AI technology behind ChatGPT was built in Iowa — with lots of water – Morganton News Herald

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DES MOINES, Iowa — The cost of building an artificial intelligence product like ChatGPT can be hard to measure.
But one thing Microsoft-backed OpenAI needed for its technology was plenty of water, pulled from the watershed of the Raccoon and Des Moines rivers in central Iowa to cool a powerful supercomputer as it helped teach its AI systems how to mimic human writing.
As they race to capitalize on a craze for generative AI, leading tech developers including Microsoft, OpenAI and Google acknowledged that growing demand for their AI tools carries hefty costs, from expensive semiconductors to an increase in water consumption.
They’re often secretive about the specifics. Few people in Iowa knew about its status as a birthplace of OpenAI’s most advanced large language model, GPT-4, before a top Microsoft executive said in a speech it “was literally made next to cornfields west of Des Moines.”
Vehicles on Interstate 35 pass a Microsoft data center Sept. 5 in West Des Moines, Iowa.
Building a large language model requires analyzing patterns across a huge trove of human-written text. All of that computing takes a lot of electricity and generates a lot of heat. To keep it cool on hot days, data centers need to pump in water — often to a cooling tower outside its warehouse-sized buildings.
In its latest environmental report, Microsoft disclosed that its global water consumption spiked 34% from 2021 to 2022 to nearly 1.7 billion gallons, or more than 2,500 Olympic-sized swimming pools. That’s a sharp increase compared to previous years that outside researchers tie to its AI research.
“It’s fair to say the majority of the growth is due to AI,” including “its heavy investment in generative AI and partnership with OpenAI,” said Shaolei Ren, a researcher at the University of California, Riverside, who has been trying to calculate the environmental impact of generative AI products such as ChatGPT.
In a paper due to be published later this year, Ren’s team estimates ChatGPT gulps up 500 milliliters of water — close to what’s in a 16-ounce water bottle — every time you ask it a series of between 5 to 50 prompts or questions. The range varies depending on where its servers are located and the season. The estimate includes indirect water usage that the companies don’t measure — such as to cool power plants that supply the data centers with electricity.
“Most people are not aware of the resource usage underlying ChatGPT,” Ren said. “If you’re not aware of the resource usage, then there’s no way that we can help conserve the resources.”
Google reported a 20% growth in water use in the same period, which Ren also largely attributes to its AI work. Google’s spike wasn’t uniform — it was steady in Oregon, where its water use attracted public attention, while doubling outside Las Vegas. It was also thirsty in Iowa, drawing more potable water to its Council Bluffs data centers than anywhere else.
Microsoft said this past week it is investing in research to measure AI’s energy and carbon footprint “while working on ways to make large systems more efficient, in both training and application.”

“We will continue to monitor our emissions, accelerate progress while increasing our use of clean energy to power data centers, purchasing renewable energy, and other efforts to meet our sustainability goals of being carbon negative, water positive and zero waste by 2030,” the company said.
OpenAI echoed those comments in its own statement, saying it’s giving “considerable thought” to the best use of computing power. “We recognize training large models can be energy and water-intensive” and work to improve efficiencies, it said.
A Microsoft data center on Sept. 5 near Interstate 35 in West Des Moines, Iowa.
Microsoft made its first $1 billion investment in San Francisco-based OpenAI in 2019, more than two years before the startup introduced ChatGPT and sparked worldwide fascination with AI advancements. As part of the deal, the software giant would supply computing power needed to train the AI models.
The two companies looked to West Des Moines, Iowa, a city of 68,000 people where Microsoft amassed data centers to power its cloud computing services for more than a decade. Its fourth and fifth data centers are due to open there later this year.
Steve Gaer, who was the city’s mayor when Microsoft came to town, said the company was attracted to the city’s commitment to building public infrastructure and contributed a “staggering” sum of money through tax payments that support that investment.
Microsoft first said it was developing one of the world’s most powerful supercomputers for OpenAI in 2020, declining to reveal its location at the time but describing it as a “single system” with more than 285,000 cores of conventional semiconductors, and 10,000 graphics processors — a kind of chip crucial to AI workloads.
Experts said it can make sense to “pretrain” an AI model at a single location because of the large amounts of data that need to be transferred between computing cores.
It wasn’t until late May that Microsoft’s president, Brad Smith, disclosed that it built its “advanced AI supercomputing data center” in Iowa, exclusively to enable OpenAI to train what has become its fourth-generation model, GPT-4. The model now powers premium versions of ChatGPT and some of Microsoft’s own products.
“It was made by these extraordinary engineers in California, but it was really made in Iowa,” Smith said.
In some ways, West Des Moines is a relatively efficient place to train a powerful AI system, especially compared to Microsoft’s data centers in Arizona that consume far more water for the same computing demand.
For much of the year, Iowa’s weather is cool enough for Microsoft to use outside air to keep the supercomputer running properly and vent heat out of the building. Only when the temperature exceeds about 85 degrees Fahrenheit does it draw water, the company said in a public disclosure.
Are the robots taking over, or is AI just hype? Although different sectors of the economy have been using AI for years, everyone’s talking about AI these days. The hype is partly due to the public release of ChatGPT, which has allowed people to use AI in their daily lives and understand how it can better help them.
One key thread running through this topic is how AI will change the world of work, but that can only happen with widespread AI adoption. Magnifi, an AI investing platform, analyzed data from McKinsey and Stanford University’s Institute for Human-Centered Artificial Intelligence to illustrate how AI has been deployed across the economy over the last year and its implications for individual businesses. All industry adoption rates are year-over-year changes based on responses from individual companies surveyed within those industries detailing how they’re adopting AI and for what functions.
Across all industries, American firms reported a 2 percentage-point increase in adoption of AI technologies in 2022 compared to 2021, according to McKinsey survey data. Strategy and corporate finance led all other functions for adoption across all industries in 2022, which could be symbolic of the difficult economic conditions that surfaced in the last year, forcing companies to tighten belts and sometimes lay off staff.
While industry adoption may be increasing, not every company has hopped on the AI bandwagon—just over half of companies are using AI, according to McKinsey.
Those that aren’t adopting AI could find themselves at a competitive disadvantage. According to Michael Chui, partner at McKinsey Global Institute, companies embracing AI and committing to building their capabilities will benefit from cost savings and increased revenues.

Companies leverage AI in numerous ways, and according to McKinsey’s survey, companies have increased the number of AI tools they’ve deployed on average from 1.9 in 2018 to 3.8 in 2022.
The most popular tool is robotic process automation, or software capable of doing repetitive tasks, used by nearly 2 in 5 companies. Thirty-four percent of companies use computer vision, a field of AI that understands and can extract data from visual input like images and video.
Rounding out the top four capabilities, at 33% implementation, are natural-language text understanding and virtual agents and conversational interfaces. These two fields could become more popular as the AI models get more robust. For example, OpenAI’s GPT-3, released in June 2020, was trained on about 100 times more data than its GPT-2, released a year earlier. And GPT-4, released in March 2023, was reportedly trained on at least 10 times more data than that.
Consumer goods and retail companies are finding more ways to use AI within their strategy and corporate finance functions, which could help them be more competitive. McKinsey found that, across all industries, 43% of strategy and corporate finance functions discovered AI helped them lower costs, with 31% achieving a decrease of over 10%.
On the revenue side, 65% of strategy and corporate finance functions saw revenue increases, with 41% achieving nearly a 5% increase. In one example of how AI helps companies strategize, Ananda Chakravarty, vice president of research at International Data Corporation, told The Washington Post that AI’s power to crawl through large amounts of data helps retailers track, set, and forecast prices, making them more competitive.
One of AI’s strengths is its ability to sift through and process mass amounts of data. For tech and telecom companies, this can help them assess and manage risk by quickly detecting cybersecurity threats and data breaches and mitigating them.
But information technology professionals also worry about potential AI weaponization. A 2023 BlackBerry survey found that over half of IT professionals believe AI could assist in successful cyberattacks. That’s driving the sectors’ investment in AI tools to manage risk. BlackBerry found that at least 4 in 5 IT decision-makers plan to adopt more AI-driven cybersecurity tools.
From 2021 to 2022, financial service companies focused their AI adoption strategies on tools that would help expand their product offerings and improve customer experience.
While it could take years for companies to launch new products, some banks are already talking about how they’re integrating AI.
In March 2023, The Washington Post reported that the Royal Bank of Canada could use AI to quickly write or find existing code developers can use to create new products. CNBC also reported Goldman Sachs was testing AI to speed up the coding process and JPMorgan Chase’s development of an AI-based consumer product to help investors optimize their personal investment portfolio.
Business, legal, and professional services companies are putting more money into ways AI can optimize strategy and accounting. Still, they have decreased their investments in marketing and sales AI tools by 19%. A June 2023 Thomson Reuters study found that while nearly 4 in 5 responding professional services firms thought AI could help their business operations, only 4% were actually using it.
Not helping AI’s case was the hot water two New York attorneys found themselves in after discovering that a legal brief they submitted in court included fictitious cases generated by ChatGPT. The two were sanctioned in court and ordered to pay a $5,000 fine. However, that incident hasn’t deterred some firms from taking the AI plunge: Accounting firm PricewaterhouseCoopers announced in 2023 it was using AI in its legal department and plans to find ways for its accountants to use it too.
AI has been transforming the health care and pharmaceutical industries for several years. Johnson & Johnson and Moderna even leveraged AI tools to develop their COVID-19 vaccines.
Generative AI is helping doctors process their patient documentation more quickly. AI can also quickly analyze patient and insurance claims data, but companies must ensure patient privacy and data remain secure. Damian Chung, business information security officer at Netskope, told that health care companies face risk in third-party AI tools learning from their data and using it for other customers.
In terms of increasing revenues, companies are getting the most bang for their buck when using AI in product development, marketing, and sales functions. McKinsey’s 2022 AI survey found that 7 in 10 respondents earned more money using AI in these functional areas. AI tools are helping companies quickly analyze customer buying habits and create more customized marketing messages.
AI can also shorten product development cycles. In one example, PepsiCo Chief Strategy and Transformation Officer Athina Kanioura told that AI has shortened the company’s product development cycle from years to months because it can quickly analyze consumer trends. The analysis led the company to create a new seaweed snack in less than a year.
Data reporting by Dom DiFurio. Story editing by Jeff Inglis. Copy editing by Paris Close. Photo selection by Abigail Renaud.
This story originally appeared on Magnifi and was produced and distributed in partnership with Stacker Studio.
Get the latest local business news delivered FREE to your inbox weekly.
Zain Asher speaks to Time Magazine’s CEO Sam Jacobs about the TIME100 AI List of artificial intelligence innovators.

Vehicles on Interstate 35 pass a Microsoft data center Sept. 5 in West Des Moines, Iowa.
A Microsoft data center on Sept. 5 near Interstate 35 in West Des Moines, Iowa.
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