understanding the place — where the site is located. Is it urban? A resort? The point is for the design to be integrated into the environment. Not only is it important for the nearby community, it’s important for the guests visiting. Travelers are looking for something authentic that tells the story of the place. Our job is to convey that through the design. Integration with the natural environment is key to what we do.
I’m curious how you applied this approach to AutoCamp in Joshua Tree?
The AutoCamp at Joshua Tree was unique for us. We have designed several five star resorts — Four Seasons, Ritz Carlton, Rosewood to name a few — but Joshua Tree was our first autocamp. (We have since done another in Zion State Park.) They were going for approachable luxury versus ultra luxury — they wanted to provide a higher-end experience and amenities at a lower price point, still with good service. The point was to build a place for guests to experience a natural environment with a high level of quality. It’s definitely a trend we’re seeing quite a bit, this desire to reconnect with nature.
Matt Kisiday/courtesy of HKS
Your Habitable score shows extremely high for drought, heat, fire, and even flooding! Were you aware of that when you built here?
We were definitely aware of the issues of building in a desert environment. The high desert freezes in wintertime, and while we are aware of the climate and were considering that from our design approach, I didn’t know about the flood risk. I guess flash floods can be an issue for Palm Springs. Still, the AutoCamp location is at a higher elevation. It’s not far way but a bit of a different climate.
What decisions did you make to build AutoCamp for this desert environment?
When it came to building orientation, that was a big factor we looked at. The main clubhouse building was the one fixed piece of architecture at AutoCamp — the guest rooms are a collection of Airstream trailers that can be moved. We oriented the clubhouse to minimize the solar impact and allow for natural light to come in, for the breeze winds to come through and cool off the interior during the summer months.
The number one thing during summer months in the desert is to provide shade to escape to, so we built it so the sun doesn’t hit the glass directly so that it doesn’t absorb into the interior space. The glass is protected with horizontal elements — trellis slats or louvers — to let light come through but not the [direct] sun.
We also worked with a landscape designer that is familiar with the desert environment, so we planted a lot of native species also to save on water. The biggest goal is to minimize the site impact. Bringing in prefab trailers really helped. Non-conventional construction meant we didn’t have to wipe out land to rebuild. We were trying to have a light touch.
How did you adapt the design for different desert seasons?
By providing large operable expanses of glass that allow the clubhouse to open up during more temperate months. We built in the ability to bring in natural air and breezes [instead of] always having to use the AC.
Matt Kisiday/courtesy of HKS
What are your three top takeaways for people living in a desert environment?
1. Mobility is a great option. I love the idea of a moveable trailer to take to different environments. The light touch minimizes disruption to the site.
2. Providing shade not just for people but for the buildings is key. Come up with creative ways to minimize solar impact. Landscaping goes a long way.
3. The main AutoCamp building is in a barrel arched shape based on a Quonset huts, industrial buildings used by the military that can be erected quickly in a time of need. They require minimal construction and the panels are preformed with structural integrity. It’s a playful spin off of something meant for industrial use and ties into the whole approachable luxury concept. It doesn’t feel so precious.
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Why the new “reasoning” models might gobble up more electricity — at least in the short term
What happens when artificial intelligence takes some time to think?
The newest set of models from OpenAI, o1-mini and o1-preview, exhibit more “reasoning” than existing large language models and associated interfaces, which spit out answers to prompts almost instantaneously.
Instead, the new model will sometimes “think” for as long as a minute or two. “Through training, they learn to refine their thinking process, try different strategies, and recognize their mistakes,” OpenAI announced in a blog post last week. The company said these models perform better than their existing ones on some tasks, especially related to math and science. “This is a significant advancement and represents a new level of AI capability,” the company said.
But is it also a significant advancement in energy usage?
In the short run at least, almost certainly, as spending more time “thinking” and generating more text will require more computing power. As Erik Johannes Husom, a researcher at SINTEF Digital, a Norwegian research organization, told me, “It looks like we’re going to get another acceleration of generative AI’s carbon footprint.”
Discussion of energy use and large language models has been dominated by the gargantuan requirements for “training,” essentially running a massive set of equations through a corpus of text from the internet. This requires hardware on the scale of tens of thousands of graphical processing units and an estimated 50 gigawatt-hours of electricity to run.
Training GPT-4 cost “more than” $100 million OpenAI chief executive Sam Altman has said; the next generation models will likely cost around $1 billion, according to Anthropic chief executive Dario Amodei, a figure that might balloon to $100 billion for further generation models, according to Oracle founder Larry Ellison.
While a huge portion of these costs are hardware, the energy consumption is considerable as well. (Meta reported that when training its Llama 3 models, power would sometimes fluctuate by “tens of megawatts,” enough to power thousands of homes). It’s no wonder that OpenAI’s chief executive Sam Altman has put hundreds of millions of dollars into a fusion company.
But the models are not simply trained, they're used out in the world, generating outputs (think of what ChatGPT spits back at you). This process tends to be comparable to other common activities like streaming Netflix or using a lightbulb. This can be done with different hardware and the process is more distributed and less energy intensive.
As large language models are being developed, most computational power — and therefore most electricity — is used on training, Charlie Snell, a PhD student at University of California at Berkeley who studies artificial intelligence, told me. “For a long time training was the dominant term in computing because people weren’t using models much.” But as these models become more popular, that balance could shift.
“There will be a tipping point depending on the user load, when the total energy consumed by the inference requests is larger than the training,” said Jovan Stojkovic, a graduate student at the University of Illinois who has written about optimizing inference in large language models.
And these new reasoning models could bring that tipping point forward because of how computationally intensive they are.
“The more output a model produces, the more computations it has performed. So, long chain-of-thoughts leads to more energy consumption,” Husom of SINTEF Digital told me.
OpenAI staffers have been downright enthusiastic about the possibilities of having more time to think, seeing it as another breakthrough in artificial intelligence that could lead to subsequent breakthroughs on a range of scientific and mathematical problems. “o1 thinks for seconds, but we aim for future versions to think for hours, days, even weeks. Inference costs will be higher, but what cost would you pay for a new cancer drug? For breakthrough batteries? For a proof of the Riemann Hypothesis? AI can be more than chatbots,” OpenAI researcher Noam Brown tweeted.
But those “hours, days, even weeks” will mean more computation and “there is no doubt that the increased performance requires a lot of computation,” Husom said, along with more carbon emissions.
But Snell told me that might not be the end of the story. It’s possible that over the long term, the overall computing demands for constructing and operating large language models will remain fixed or possibly even decline.
While “the default is that as capabilities increase, demand will increase and there will be more inference,” Snell told me, “maybe we can squeeze reasoning capability into a small model ... Maybe we spend more on inference but it’s a much smaller model.”
OpenAI hints at this possibility, describing their o1-mini as “a smaller model optimized for STEM reasoning,” in contrast to other, larger models that “are pre-trained on vast datasets” and “have broad world knowledge,” which can make them “expensive and slow for real-world applications.” OpenAI is suggesting that a model can know less but think more and deliver comparable or better results to larger models — which might mean more efficient and less energy hungry large language models.
In short, thinking might use less brain power than remembering, even if you think for a very long time.
On Azerbaijan’s plans, offshore wind auctions, and solar jobs
Current conditions: Thousands of firefighters are battling raging blazes in Portugal • Shanghai could be hit by another typhoon this week • More than 18 inches of rain fell in less than 24 hours in Carolina Beach, which forecasters say is a one-in-a-thousand-year event.
Azerbaijan, the host of this year’s COP29, today put forward a list of “non-negotiated” initiatives for the November climate summit that will “supplement” the official mandated program. The action plan includes the creation of a new “Climate Finance Action Fun” that will take (voluntary) contributions from fossil fuel producing countries, a call for increasing battery storage capacity, an appeal for a global “truce” during the event, and a declaration aimed at curbing methane emissions from waste (which the Financial Times noted is “only the third most common man-made source of methane, after the energy and agricultural sectors”). The plan makes no mention of furthering efforts to phase out fossil fuels in the energy system.
The Interior Department set a date for an offshore wind energy lease sale in the Gulf of Maine, an area which the government sees as suitable for developing floating offshore wind technology. The auction will take place on October 29 and cover eight areas on the Outer Continental Shelf off Massachusetts, New Hampshire, and Maine. The area could provide 13 gigawatts of offshore wind energy, if fully developed. The Biden administration has a goal of installing 30 GW of offshore wind by 2030, and has approved about half that amount so far. The DOI’s terms and conditions for the October lease sale include “stipulations designed to promote the development of a robust domestic U.S. supply chain for floating wind.” Floating offshore wind turbines can be deployed in much deeper waters than traditional offshore projects, and could therefore unlock large areas for clean power generation. Last month the government gave the green light for researchers to study floating turbines in the Gulf of Maine.
In other wind news, BP is selling its U.S. onshore wind business, bp Wind Energy. The firm’s 10 wind farm projects have a total generating capacity of 1.3 gigawatts and analysts think they could be worth $2 billion. When it comes to renewables, the fossil fuel giant said it is focusing on investing in solar growth, and onshore wind is “not aligned” with those plans.
The number of jobs in the U.S. solar industry last year grew to 279,447, up 6% from 2022, according to a new report from the nonprofit Interstate Renewable Energy Council. Utility-scale solar added 1,888 jobs in 2023, a 6.8% increase and a nice rebound from 2022, when the utility-scale solar market recorded a loss in jobs. The report warns that we might not see the same kind of growth for solar jobs in 2024, though. Residential installations have dropped, and large utility-scale projects are struggling with grid connection. The report’s authors also note that as the industry grows, it faces a shortage of skilled workers.
Interstate Renewable Energy Council
Most employers reported that hiring qualified solar workers was difficult, especially in installation and project development. “It’s difficult because our projects are built in very rural areas where there just aren't a lot of people,” one interviewee who works at a utility-scale solar firm said. “We strive to hire as many local people as possible because we want local communities to feel the economic impact or benefit from our projects. So in some communities where we go, it is difficult to find local people that are skilled and can perform the work.”
The torrential rain that has battered central Europe is tapering off a bit, but the danger of rising water remains. “The massive amounts of rain that fell is now working its way through the river systems and we are starting to see flooding in areas that avoided the worst of the rain,” BBC meteorologist Matt Taylor explained. The Polish city of Nysa told its 44,000 residents to leave yesterday as water rose. In the Czech Republic, 70% of the town of Litovel was submerged in 3 feet of flooding. The death toll from the disaster has risen to 18. Now the forecast is calling for heavy rain in Italy. “The catastrophic rainfall hitting central Europe is exactly what scientists expect with climate change,” Joyce Kimutai, a climate scientist with Imperial College London’s Grantham Institute, toldThe Guardian.
A recent study examining the effects of London’s ultra-low emissions zone on how students get to school found that a year after the rules came into effect, many students had switched to walking, biking, or taking public transport instead of being driven in private vehicles.
Welcome to Decarbonize Your Life, Heatmap’s special report that aims to help you make decisions in your own life that are better for the climate, better for you, and better for the world we all live in. This is our attempt, in other words, to assist you in living something like a normal life while also making progress in the fight against climate change.
That means making smarter and more informed decisions about how climate change affects your life — and about how your life affects climate change. The point is not what you shouldn’t do (although there is some of that). It’s about what you should do to exert the most leverage on the global economic system and, hopefully, nudge things toward decarbonization just a little bit faster.
We certainly think we’ve hit upon a better way to think about climate action, but you don’t have to take our word for it. Keep reading here for more on how (and why) we think about decarbonizing your life — or just skip ahead to our recommendations, below.