OpenAI CEO Sam Altman has dismissed concerns over artificial intelligence’s water consumption as a widely repeated “meme,” noting that modern data centers generally use far less water than their public image suggests.

Altman addressed the issue during the premiere episode of the Sources podcast with Alex Heath, published Tuesday, as he was asked about the growing resistance to AI and the environmental concerns surrounding the rapid expansion of data center infrastructure.

AI companies have faced increasing scrutiny over the electricity, land and water required to build and operate the computing infrastructure needed to train and run powerful models. Altman acknowledged that the industry has developed a reputation for consuming large quantities of water, but disputed the scale of that impact.

“That has been a robust meme and difficult to disprove, but I don’t think holds up to any scrutiny,” Altman said.

He argued that modern data centers typically consume roughly as much water as an office building. That claim is broadly consistent with some available data, although water consumption varies significantly depending on a facility’s cooling technology, size, location and local climate.

A 2024 report by a Virginia state government commission, examining the state’s rapidly expanding data center industry, found that water use differed substantially between facilities. However, most of the data centers examined consumed amounts of water comparable to or below those of an average large office building.

The issue remains one of the most contentious elements of the backlash against AI infrastructure. Data centers can require substantial quantities of water when they use evaporative cooling systems, particularly in hot or water-stressed regions.

A Gallup survey published in May found that 71% of Americans opposed the construction of a data center in their local area. About 70% of respondents said they were concerned about the environmental impact, while half cited the effect on local resources. Water specifically was identified by 18% of respondents.

A Business Insider investigation last year also linked data center development to worsening water pressures in parts of the U.S. West, citing the use of water-intensive evaporative cooling systems among the factors contributing to consumption.

The industry, however, has increasingly sought to reduce its dependence on fresh water. The Data Center Coalition, an industry trade group, says developers use a range of cooling technologies, including closed-loop and waterless systems, and consider local water availability when designing facilities.

Altman also sought to put AI’s water consumption into perspective by comparing ChatGPT queries with California’s almond industry, one of the state’s more water-intensive agricultural sectors.

He said growing a single California almond requires more water than thousands of ChatGPT queries.

“The people that are scarfing down 12 almonds at a time don’t feel like they’re doing something horrible from a water perspective, for the most part,” Altman said.

The comparison has limitations, however, because the water footprint of an AI query and the agricultural water requirements of a crop are calculated in very different ways. It also does not account for differences between data centers, cooling systems, locations, or the source of the water being consumed.

Still, available estimates support the broad magnitude of Altman’s comparison.

Altman has previously estimated that an average ChatGPT query consumes about 0.32 milliliters of water. Google has estimated that an average text prompt on its Gemini app uses about 0.26 milliliters.

By comparison, a 2019 study by researchers affiliated with the U.S. Geological Survey estimated that producing a single California almond required an average of about 3.56 liters of water, or slightly less than a gallon.

Using those figures, the water associated with one almond would be equivalent to roughly 11,000 ChatGPT queries at Altman’s stated estimate.

The larger debate, however, is less about the water consumed by an individual AI prompt than about the aggregate demand created by billions of queries and the construction of increasingly large data centers.

A small amount of water per interaction can become a significant resource requirement when multiplied across massive user bases, while the location of the infrastructure can determine whether that consumption places meaningful pressure on local water supplies.

This is where Altman’s argument faces its most important test. Saying that AI uses relatively little water on a per-query basis does not necessarily resolve concerns about the cumulative impact of rapidly expanding computing infrastructure, particularly in regions already facing water scarcity.

Altman nevertheless argued that the industry should focus less on defending AI against criticism and more on demonstrating its usefulness.

“I think the right way to get people to like something is to deliver them value,” he said.

“The industry has got work to do in terms of how we make these products easy to use and easy for people to get a lot of value out of.”

AI companies are investing hundreds of billions of dollars in computing capacity while attempting to convince governments and communities that the economic and technological benefits of that infrastructure outweigh its environmental costs.

Chinese consumer electronics maker TCL has sued South Korean rival Samsung in a U.S. federal court, accusing it of falsely marketing a new range of televisions as using Mini LED technology when, according to the complaint, the sets are based on conventional LED technology.

The lawsuit, filed Monday in Los Angeles federal court, targets Samsung’s M Model televisions, which TCL says were introduced in March at prices below its cheapest genuine Mini LED models. TCL alleges Samsung repackaged televisions from its standard LED lineup and marketed them as Mini LED products, misleading consumers seeking the improved picture quality associated with the technology.

The case puts a potentially important segment of the global television market at the center of a legal fight between two of its largest manufacturers. TCL has been challenging Samsung in the U.S. with aggressively priced Mini LED televisions, while Samsung has sought to defend its position across premium and mass-market display categories.

TCL’s complaint alleges that Samsung “took a cheap, non-Mini LED model from a recycled product line and peddled it to the public as a ‘supreme’ Mini LED model at an attractive price point.”

Samsung has rejected the accusation and said it will vigorously defend the case. The company said it stands “fully behind the quality and accuracy of our product descriptions.”

The dispute turns on what consumers are actually getting when they buy a television marketed as Mini LED.

Unlike conventional LED televisions, Mini LED displays use much smaller light-emitting diodes in the backlight, allowing manufacturers to place substantially more independently controlled lighting zones behind the screen. That can improve control over bright and dark areas, increase contrast, and expand dynamic range.

The technology has become a crucial middle ground between conventional LED televisions and more expensive OLED displays. For manufacturers, it offers a way to deliver higher-end picture performance while maintaining more competitive prices.

TCL says it was able to exploit that opportunity earlier and more aggressively than Samsung in the U.S. The company launched its affordable QM Mini LED television range in 2023 and claims it overtook Samsung in U.S. Mini LED sales and market share between 2023 and 2025.

The lawsuit alleges Samsung did not have a Mini LED television capable of competing with TCL’s products on both price and performance. Instead, TCL claims, Samsung repackaged its standard Crystal UHD television line as the M Model and introduced the products at lower prices than TCL’s Mini LED offerings.

TCL further alleges that the M Model televisions contain none of the technological components associated with Mini LED and are substantially similar to Samsung’s conventional LED televisions. The complaint claims the strategy rapidly increased Samsung’s sales of the disputed products, with the company’s Mini LED television sales allegedly rising almost fourfold in less than three months.

TCL attorney R.C. Harlan said the alleged marketing strategy harmed both consumers and TCL.

“Samsung’s false advertising misled consumers who wanted the higher picture quality associated with Mini LED televisions into buying Samsung’s falsely labeled product, unfairly damaging TCL’s sales, goodwill, and valuable technology in the process,” Harlan said.

A fight over market share as much as technology

The lawsuit has drawn large attention because TCL’s allegations go beyond a technical disagreement over television specifications. At stake is the value of the Mini LED label itself and the competitive advantage that comes from convincing consumers that a product belongs to a higher-performance category.

If TCL succeeds, Samsung could face restrictions on how it markets the M Model televisions in the U.S., potentially forcing changes to product descriptions, packaging and advertising. TCL is also seeking an unspecified amount of damages. The case could also increase scrutiny of how television manufacturers define and market technologies such as Mini LED, particularly as consumers increasingly compare products using technical labels rather than detailed hardware specifications.

TCL’s strategy has been to make Mini LED more accessible through aggressive pricing. Samsung, meanwhile, has traditionally occupied a powerful position in televisions through its broad product portfolio and premium display brands.

That makes pricing particularly important. If a conventional LED television can be marketed under the same Mini LED terminology as a more technologically sophisticated product, TCL’s competitive advantage from investing in Mini LED hardware and bringing it down to lower price points could be weakened.

Legal Risk Extends Beyond One Television Line

The lawsuit also illustrates how product differentiation can become a legal battleground in mature consumer electronics markets.

Technology companies frequently compete through proprietary branding and technical terminology, but the commercial value of those terms depends on consumers understanding them as meaningful indicators of performance. A court ruling against Samsung could therefore have implications beyond the M Model range by encouraging greater scrutiny of technical claims used to differentiate television products.

The case remains at an early stage, and TCL’s allegations have not been established in court. Samsung’s decision to contest the claims means the dispute could ultimately hinge on technical evidence concerning the construction of the M Model televisions, industry definitions of Mini LED and the precise representations Samsung made to consumers.

At its core, the lawsuit is a contest over whether a television can command the price and market positioning of a more advanced display technology based on its marketing label alone. The answer could affect not only TCL and Samsung, but also how the rapidly expanding Mini LED category is defined and sold to consumers.

California lawmakers have approved legislation that would establish the nation’s first statewide statutory framework governing how lawyers may use generative artificial intelligence in legal practice, placing responsibility for the accuracy and confidentiality of AI-assisted work firmly on attorneys.

Both chambers of the California legislature had approved the latest version of Senate Bill 574 as of Monday, sending the measure to Democratic Governor Gavin Newsom, who must now decide whether to sign it into law or veto it.

The legislation comes as generative AI tools become increasingly common in law firms and legal departments, while courts across the United States confront a growing number of cases involving fabricated case citations, inaccurate legal arguments and other material generated by AI systems.

Under the proposed law, lawyers would be prohibited from “delegat[ing] the practice of law” to generative AI. Attorneys using AI would instead have to take “reasonable steps” to verify the accuracy of material generated by the technology, including case citations and other legal authorities, and correct false or hallucinated information before using it.

The measure would also require lawyers to disclose their use of AI in documents submitted to courts. It would restrict attorneys from entering confidential or otherwise nonpublic information into certain generative AI systems, addressing concerns that sensitive client information could be exposed through AI platforms.

Arbitrators would face a separate restriction: they would not be permitted to delegate decision-making to an AI tool.

Senator Tom Umberg, a Democrat who chairs the California Senate Judiciary Committee and introduced the bill, said the legislation is intended to address a problem that has become increasingly visible in courtrooms.

“Submit materials that have hallucinations or have some other anomaly, and they attribute it to AI, and that simply can’t exist,” Umberg told Reuters.

“Our system, our courts, our judiciary has to rely on the integrity of the litigants and the advocates. And if they can’t do that, everything breaks down,” he said.

The proposed law largely builds on obligations lawyers already face under California’s civil litigation and professional conduct rules, including requirements that court filings be supported by existing law. It was modeled in part on a separate California Judicial Council policy governing the use of AI by judges and court employees.

The Judicial Council, which serves as the policy-making body for California’s court system, said it had no position or comment on the legislation.

Umberg said requiring attorneys to verify AI-generated material would raise the standard for lawyers using the technology while giving courts another basis for imposing sanctions when attorneys fail to comply.

“The requirement to verify all material submitted in court ‘should raise the standard for lawyers,’” Umberg said, adding that the legislation would give courts “another tool” for potential sanctions.

The proposal, however, has raised questions about whether a new statute is necessary when lawyers are already bound by professional and ethical duties requiring them to ensure the accuracy of their work.

Wayne Stacy, executive director of the Berkeley Center for Law and Technology at the University of California, Berkeley School of Law, said the measure is largely “duplicative” of existing ethics rules governing attorneys.

That tension could become one of the central issues surrounding California’s approach. The legislation does not fundamentally create a new obligation for lawyers to ensure that their court filings are accurate. Rather, it would expressly apply that existing professional responsibility to work produced with generative AI and establish additional disclosure and confidentiality requirements.

The move also underlines a broader shift in the legal profession’s approach to AI. Early concerns focused heavily on whether lawyers should use generative AI at all. The emerging regulatory question is how lawyers can use it while retaining professional responsibility for the final work. AI systems can produce convincing but incorrect legal authorities, a problem commonly referred to as AI “hallucination.” The technology can therefore accelerate research and drafting while simultaneously creating a new verification burden for lawyers.

California’s proposed framework could also have significance beyond the state’s legal profession. If enacted, it would provide one of the clearest statutory models in the United States for regulating professional use of generative AI, potentially influencing law firms, courts and policymakers elsewhere as they develop their own rules.

The bill now awaits Newsom’s decision.