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How the AI-based 'recognition' economy works and why it may lead to a post-device world

Metropolis, which uses AI and computer vision to identify vehicles and take parking lot payments without any physical transaction, has raised $1.6 billion in combined debt and equity in a new fundraising round at a $5 billion valuation.

Already the largest parking lot network in the U.S., handling more than 7% of licensed drivers (nearly 20 million people) across over 4,000 locations, the Santa Monica, California-based company is planning to use the capital for a major expansion across the retail sector, including gas stations and quick-service restaurant drive-thru windows, as well as into hotels and office buildings.

“With this new capital, we’re continuing to scale our platform and forge the foundation of the Recognition Economy, building a new paradigm for how AI is deployed in the real world,” said Alex Israel, CEO and co-founder of Metropolis, in the deal announcement.

The $1.6 billion capitalization includes a $1.1 billion senior secured loan and $500 million in Series D equity funding, led by new investor LionTree. Additional investors included Eldridge, SoftBank, DFJ, Tekne Capital, Vista and BDT & MSD Partners’ affiliated credit funds. It’s the largest round that the company has raised across its $2 billion in deals not specifically tied to an acquisition — Metropolis took parking lot operator SP Plus private in 2024, the largest private M&A deal of 2024. The company doubled the debt it was able to raise since its last credit market deal in 2024 in a new financing led by J.P. Morgan, which the company attributed to its expanding gross margins.

“Metropolis is demonstrating that AI can be thoughtfully commercialized at real-world scale,” said Ramin Arani, head of investments at LionTree, in the deal announcement.

Metropolis ranked No. 13 on the 2025 CNBC Disruptor 50 list.

Metropolis

Any driver that has used a Metropolis parking lot knows that the payment can be conducted with no waiting, no tickets, machines, credit cards, or apps. The company’s proprietary computer vision platform recognizes a “vehicle fingerprint” based on their unique characteristics. Users do have to first set up an account in the company’s app or on its website with basic profile information including a license plate number, though its technology is not limited to license plate scanning.

The company says it has been growing by one million members per month and sees a total addressable market of at least 50 million individuals. Across its current operations, Metropolis is handling $5 billion in annual transactions.

The physical world remains hopelessly analog,” said Courtney Fukuda, chief integration officer and co-founder of Metropolis, at the recent CNBC AI Summit in Nashville. “We started by fixing parking, partially because it’s ubiquitous and because it’s a nightmare,” she added.

As the company expands into retail locations including fueling and drive-thrus, it will be focused on a software-as-a-service model, with retail and real estate owners benefitting from offering the technology to their consumers. “We’re not going to go and buy 1,000 McDonald’s and suddenly franchise McDonald’s with our computer vision technology,” Fukuda said. “We’re going to be licensing our technology to those operators.”

While the parking lot experience is more limited to making the payment transaction frictionless, Metropolis is betting that as it moves deeper across retail and the physical world, its ability to gather and analyze data on individuals will lead to a level of personalization that consumers prefer and that increases revenue opportunities for businesses, ushering in a “post-device world.”

“We know where people are actually moving in the real world, and we can start to put together essentially a member graph of their physical world footprint and insights,” Fukuda said, data analysis that will be valuable to commercial real estate owners, and hotel companies. “It gives them information about what used to be a black box and used to just be kind of cash collections,” Fukuda added.

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Correction: Courtney Fukuda is chief integration officer and co-founder of Metropolis. An earlier version of this article misspelled her name.

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Software startup deploys Singapore’s first quantum computer for commercial use

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Software startup deploys Singapore’s first quantum computer for commercial use

Inside Horizon Quantum’s office in Singapore on Dec. 3, 2025. The software firm claimed it is the first private company to deploy a commercial quantum computer in the city-state.

Sha Ying | CNBC International

Singapore-based software firm Horizon Quantum on Wednesday said it has become the first private company to run a quantum computer for commercial use in the city-state, marking a milestone ahead of its plans to list in the U.S.

The start-up, founded in 2018 by quantum researcher Joe Fitzsimons, said the machine is now fully operational. It integrates components from quantum computing suppliers, including Maybell Quantum, Quantum Machines and Rigetti Computing.

According to Horizon Quantum, the new computer also makes it the first pure-play quantum software firm to own its own quantum computer — an integration it hopes will help advance the promising technology.

“Our focus is on helping developers to start harnessing quantum computers to do real-world work,” Fitzsimons, the CEO, told CNBC. “How do we take full advantage of these systems? How do we program them?” 

Horizon Quantum builds the software tools and infrastructure needed to power applications for quantum computing systems. 

“Although we’re very much focused on the software side, it’s really important to understand how the stack works down to the physical level … that’s the reason we have a test bed now,” Fitzsimons said. 

Quantum race

Horizon Quantum hopes to use its new hardware to accelerate the development of real-world quantum applications across industries, from pharmaceuticals to finance.

Quantum systems aim to tackle problems too complex for traditional machines by leveraging principles of quantum mechanics.

For example, designing new drugs, which requires simulating molecular interactions, or running millions of scenarios to assess portfolio risk, can be slow and computationally costly for conventional machines. Quantum computing is expected to provide faster, more accurate models to tackle these problems.

A top executive at Google working on quantum computers told CNBC in March that he believes the technology is only five years away from running practical applications.

Still, today’s quantum systems remain in the nascent stages of development and pose many engineering and programming challenges.

Investment in the space has been rising, however, as major tech companies report technological breakthroughs. Alphabet, Microsoft, Amazon and IBM, along with the U.S. government, are already pouring millions into quantum computing.

Investor attention also received a bump in June after Nvidia chief executive Jensen Huang offered upbeat remarks, saying quantum computing is nearing an “inflection point” and that practical uses may arrive sooner than he had expected.

Nvidia CEO: Quantum computing is reaching an inflection point

Nasdaq listing

Horizon Quantum’s announcement comes ahead of a merger with dMY Squared Technology Group Inc., a special purpose acquisition company. The deal, agreed upon in September, aims to take Horizon public on the Nasdaq under the ticker “HQ.”

The software firm said in September that the transaction valued the company at around $503 million and was expected to close in the first quarter of 2026. 

The launch of its quantum computer also helps cement Singapore’s ambition to be a regional quantum computing hub. The city-state has invested heavily in the technology for years, setting up its first quantum research center in 2007.

Before Horizon Quantum’s system came online, Singapore reportedly had one quantum computer, used primarily for research purposes. Meanwhile, U.S.-based firm Quantinuum plans to deploy another commercial system in 2026.

Singapore’s National Quantum Strategy, unveiled in May 2024, committed 300 million Singapore dollars over five years to expand the sector, with a significant portion directed toward building local quantum computer processors.  

In May 2024, the National Quantum Strategy (NQS), Singapore’s national quantum initiative, pledged around S$300 million over five years to strengthen development in the sector, with a significant portion directed toward building local quantum computer processors.

Why Amazon, Google, Microsoft, IBM and numerous startups are racing to build quantum computers

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A little-known startup just used AI to make a moon dust battery for Blue Origin

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A little-known startup just used AI to make a moon dust battery for Blue Origin

Istari Digital CEO Will Roper talks about the AI technology that built the Blue Origin moon vacuum

Artificial intelligence has created a device that turns moon dust into energy.

The moon vacuum, which was unveiled on Wednesday by Blue Origin at Amazon‘s re:Invent 2025 conference in Las Vegas, was built using critical technology from startup Istari Digital.

“So what it does is sucks up moon dust and it extracts the heat from it so it can be used as an energy source, like turning moon dust into a battery,” Istari CEO Will Roper told CNBC’s Morgan Brennan.

Spacecraft carrying out missions on the lunar surface are typically constrained by lunar night, the two-week period every 28 days during which the moon is cast in darkness and temperatures experience extreme drops, crippling hardware and rendering it useless unless a strong, long-lasting power source is present.

“Kind of like vacuuming at home, but creating your own electricity while you do it,” he added.

The battery was completely designed by AI, said Roper, who was assistant secretary of the Air Force under President Donald Trump‘s first term and is known for transforming the acquisition process at both the Air Force and, at the time, the newly created Space Force.

Read more CNBC tech news

A major part of the breakthrough in Istari’s technology is the way in which it handles and limits AI hallucinations.

Roper said the platform takes all the requirements a part needs and creates guardrails or a “fence around the playground” that the AI can’t leave while coming up with designs.

“Within that playground, AI can generate to its heart’s content,” he said.

“In the case of Blue Origin’s moon battery, [it] doesn’t tell you the design was a good one, but it tells us that all of the requirements were met, the standards were met, things like that that you got to check before you go operational,” he added.

Istari is backed by former Google CEO Eric Schmidt and already works with the U.S. government, including as a prime contractor with Lockheed Martin on the experimental x-56A unmanned aircraft.

Watch the full interview above and go deeper into the business of the stars with the Manifest Space podcast.

X-Energy’s Kam Ghaffarian on Nuclear Power, AI, and the Space Tech Race

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Nvidia CEO Jensen Huang talks chip restrictions with Trump, blasts state-by-state AI regulations

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Nvidia CEO Jensen Huang talks chip restrictions with Trump, blasts state-by-state AI regulations

Jensen Huang: State-by-state AI regulation would drag industry to a halt

Nvidia CEO Jensen Huang said he met with President Donald Trump on Wednesday and that the two men discussed chip export restrictions, as lawmakers consider a proposal to limit exports of advanced artificial intelligence chips to nations like China.

“I’ve said it repeatedly that we support export controls, and that we should ensure that American companies have the best and the most and first,” Huang told reporters on Capitol Hill.

Lawmakers were considering including the Guaranteeing Access and Innovation for National Artificial Intelligence Act in a major defense package, known as the National Defense Authorization Act. The GAIN AI Act would require chipmakers like Nvidia and Advanced Micro Devices to give U.S. companies first pick on their AI chips before selling them in countries like China.

The proposal isn’t expected to be part of the NDAA, Bloomberg reported, citing a person familiar with the matter.

Huang said it was “wise” that the proposal is being left out of the annual defense policy bill.

“The GAIN AI Act is even more detrimental to the United States than the AI Diffusion Act,” Huang said.

Nvidia’s CEO also criticized the idea of establishing a patchwork of state laws regulating AI. The notion of state-by-state regulation has generated pushback from tech companies and spurred the creation of a super PAC called “Leading the Future,” which is backed by the AI industry.

“State-by-state AI regulation would drag this industry into a halt and it would create a national security concern, as we need to make sure that the United States advances AI technology as quickly as possible,” Huang said. “A federal AI regulation is the wisest.”

Trump last month urged legislators to include a provision in the NDAA that would preempt state AI laws in favor of “one federal standard.”

But House Majority Leader Steve Scalise (R-LA) told CNBC’s Emily Wilkins on Tuesday the provision won’t make it into the bill, citing a lack of sufficient support. He and other lawmakers will continue to look for ways to establish a national standard on AI, Scalise added.

WATCH: Nvidia currying favor to be able to sell chips in China

Nvidia obviously currying favor to be able to sell chips in China, says Niles Investment's Dan Niles

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