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Houston energy expert asks: Who pays when AI outruns the power grid?

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Scotty Nyquist discuss the growth in AI data centers and the strain on the system. Photo via HARC report

For most of the past 20 years, U.S. electricity policy relied on predictable trends in demand. Electricity use, in most regions, increased gradually, forecasts were stable, and utilities adjusted the system in small steps. Power plants, transmission lines, and substations were generally added to reflect shifts in load, rather than growth, and costs were recovered through modest adjustments to customer bills.

Growth in AI data centers has disrupted this model. A single facility can add as much electricity demand as a small town. That demand comes all at once, runs continuously, and has little tolerance for outages. If electricity service drops even briefly, computation stops, and services shut down. Ironically, data centers need reliable service, a point that their emergence is driving concern around for the rest of the grid.

What the numbers say

The International Energy Agency projects global electricity consumption from data centers to double by 2030, reaching roughly 945 TWh, nearly 3 percent of global electricity demand, with consumption growing about 15 percent per year this decade. McKinsey projects that U.S. data center demand alone could grow 20–25 percent per year, with global capacity demand more than tripling by 2030.

After years of roughly 0.5 percent annual demand growth, many forecasts now place total U.S. electricity demand growth closer to 2–3 percent per year through the mid-2030s, with much higher growth in specific regions. In Texas, some forecasters are saying electricity demand could double over the next five years, a staggering 10 percent per year growth rate. What sounds incremental on paper translates into a major challenge on the ground. Meeting this pace of growth is estimated to require $250–$300 billion per year in grid investment, about double what the system has been absorbing.

Where the system starts to strain

The strain appears first in the interconnection queue. It shows up as long waits, backlogs, and delays for connecting new loads and new generation.

Before new generators or large load customers can be connected, a study is required to assess their impact on the grid, whether it can physically handle the added load, and whether upgrades are required. With AI-driven data centers, utilities face far more connection requests than they can realistically support. In ERCOT, large-load interconnection requests exceed 200 gigawatts, most tied to data centers. That amount exceeds historical norms, and it is several times larger than what can be practically studied or built in the near term.

To be clear, public utility commissions are required to study these requests because they must manage system capabilities to ensure minimal disruption. This means engineers spend time evaluating projects that may never be built, while other more commercially viable projects may wait longer for approvals. This extends timelines and makes infrastructure planning less reliable.

Why policymakers are rethinking the rules

Utilities and their regulators must decide how much generation, transmission, and substation capacity to build years before it comes online. Those decisions are based on expected demand at the time projects are approved. When it comes to data centers, by the time infrastructure is completed, they may end up deploying newer, more efficient chips that use less power than originally assumed. This can result in grid infrastructure built for a higher load than what actually materializes, leaving excess capacity that still must be paid for through system-wide rates.

That’s the central dilemma. If utilities build too little capacity, the system operates with less reserve margin. During periods of grid stress, operators have fewer options, increasing the likelihood of curtailments or outages. However, if utilities build too much, customers may be asked to pay for infrastructure that is not fully used.

In response, policymakers are adjusting the rules. In some regions, regulators are moving toward bring-your-own-power approaches that require large data centers to supply or fund part of the capacity needed to serve them or reduce demand during system stress. At the federal level, permitting reforms tied to datacenter infrastructure increasingly treat electricity as a strategic economic input.

As Ken Medlock, senior director at the Baker Institute Center for Energy Studies (CES), explains:

“Many of the planned data centers are now also adding behind-the-meter options to their development plans because they do not anticipate being able to manage their needs solely from the grid, and they certainly cannot do so with only intermittent power sources.”

Behind-the-meter (BTM) refers to power that a consumer controls on its side of the utility meter, such as on-site gas generation or a dedicated power plant. These resources allow data centers to keep operating during grid-related service. Most facilities remain connected to the grid, but the backup BTM generation serves as insurance for operating their core business.

This shifts responsibility. Utilities traditionally manage reliability across all customers by maintaining an operating reserve margin, or spare capacity. Increasingly, large-load customers manage part of their own electricity reliability needs, which changes how infrastructure is planned and how risk is distributed.

Bottom line

AI-driven load growth is arriving faster and in more concentrated places than the power system was built to accommodate. Utilities and regulators are being forced to make decisions sooner than planned about where to build, how fast to build, and which customers get priority when capacity is limited. The effects extend beyond data centers, showing up in system costs, reliability margins, competition for grid access, and pressure on communities and industries that depend on affordable and dependable power. The issue is not whether electricity can be generated, but how the costs and risks of rapid demand growth are distributed as the system tries to keep up. How regulators balance these decisions will determine who pays as AI demand outruns the power grid.

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Scott Nyquist is a senior advisor at McKinsey & Company and vice chairman, Houston Energy Transition Initiative of the Greater Houston Partnership. The views expressed herein are Nyquist's own and not those of McKinsey & Company or of the Greater Houston Partnership. This article originally appeared on LinkedIn.

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Collide has rolled out RIGGS, a large language model for energy professionals. Photo via Getty Images

Houston AI startup rolls out platform to reshape oil and gas workflows

AI for energy

Houston-based Collide is looking to solve AI issues in the energy industry from within.

Co-founded by former oil roughneck Collin McLelland, the company has developed AI software for operators and field teams, shaped by firsthand oilfield experience. Its AI-native platform “retrieves and synthesizes data from authoritative sources to deliver accurate, cited, and energy-focused insights to oil and gas professionals,” according to the company.

“Oil and gas has a graveyard full of technology that was technically impressive and operationally useless,” McLelland tells Energy Capital. “The reason is almost always the same: the people who built it didn't understand what they were actually solving for. When you're an outsider, you see workflows and try to automate them. When you're an insider, you understand why those workflows exist—the regulatory constraints, the physical realities, the liability concerns, the trust dynamics between operators and service companies.”

Collide’s large language model, known as RIGGS, performed well in recent benchmarking results when taking a standardized petroleum engineering (SPE) exam, the company reports. The exam assesses understanding from conceptual terminology to complex mathematical problem-solving.

According to Collide, RIGGS achieved a score of 67.5 percent on a 40-question subset of the SPE petroleum engineering exam, outperforming other large language models like Grok 4 (62.5 percent), Claude Sonnet 4.5 (52.5 percent) and GPT 5.1 (4 percent).

RIGGS completed the test in 15 minutes, while Grok took two hours. Collide hopes over the next few months, RIGGS will receive a score between 75 percent to 80 percent accuracy.

The software could potentially help oil and gas companies produce accurate outputs and automate trivial workflows, which can open up valuable time for engineers and teams to work on other pressing matters, according to McLelland.

“Collide exists because we sat in those seats — we were the engineers, the operators, the field guys,” he says. ”RIGGS scoring higher on the PE exam versus the frontier labs isn't a party trick. It's evidence that the model understands petroleum engineering the way a petroleum engineer does, because it was built by people who do.”

RIGGS was trained on Collide’s Spindletop hardware and is supported by a vast library of information, as well as a reasoning engine and validation layer that uses logic to solve problems.

“Longer term, we see RIGGS as the intelligence layer that sits underneath every operator's workflow — not a chatbot you open in a browser, but something embedded in the tools engineers already use,” McLelland says. “The goal is to give every engineer the knowledge and pattern recognition of a 30-year veteran, on demand."

According to McLelland, Collide is already building toward reservoir analysis and production optimization, automated regulatory compliance (Railroad Commission filings, W-10s, G-10s), workover report generation, and engineering decision support in the field for near-term use cases. In March, Collide and Texas-based oil and gas operator Winn Resources announced a collaboration to automate the time-intensive process of filing monthly W-10 and G-10 forms with the Texas Railroad Commission, completing what’s normally a multi-hour task in under 30 minutes. Collide reports that Winn’s infrastructure now automates regulatory filings and provides real-time visibility into data gaps, which has reduced processing time by over 95 percent.

“Before Collide, I'd spend hours manually keying in filings,” Buck Crum, director of operations, said in a news release. “(In March), we had 50 wells to file and I was done in 20 minutes. It does the majority of the heavy lifting while keeping me in control. That human-in-the-loop approach saves meaningful time and gives us greater confidence in our compliance and reporting.”

Collide was originally launched by Houston media organization Digital Wildcatters as “a professional network and digital community for technical discussions and knowledge sharing.” After raising $5 million in seed funding led by Houston’s Mercury Fund last year, the company said it would shift its focus to rolling out its enterprise-level, AI-enabled solution.
This are heating up for Fervo. Photo via Fervo Energy

Fervo taps new geothermal site and more energy transition news to know

Trending Topics

Editor's note: We're looking back at the biggest energy transition headlines from the second half of February, including Fervo's hottest well to date and the future of data centers in Texas. Below are the five most-read EnergyCapital stories from February 16-28, 2026.

1. Fervo taps into its hottest-ever geothermal reservoir

Fervo Energy has unlocked multigigawatt potential from a new geothermal energy site. Photo courtesy Fervo Energy.

Things are heating up at Houston-based geothermal power company Fervo Energy. Fervo recently drilled its hottest well so far at a new geothermal site in western Utah. Fewer than 11 days of drilling more than 11,000 feet deep at Project Blanford showed temperatures above 555 degrees Fahrenheit, which exceeds requirements for commercial viability. Fervo used proprietary AI-driven analytics for the test. Continue reading.

2. Texas could topple Virginia as biggest data-center market by 2030, JLL report says

A new report shows the role Texas could play as the data-center sector enters "hyperdrive." Photo via JLL.com.

Everything’s bigger in Texas, they say—and that phrase now applies to the state’s growing data-center presence. A new report from commercial real estate services provider JLL says Texas could overtake Northern Virginia as the world’s largest data-center market by 2030. Northern Virginia is a longtime holder of that title. Continue reading.

3. Texas claims No. 1 spot on new energy resilience report

Texas outpaced the rest of the country in a new energy resilience report, despite grid challenges and rising AI demand. Photo courtesy of ERCOT

A new report by mineral group Texas Royalty Brokers ranks Texas as the No. 1 most energy-resilient state. The study focused on four main sources of electricity in hydroelectric dams, natural gas plants, nuclear reactors and petroleum facilities. Each state was given an Energy Resilience Score based on size and diversity of its power infrastructure, energy production and affordability for residents. Continue reading.

4. Texas' oil and gas foundation could boost its geothermal future, UH says

A new UH white paper says that Texas is poised to lead advanced geothermal due to its oil and gas skills and capacity. Photo via UH.edu.

Equipped with the proper policies and investments, Texas could capitalize on its oil and gas infrastructure and expertise to lead the U.S. in development of advanced geothermal power, a new University of Houston white paper says. Continue reading.

5. HETI leader reflects on four years focused on the energy transition

Jane Stricker reflects on four years at HETI. Courtesy photo

It’s hard to believe only four years have passed since I joined the Greater Houston Partnership to lead the Houston Energy Transition Initiative. We talk about COVID years feeling simultaneously like just yesterday and a lifetime ago, and my time at HETI feels quite similar. The energy and climate landscape has evolved dramatically over the last few years, but one constant has endured…Houston remains at the heart of the energy industry. Continue reading.

Merab Momen, founder of AI CTO Services. Courtesy Photo

How this Houston expert helps startups turn AI hype into real impact

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Artificial intelligence is now everywhere. It is mentioned in every startup pitch deck, and every corporate roadmap claims to use it. However, many early-stage businesses struggle with the simple question, “What does AI actually mean for my business?”

In a recent podcast episode of EnergyTech Startups, Merab Momen, founder of AI CTO Services and a long time AI practitioner, explains why most founders misunderstand AI, how startups can practically apply it and why Houston is quietly becoming a serious hub for AI-driven innovation.

Filling the AI Leadership Gap

Merab’s career has spanned decades of technology transitions. He worked on neutral networks in the 1990s, constructed computer vision systems long before they were common, and helped install AI solutions inside huge industrial companies. However, he noticed a huge problem when generative AI started to explode into the mainstream-The requirement of a real partner by the founders for AI integration but inability to rely on a full-time CTO and project-based consultants.

“I really needed something which is much more engaging where I can give that partner-level advice to the founders,” he said. By giving firms on-demand access to high-level AI knowledge and expertise, his methodology enables them to analyse tools, steer clear of cost blunders and eventually transition to a permanent technology leader when the time is right.

AI is Older than Most People Think

Despite its recent rise in popularity, AI is nothing new. AI actually began in the 1950s. Merab in his conversation explained how he worked on his first AI project back in the year 1996 that worked perfectly, but the processing power wasn’t just there to make it practical. He continued how he utilized the swarm intelligence models to optimize supply chains, now referred to as MLPOs and data engineering.

From Language Models to Physical World

Much of the public conversation about AI revolves around chatbots and text generation. But Merab sees far greater potential in AI’s interaction with the physical world, especially in industrial settings. He emphasized edge computing and vision language models (VLMs) as significant advances in manufacturing and energy. This physical shift is opening doors for new opportunities for robotics, automated inspections, and industrial safety applications. Merab added that Houston is uniquely positioned for this transition.

Why Houston has an AI Advantage

Silicon Valley may dominate the AI headlines, but Merab believes Houston’s advantage lies beneath the surface. The city doesn’t lag in AI utilization; it just operates in industries where results show differently.

Machine learning isn’t new to Houston’s core industries. Energy companies, manufacturers, logistics providers, and healthcare systems have been using advanced analytics for decades. The difference lies in them innovating in industrial sectors rather than consumer technology.

What’s Next

With the AI CTO Services growing, Merab is working with startups across industries to deploy AI in practical, business-first ways.

He is more interested in assisting founders in finding answers to critical issues than following new trends.

For Houston’s energy and climate tech community, it needs to transform AI enthusiasm into real-world impact.

Listen to the full conversation with Mehrab Momin on the Energy Tech Startups Podcast to learn more.

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Energy Tech Startups Podcast is hosted by Jason Ethier and Nada Ahmed. It delves into Houston's pivotal role in the energy transition, spotlighting entrepreneurs and industry leaders shaping a low-carbon future.


A new report shows the role Texas could play as the data-center sector enters "hyperdrive." Photo via JLL.com.

Texas could topple Virginia as biggest data-center market by 2030, JLL report says

data analysis

Everything’s bigger in Texas, they say—and that phrase now applies to the state’s growing data-center presence.

A new report from commercial real estate services provider JLL says Texas could overtake Northern Virginia as the world’s largest data-center market by 2030. Northern Virginia is a longtime holder of that title.

What’s driving Texas’ increasingly larger role in the data-center market? The key factor is artificial intelligence.

Companies like Google and Microsoft need more energy-hungry data centers to power AI innovations. In a 2023 article, Forbes explained that AI models consume a lot of energy because of the massive amount of data used to train them, as well as the complexity of those models and the rising volume of tasks assigned to AI.

“The data-center sector has officially entered hyperdrive,” Andy Cvengros, executive managing director at JLL and co-leader of its U.S. data-center business, said in the report. “Record-low vacancy sustained over two consecutive years provides compelling evidence against bubble concerns, especially when nearly all our massive construction pipeline is already pre-committed by investment-grade tenants.”

Dallas-Fort Worth has long dominated the Texas data-center market. But in recent years, West Texas has emerged as a popular territory for building data-center campuses, thanks in large part to an abundance of land and energy. Nearly two-thirds of data-center construction underway now is happening in “frontier markets” like West Texas, Ohio, Tennessee and Wisconsin, the JLL report says.

Northern Virginia, the current data-center champ in the U.S., boasted a data-center market with 6,315 megawatts of capacity at the end of 2025, the report says. That compares with 2,423 megawatts in Dallas-Fort Worth, 1,700 megawatts in the Austin-San Antonio corridor, 200 megawatts in West Texas, and 164 megawatts in Houston.

UH researchers have developed a thin film that could allow AI chips to run cooler and faster. Photo courtesy University of Houston.

Houston researchers develop energy-efficient film for AI chips

AI research

A team of researchers at the University of Houston has developed an innovative thin-film material that they believe will make AI devices faster and more energy efficient.

AI data centers consume massive amounts of electricity and use large cooling systems to operate, adding a strain on overall energy consumption.

“AI has made our energy needs explode,” Alamgir Karim, Dow Chair and Welch Foundation Professor at the William A. Brookshire Department of Chemical and Biomolecular Engineering at UH, explained in a news release. “Many AI data centers employ vast cooling systems that consume large amounts of electricity to keep the thousands of servers with integrated circuit chips running optimally at low temperatures to maintain high data processing speed, have shorter response time and extend chip lifetime.”

In a report recently published in ACS Nano, Karim and a team of researchers introduced a specialized two-dimensional thin film dielectric, or electric insulator. The film, which does not store electricity, could be used to replace traditional, heat-generating components in integrated circuit chips, which are essential hardware powering AI.

The thinner film material aims to reduce the significant energy cost and heat produced by the high-performance computing necessary for AI.

Karim and his former doctoral student, Maninderjeet Singh, used Nobel prize-winning organic framework materials to develop the film. Singh, now a postdoctoral researcher at Columbia University, developed the materials during his doctoral training at UH, along with Devin Shaffer, a UH professor of civil engineering, and doctoral student Erin Schroeder.

Their study shows that dielectrics with high permittivity (high-k) store more electrical energy and dissipate more energy as heat than those with low-k materials. Karim focused on low-k materials made from light elements, like carbon, that would allow chips to run cooler and faster.

The team then created new materials with carbon and other light elements, forming covalently bonded sheetlike films with highly porous crystalline structures using a process known as synthetic interfacial polymerization. Then they studied their electronic properties and applications in devices.

According to the report, the film was suitable for high-voltage, high-power devices while maintaining thermal stability at elevated operating temperatures.

“These next-generation materials are expected to boost the performance of AI and conventional electronics devices significantly,” Singh added in the release.

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This article originally appeared on our sister site, InnovationMap.

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The latest Houston energy breakthroughs + more top headlines for June

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Editor's note: June brings exciting news in the energy transition sector, from major milestones in clean energy production for Cemvita and Merichem to the release of the 2026 Fortune 500 list. Below are the five most-read stories published on EnergyCapitalHTX from June 1-14, 2026:

1. Houston startup strikes deal to develop hydrogen production plant in Canada

Houston-based cleantech startup Vema Hydrogen has reached a tentative agreement with Canada-based CHARBONE Corp. to develop a hydrogen production and processing plant in Québec. The deal would couple Vema’s production of engineered mineral hydrogen with CHARBONE’s purification, compression and distribution capabilities. Engineered mineral hydrogen, also known as orange hydrogen, is produced underground by accelerating naturally occurring geochemical reactions in iron-rich rock formations. Continue reading.

2. Cemvita reaches breakthrough in sustainable fuel feedstock production

Houston-based biotech company Cemvita announced that it recently reached a critical milestone in the development of its FermOil product, which can be used to create Sustainable Aviation Fuel (SAF) and other renewable fuels at industrial scale. The company completed a 75,000-liter industrial fermentation run at Belgium's Bio Base Europe Pilot Plant. The campaign achieved target technical metrics for the production of FermOil, Cemvita’s renewable natural oil (RNO). Continue reading.

3. Houston chemical co. completes successful field trial of cleaner natural gas processing tech

Houston-based Merichem Technologies has announced successful results from the field trial of its new hydrogen sulfide (H2S) removal technology in the Permian Basin. The technology, known as ECOTREAT, removed more than 99 percent of hydrogen sulfide gas from natural gas streams, or “sour gas,” without producing solid waste during the month-long trial. It also showed sustained performance even when operating above the unit’s design capacity. Continue reading.

4. 6+ must-attend Houston energy transition events for June 2026

Editor's note: Summer is here, and June brings a slate of must-attend events for those in the energy transition sector. The month continues with EPC Show and InnovateEnergy Week. Mark your calendars and register now. Continue reading.

5. Houston lands 27 Fortune 500 headquarters, led by energy heavyweights

Houston is a giant among U.S. hubs for corporate headquarters. The 2026 Fortune 500 lists 27 companies based in the Houston area, with many energy companies claiming top spots. Houston ties with Chicago for the second-most Fortune 500 headquarters, preceded only by New York City (53). Dallas-Fort Worth is home to 23 Fortune 500 headquarters. Texas leads the nation for Fortune 500 headquarters (57), with California in the No. 2 spot and New York at No. 3. Continue reading.

Japanese company plans $357M solar manufacturing plant in Houston area

coming soon

Japanese solar manufacturing company TOYO Co. Ltd. plans to invest $357 million to bring a 1.5-gigwatt solar cell manufacturing facility to the Houston area.

TOYO’s latest state-of-the-art facility will be co-located at its existing solar module site in Humble, according to a news release from the company. It will produce heterojunction (HJT) solar cells, which are known to be more durable and efficient with a higher heat threshold.

TOYO reports that the new facility will create 400 full-time manufacturing jobs. The project is expected to be completed in 20 months, which includes an initial pilot production.

"Expanding into domestic cell manufacturing is the natural next step in our commitment to creating an integrated onshore solar supply chain from polysilicon to panels," Takahiko Onozuka, chairman and CEO of TOYO, said in the news release. "Co-locating 1.5 GW of HJT cell capacity at our Houston module site significantly optimizes our capital allocation and infrastructure spend.”

TOYO entered the Houston market in 2024 through its acquisition of a majority stake in Solar Plus Technology Texas LLC.

Earlier this year, it began producing solar modules at its 567,140-square-foot plant in Lovett Industrial’s Nexus North Logistics Park. At the time, the company said it planned to expand manufacturing capacity to 6.5 gigawatts.

"The new cell plant reflects TOYO's long-term strategy to build a fully FEOC-compliant domestic manufacturing platform focused on serving the needs of the U.S. utility-scale solar market," Rhone Resch, TOYO's chief strategy officer, added in the release. "By producing premium solar products in the United States, we will be well positioned to meet the market's evolving domestic content requirements while strengthening supply chain security and reliability. Looking ahead, we believe HJT is the optimal technology platform for integrating next-generation perovskite solar cells, which we expect will drive the next major advancement in solar conversion efficiency and support TOYO's long-term technology roadmap.”

New survey reveals concerns over AI data center growth in Houston

data findings

A new report out of the University of Houston shows that area residents remain wary of the long-term effects of operating data centers.

The recent survey from the University of Houston’s latest SPACE City Panel, conducted by the Center for Public Policy at the Hobby School of Public Affairs, shows that while 85 percent of Houston-area residents use AI, nearly 63 percent oppose the construction of AI data centers within 1 mile of their homes.

Respondents’ concerns centered around data centers’ high energy demand and the area’s power grid reliability. According to the survey, 32 percent of residents who oppose local data center projects would be more likely to support the centers if they relied on renewable energy over fossil fuels.

“Respondents understand that AI can bring economic and educational benefits, but they are also concerned about the physical infrastructure needed to fuel AI, especially data centers,” Soran Mohtadi, post-doctoral fellow at the Hobby School and a researcher on the report, said in a news release. “This physical infrastructure demands more electricity and water, leading to environmental impacts.”

Experts estimate that 6.5 gigawatts of data center capacity will be added to the Texas grid by 2030. And Houston’s data center capacity is predicted to more than double by 2028.

The Electric Reliability Council of Texas also projects electricity demand could reach 218 gigawatts by 2031, which would be more than double the record peak set in August 2023. Data centers are expected to account for 86 gigawatts of that new demand.

Survey respondents also said they are concerned about the state's future water supply, given the large amounts of water that data centers need to stay cool.

In terms of who’s responsible for that issue, 57.6 percent of respondents said they put the onus on Texas lawmakers, while 31.5 percent say tech companies should be responsible.

Additionally, more than 75 percent of respondents believed that data center developers and technology companies—not residents—should bear the cost of infrastructure upgrades to support data centers.

“Every decision legislators make has implications on residents’ everyday lives and local infrastructure now and in the future,” Maria P. Perez Arguelles, lead researcher on the report and research assistant professor at the Hobby School, added in the news release. “This issue is going to become more important in years to come, so this is just the beginning.”

Read the full report here.

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This article originally appeared on our sister site, EnergyCapitalHTX.com.

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