Tools & Platforms
EPA IT chief’s warning: AI can’t be used ‘to solve any problem’
Like most of its government peers, the Environmental Protection Agency has embraced artificial intelligence and filled its federally required inventory with more than a dozen use cases. But the emerging technology shouldn’t be mistaken for a cure-all, the agency’s new IT chief warned Tuesday.
Carter Farmer, who took over as the EPA’s chief information officer in May after seven-plus years in IT systems roles at the U.S. Institute of Peace, said during a FedInsider webinar that he’s observed a tendency in organizations to “jump straight” to AI to “solve any problem.”
“They just jump in there without asking the right questions first,” Farmer said. “Many times, the solution or the problem you’re trying to solve doesn’t need AI.”
Looking for quick fixes via AI without interrogating the plusses and minuses first “can actually slow the process down,” he added, especially if tech leaders have overlooked a more straightforward — and cheaper — way to attack the problem.
“If you don’t ask those questions up front, you can go down a road pretty far and … [then have to] reverse and go back and figure out where you should have gone down first,” Farmer said.
The EPA CIO’s comments on “hyped up” technologies come at a time when the Trump administration is pushing agencies to largely continue the Biden White House’s AI use case reporting protocols, albeit with some key differences.
In an Office of Management and Budget document released last week, the administration detailed an AI reporting process that requires agencies to provide much of the same information called for in rescinded Biden-era guidance, but also eliminates a handful of data collection categories and pares down others, including some involving risk management practices.
The new OMB AI guidance wasn’t covered during Tuesday’s webinar, but Farmer spoke at length about the need for agency IT leaders to treat data as “the backbone of what we do when we build systems.”
“The most critical part of this whole situation, especially when using AI and a lot of advanced technology, is you need to document how the data was used to define [an] outcome, and it’s got to be repeated,” Farmer said. “Someone’s got to be able to take that data, follow your methodology, and come to the same conclusion.”
For the EPA, following the data goes hand-in-hand with “finding the actual best use cases where AI can be best applied,” Farmer noted. He shared an example of the agency’s use of AI to categorize and summarize public comments on proposed rulemaking.
The EPA has historically used contractors to sift through the hundreds of thousands of comments often submitted to the agency, Farmer said, amounting to a monthslong process. But with the development of an in-house tool that leverages AI, the agency will be able to plug comments from regulations.gov into a system that delivers synthesized information to an EPA employee who can quickly review and interpret the results.
“It provides opportunity to significantly improve our processes … while still remaining transparent to the public,” Farmer said. “Having a human in the process … is very important, and also being transparent to the public is just as important.”
Farmer said he’s looking down the road to agentic AI while keeping in mind the “hive mind” mentality that can take hold when dealing with new technologies. And as a newcomer to the EPA and the CIO role, he’s still focused on longheld, data-centered IT priorities and how they align with his overarching transparency goals.
“Many times people think that modernization is going to lead to less transparency,” he said, “when in real-world processes and outcomes, you actually see more transparency and the ability to actually give you more data back than you ever had before.”
Tools & Platforms
“Elon Musk Unleashes the Colossus!”: World’s Most Powerful AI Supercomputer Dwarfs All Rivals and Sparks Panic in the Global Tech Community
| IN A NUTSHELL |
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Elon Musk’s relentless pursuit of AI supremacy has taken a monumental step forward with the introduction of Colossus, a groundbreaking supercomputer. Boasting an astounding 100,000 Nvidia H100 GPUs, this AI powerhouse promises to redefine the landscape of artificial intelligence. As xAI, Musk’s brainchild, plans to enhance Colossus with an additional 100,000 GPUs, including the cutting-edge H200 chips, the stakes in the AI race have never been higher. This bold move is not merely a technological feat but a statement of intent, as Musk aims to outpace rivals such as OpenAI and Meta, cementing his place at the forefront of AI innovation.
The Birth of Colossus: A Supercomputer Like No Other
Launched in a mere four months, Colossus stands as a testament to the rapid advancements in AI technology spearheaded by Elon Musk and his team at xAI. Unlike other AI clusters, Colossus integrates its vast number of GPUs into a singular, cohesive system, allowing for unparalleled performance and efficiency. This supercomputer will serve as the training ground for xAI’s next-generation large language models (LLMs), including the upcoming Grok-3, which is poised to challenge OpenAI’s GPT-4 by December.
Elon Musk, ever the visionary, took to his social media platform, X (formerly Twitter), to laud the efforts of his team and partners. “Excellent work by the team, Nvidia, and our many partners/suppliers,” Musk declared, highlighting the collaborative nature of this monumental achievement. The creation of Colossus is not just a milestone for xAI but a significant leap for the entire AI industry, pushing the boundaries of what is possible.
Partnerships and Power: Behind the Scenes of Colossus
Colossus’s creation was made possible through strategic partnerships with industry leaders such as Dell Technologies and Super Micro Computer. Michael Dell, CEO of Dell Technologies, expressed immense pride in contributing to this groundbreaking project. Furthermore, xAI’s financial prowess was bolstered by a substantial $6 billion Series B funding round, led by top investors like Andreessen Horowitz and Sequoia Capital, elevating its valuation to an impressive $24 billion.
However, the supercomputer’s immense power requirements have sparked controversy. Environmental advocates in Memphis, Tennessee, where Colossus is housed, have voiced concerns over the use of gas-powered turbines to meet its energy demands. The Southern Environmental Law Center (SELC) has accused xAI of operating without the necessary air permits, potentially exacerbating local air pollution. These allegations underscore the delicate balance between technological advancement and environmental responsibility.
The Technical Edge: Nvidia’s Role in Colossus’s Supremacy
Nvidia’s cutting-edge technology is at the heart of Colossus’s impressive capabilities. The H100 and H200 chips, known for their exceptional memory and bandwidth performance, are instrumental in powering this AI behemoth. While Nvidia has recently unveiled its Blackwell chip, which surpasses the H200’s specifications, the H200 remains integral to Colossus’s architecture.
The AI community has reacted with enthusiasm to the launch of Colossus, viewing it as a pivotal moment in the industry’s evolution. Nvidia and industry luminaries like Cathie Wood, CEO of ARK Invest, have praised xAI’s groundbreaking achievement, recognizing Colossus as a significant milestone in AI development. This collaboration between xAI and Nvidia exemplifies the synergy between visionary leadership and cutting-edge technology, propelling the AI industry to new heights.
Environmental Concerns and Regulatory Hurdles
Despite its technological marvel, Colossus has ignited environmental and regulatory concerns. The SELC’s allegations regarding the turbines’ operation without proper permits cast a spotlight on the environmental impact of such massive computing infrastructure. Elon Musk’s vision of AI dominance comes with a considerable environmental cost, emphasizing the need for sustainable energy solutions as AI systems scale.
Musk, an advocate for responsible AI development, supports legislative efforts like California’s Senate Bill 1047, which aims to regulate AI technologies. This stance, however, has sparked debates within the tech community, with some fearing that it could stifle innovation. As xAI navigates these challenges, the balance between technological progress and ethical responsibility continues to be a focal point in the AI discourse.
As xAI continues to expand Colossus, the potential for groundbreaking advancements in AI research and development is immense. This supercomputer is not just a technological marvel; it embodies Musk’s ambition to redefine AI capabilities and secure a leading position in the AI sector. However, navigating complex regulatory landscapes and addressing environmental concerns will be crucial in fully realizing Colossus’s potential. What role will ethical and sustainable practices play in the future of AI development?
This article is based on verified sources and supported by editorial technologies.
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Dive Brief:
- Kroger will continue investing in AI as tools enable better product visibility and productivity, leading to reduced inventory loss or shrink and improved talent retention, executives said during the grocer’s Q1 earnings call in June.
- “We’ve seen good progress [around shrink],” SVP and CFO David Kennerley said during the call. “What we really attribute this to is we’ve made some investments in some AI-enabled technology and deployed new processes around that technology.”
- The company also launched a virtual AI assistant for its associates, which it partly credited for record levels of store and company retention during the quarter. “When our associates stay longer, they learn more, take on additional responsibilities and deliver a better customer experience, which leads to better sales,” said interim CEO Ron Sargent.
Dive Insight:
Kroger is doubling down on AI while keeping savings top of mind, joining a cost-conscious group of businesses making similar moves.
The grocer will close 60 underperforming stores by the end of next year as it reassesses capital allocation and “aggressively” finds ways to reduce costs throughout the company, according to the earnings call.
Kroger sees AI and other technologies as part of the solution, too.
“The other thing that will also contribute towards better cost performance is what I call ways of working and process improvement,” Kennerley said. “There’s a lot of opportunity here to work smarter, more efficiently, more tech-enabled, and we’ve already got some good proof points on that.”
Excluding fuel, identical-store sales ticked up 3.2% during Q1 2025, which ended May 24, compared with the same period last year. Kroger characterizes a store as identical if it operates without expansion or relocation for five full quarters.
Kroger’s once-sought-after merger partner, Albertsons, has similarly sharpened its technology focus while eyeing cost-saving measures.
“Our North Star is to use technology in everything that we do,” Albertsons CEO Susan Morris said during the company’s Q4 2024 earnings report in April.
As part of the strategy, the Idaho-headquartered grocer plans to increase AI use to enhance product quality and monitoring for freshness as it looks to drive higher sales and better customer experiences.
The efforts also align with Albertsons’ three-year plan to cut $1.5 billion in costs that rolled out after the merger failed.
Scientists leverage artificial intelligence to overcome a major hurdle in zinc-ion battery development, paving the way for cheaper, greener, and more efficient energy storage.
In a significant leap forward for battery innovation, scientists from Singapore’s Nanyang Technological University and China’s Huaiyin Normal University have teamed up to create an AI-powered system that could drastically improve how rechargeable batteries are made.
Led by Dr. Edison Huixiang Ang from the NIE/NTU, the team has harnessed artificial intelligence (AI) to solve one of the biggest challenges in zinc-ion battery technology, preventing dendrite growth.
Zinc-ion batteries are a promising alternative to today’s lithium batteries. They are cheaper, safer, and better for the environment. But they have one big problem-tiny spikes called dendrites can grow inside the battery when it charges. These spikes can cause the battery to stop working or even short-circuit.
To solve this, Dr. Ang’s team turned to AI. Instead of testing materials one by one, the AI quickly checked over 168,000 different combinations. This smart approach led them to a special material made from cerium and iron, called a metal-organic framework (MOF), that helps stop the dangerous spikes from forming.
“AI helped us discover the right material quickly and at a lower cost,” Dr. Edison Ang told Tech Explorist. “This allows us to create safer batteries that are more sustainable for the future.”
The team also created a thin protective layer using this material. In tests, the new battery design worked for over 4,300 hours and stayed almost 100% efficient after 1,400 charge cycles-much better than regular batteries.
This discovery could be useful for electric cars, phones, and storing solar or wind energy. As we move toward a greener world, having strong and reliable batteries is more important than ever.
“AI is helping scientists everywhere work smarter,” said Dr. Ang. “It’s opening the door to new ideas that can change the world.”
Journal Reference
- Jianbo Dong, Guolang Zhou, Wenhao Ding, Jiayi Ji, Qing Wang, Tianshi Wang, Lili Zhang, Xiuyang Zou, Jingzhou Yin and Edison Huixiang Ang. Machine learning-assisted benign transformation of three zinc states in zinc ion batteries. Energy & Environmental Science, 2025,18, 4872-4882. DOI: 10.1039/D5EE00650C
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