OpenAI on Thursday said the U.S. National Laboratories will be using its latest artificial intelligence models for scientific research and nuclear weapons security.

Under the agreement, up to 15,000 scientists working at the National Laboratories may be able to access OpenAI’s reasoning-focused o1 series. OpenAI will also work with Microsoft, its lead investor, to deploy one of its models on Venado, the supercomputer at Los Alamos National Laboratory, according to a release. Venado is powered by technology from Nvidia and Hewlett-Packard Enterprise.

OpenAI CEO Sam Altman announced the partnership at a company event called “Building to Win: AI Economics,” in Washington, D.C.

According to OpenAI, the new partnership will involve scientists using OpenAI’s technology to enhance cybersecurity to protect the U.S. power grid, identify new approaches to treating and preventing diseases and deepen understanding of fundamental mathematics and physics.

It will also involve work on nuclear weapons, “focused on reducing the risk of nuclear war and securing nuclear materials and weapons worldwide,” the company wrote. Some OpenAI researchers with security clearances will consult on the project.

Earlier this week, OpenAI released ChatGPT Gov, an AI platform built specifically for U.S. government use. OpenAI billed the new platform as a step beyond ChatGPT Enterprise as far as security. It will allow government agencies to feed “non-public, sensitive information” into OpenAI’s models while operating within their own secure hosting environments, the company said.

OpenAI said that since the beginning of 2024, more than 90,000 employees of federal, state and local governments have generated over 18 million prompts within ChatGPT, using the technology to translate and summarize documents, write and draft policy memos, generate code and build applications.

The government partnership follows a series of moves by Altman and OpenAI that appear to be targeted at appeasing President Donald Trump. Altman contributed $1 million to the inauguration, attended the event last week alongside other tech CEOs and recently signaled his admiration for the president.

Altman wrote on X that watching Trump “more carefully recently has really changed my perspective on him,” adding that “he will be incredible for the country in many ways.” OpenAI is also part of the recently announced Stargate project that involves billions of dollars in investment into U.S. AI infrastructure.

As OpenAI steps up its ties to the government, a Chinese rival is blowing up in the U.S. DeepSeek, an AI startup lab out of China, saw its app soar to the top of Apple’s App Store rankings this week and roiled U.S. markets on reports that its powerful model was trained at a fraction of the cost of U.S. competitors.

Altman described DeepSeek’s R1 model as “impressive,” and wrote on X that “we will obviously deliver much better models and also it’s legit invigorating to have a new competitor!”

WATCH: OpenAI highly overvalued

As thousands of homes started to burn across Los Angeles on Jan. 7, fire hydrants stopped working. The rapid spread of flames in winds up to 100 miles per hour was happening too quickly for water pumps to keep up. It shocked the system and those fleeing the flames.

“This area is known for having fire issues, so you would think that they would be prepared for this,” said Joan Zoloth, 70, who said she first moved to the area when she was 6 years old.

Zoloth’s childhood home burned down in the Palisades Fire. Her own home around the corner and her son’s home nearby were also lost. 

“My mother was a teacher,” Zoloth said. “What people don’t realize is how much Malibu is filled with those types of people — not just movie stars.”

CNBC went to the wreckage of the Palisades Fire to ask officials what happened to the water system in LA, and what other cities can do to be better prepared. As many as 1 in 6 Americans now live in areas with significant wildfire risk. 

“A firefight at this size, such an urban conflagration, any system is going to have its challenges in maintaining water pressure,” said State Fire Marshall Daniel Berlant, of the California Department of Forestry and Fire Protection, known as Cal Fire.

Water pressure was the primary problem, rather than a lack of supply, fire officials and water experts told CNBC. 

Much of the water in the Palisades is provided by three 1 million gallon tanks that sit up in the hills, using gravity to maintain water pressure in the hydrants and homes they supply below.

Pumps forcibly move water from main lines and surrounding reservoirs to those tanks. The tanks were full when the fires started, but the pumps couldn’t replenish water in the tanks as quickly as firefighters were using it below. As the tanks depleted, so did the water pressure, until some 20% of hydrants ran dry.

“The hydrants would have run dry anywhere in the world with a fire event like this in the topography where this occurred,” said Greg Pierce, director of the UCLA Human Right to Water Lab.

The closure of a 117 million gallon reservoir nearby complicated matters. Earlier this month, California Gov. Gavin Newsom and LA city council members called for investigations into why the Santa Ynez Reservoir hadn’t yet reopened after being drained almost a year ago to repair a tear in its cover.

“That would have made a difference,” Pierce said. “But even, by all accounts, if that reservoir was full, it wouldn’t have stopped the fire.”

Typically, fires are also fought by aircraft dropping water and fire retardant from above, but high winds kept them grounded for several hours on the first night of the fire.

Firefighters adapted with three tactics. They shuttled water through multiple engines connected to functional hydrants, drove it to locations in large water tenders, and pumped water directly from backyard swimming pools.

The LA Department of Water and Power said it quadrupled the water flow to the area and summoned 15 water tankers to directly refill fire trucks. It wasn’t enough.

As immediate danger calmed, misinformation ran wild. The Federal Emergency Management Agency, or FEMA, reactivated its rumor response site, and the LA Fire Department directly responded to inaccurate social media posts.

President Donald Trump, for instance, claimed that water ran out in LA because of policies meant to protect a small endangered fish called the Delta smelt.

“It’s just simply false. It’s nonsense,” said Peter Gleick, co-founder of the Pacific Institute, a global water think tank. Gleick has been researching water issues for four decades.

On his first day back in office, Trump signed an executive order titled “Putting People Over Fish: Stopping Radical Environmentalism to Provide Water to Southern California.” After visiting with Newsom in LA, Trump signed another executive order directing federal officials to find ways to override “disastrous” California water policies. 

“There’s lots of conversations about California water policy and how we allocate water to protect fish or ecosystems versus deliver water to different kinds of users, but that had no role whatsoever to play in water availability for firefighting,” Gleick said.

Southern California reservoirs are at above-average levels for this time of year because of two plentiful rainy seasons, he added.

“Misinformation about how if we just had more water from Northern California in Southern California, that would have made the difference, that’s not true,” UCLA’s Pierce said. “Even if you have water stored fairly close by in the region, you can’t just move it quickly up to an area like the Palisades.”

That’s why billionaires Lynda and Stewart Resnick are also not to blame for the Palisades Fire, the water experts who spoke with CNBC said. 

The Resnicks own the Wonderful Company, which includes brands such as Pom and Fiji Water, and have sprawling farmlands in the San Joaquin Valley that grow pistachios, oranges and pomegranates. They’ve been the subject of attacks on social media, some of which are antisemitic, that blame them for the water pressure problems in LA because of their investment in a public-private water bank that’s 100 miles north of LA and that has no ability to impact water pressure in the Palisades.

“There’s absolutely no connection between the two. This is a localized problem,” said Felicia Marcus, former chair of the California State Water Resources Control Board.

The fires also resurfaced criticism around state and local water decisions, from taking down dams to not building enough reservoirs.

The real culprit is extremely dry conditions, experts told CNBC. Before the fires, LA saw close to zero rain since May, and 2024 was the hottest year on record for the planet, Gleick said.

“Higher temperatures means more demand for water by soils and vegetation and people and agriculture,” he said. “Climate change is in many ways a water problem. It’s being manifested by drought and floods and wildfires.”

Similar water pressure problems plagued the 1991 Oakland Hills Fire, which destroyed more than 3,000 homes, and two Ventura County fires that each burned more than 1,000 homes in 2017 and 2018. 

The problem extends beyond California. Texas saw the largest fire in its history last February. As population booms, more people are moving to areas at high risk of fires between dense developments and wildland. 

California is home to the top six cities at highest wildfire risk in the U.S., but Texas, Colorado and Oregon also have cities in the top 15.

There are three key components to making water systems more resilient, Pierce said: increasing water supply, improving local infrastructure, and bolstering power.

After a 2008 fire that destroyed 280 homes, Yorba Linda Water District in California addressed all three. It added backup generators at water pump stations that had failed during the fire, added a long-planned underground reservoir, and installed a first-of-its-kind water tank called a Heli-Hydrant.

That $70,000 tank can automatically refill itself and is reserved for helicopters to dip from, reducing the length of flight times between water pickups and drops. It was used to quickly stop the Blue Ridge Fire in 2020.

“Cal Fire was able to jump on it and use our Heli-Hydrant, trigger it and keep the fire to five acres,” said John DeCriscio, who was operations manager at the Yorba Linda Water District at the time. “That was a huge success.”

San Francisco implemented a comprehensive solution after the city was almost completely destroyed in the 1906 earthquake and resulting fire, which also caused most hydrants to run dry. 

In 1913, the city developed a unique fire-suppression water system separate from the rest of the city’s water. Seawater enters the system from 52 suction connections along the waterfront, and it’s pumped in from fireboats and two high-pressure pumping stations. There are more than 200 underground cisterns to store backup water. A high-elevation reservoir and two large-capacity tanks use gravity, not pumps, to feed special high-pressure emergency hydrants that can be seen around the city with black, red and blue tops.

There are other solutions that cities can implement.

A company called Rain is working on autonomous, unmanned aircraft for dropping water on fires. In Japan, an autonomous system of water cannons protects a cultural heritage site with 200-year-old thatched roof houses.

Cost is the main reason these solutions haven’t been implemented widely. 

“There’s always this delicate balance of being afraid to go to your customers and raise their rates, but if you don’t raise their rates, you can’t do these extra things,” said Marcus, the former state water board chair. “It’s the kind of thing that keeps you up at night when you manage one of these agencies.”

Chinese artificial intelligence firm DeepSeek rocked markets this week with claims its new AI model outperforms OpenAI’s and cost a fraction of the price to build.

The assertions — specifically that DeepSeek’s large language model cost just $5.6 million to train — have sparked concerns over the eyewatering sums that tech giants are currently spending on computing infrastructure required to train and run advanced AI workloads.

But not everyone is convinced by DeepSeek’s claims.

CNBC asked industry experts for their views on DeepSeek, and how it actually compares to OpenAI, creator of viral chatbot ChatGPT which sparked the AI revolution.

Last week, DeepSeek released R1, its new reasoning model that rivals OpenAI’s o1. A reasoning model is a large language model that breaks prompts down into smaller pieces and considers multiple approaches before generating a response. It is designed to process complex problems in a similar way to humans.

DeepSeek was founded in 2023 by Liang Wenfeng, co-founder of AI-focused quantitative hedge fund High-Flyer, to focus on large language models and reaching artificial general intelligence, or AGI.

AGI as a concept loosely refers to the idea of an AI that equals or surpasses human intellect on a wide range of tasks.

Much of the technology behind R1 isn’t new. What is notable, however, is that DeepSeek is the first to deploy it in a high-performing AI model with — according to the company — considerable reductions in power requirements.

“The takeaway is that there are many possibilities to develop this industry. The high-end chip/capital intensive way is one technological approach,” said Xiaomeng Lu, director of Eurasia Group’s geo-technology practice.

“But DeepSeek proves we are still in the nascent stage of AI development and the path established by OpenAI may not be the only route to highly capable AI.” 

In terms of performance, DeepSeek says its R1 model achieves performance comparable to OpenAI’s o1 on reasoning tasks, citing benchmarks including AIME 2024, Codeforces, GPQA Diamond, MATH-500, MMLU and SWE-bench Verified.

In a technical report, the company said its V3 model had a training cost of only $5.6 million — a fraction of the billions of dollars that notable Western AI labs such as OpenAI and Anthropic have spent to train and run their foundational AI models. It isn’t yet clear how much DeepSeek costs to run, however.

If the training costs are accurate, though, it means the model was developed at a fraction of the cost of rival models by OpenAI, Anthropic, Google and others.

Daniel Newman, CEO of tech insight firm The Futurum Group, said these developments suggest “a massive breakthrough,” although he shed some doubt on the exact figures.

“I believe the breakthroughs of DeepSeek indicate a meaningful inflection for scaling laws and are a real necessity,” he said. “Having said that, there are still a lot of questions and uncertainties around the full picture of costs as it pertains to the development of DeepSeek.”

Meanwhile, Paul Triolio, senior VP for China and technology policy lead at advisory firm DGA Group, noted it was difficult to draw a direct comparison between DeepSeek’s model cost and that of major U.S. developers.

“The 5.6 million figure for DeepSeek V3 was just for one training run, and the company stressed that this did not represent the overall cost of R&D to develop the model,” he said. “The overall cost then was likely significantly higher, but still lower than the amount spent by major US AI companies.” 

DeepSeek wasn’t immediately available for comment when contacted by CNBC.

However, in comments to CNBC last week, Scale AI CEO Alexandr Wang, said he believed DeepSeek used the banned chips — a claim that DeepSeek denies.

Nvidia has since come out and said that the GPUs that DeepSeek used were fully export-compliant.

Yann LeCun, chief AI scientist at Meta, said that DeepSeek’s success represented a victory for open-source AI models, not necessarily a win for China over the U.S. Meta is behind a popular open-source AI model called Llama.

“To people who see the performance of DeepSeek and think: ‘China is surpassing the US in AI.’ You are reading this wrong. The correct reading is: ‘Open source models are surpassing proprietary ones’,” he said in a post on LinkedIn.

“DeepSeek has profited from open research and open source (e.g. PyTorch and Llama from Meta). They came up with new ideas and built them on top of other people’s work. Because their work is published and open source, everyone can profit from it. That is the power of open research and open source.”

WATCH: Why DeepSeek is putting America’s AI lead in jeopardy

– CNBC’s Katrina Bishop and Hayden Field contributed to this report