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Nvidia stock surged close to a $1 trillion market cap in after-hours trading Wednesday after it reported a shockingly strong strong forward outlook and CEO Jensen Huang said the company was going to have a “giant record year.”

Sales are up because of spiking demand for the graphics processors (GPUs) that Nvidia makes, which power AI applications like those at Google, Microsoft, and OpenAI.

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Demand for AI chips in datacenters spurred Nvidia to guide to $11 billion in sales during the current quarter, blowing away analyst estimates of $7.15 billion.

“The flashpoint was generative AI,” Huang said in an interview with CNBC. “We know that CPU scaling has slowed, we know that accelerated computing is the path forward, and then the killer app showed up.”

Nvidia believes it’s riding a distinct shift in how computers are built that could result in even more growth — parts for data centers could even become a $1 trillion market, Huang says.

Historically, the most important part in a computer or server had been the central processor, or the CPU, That market was dominated by Intel, with AMD as its chief rival.

With the advent of AI applications that require a lot of computing power, the graphics processor (GPU) is taking center stage, and the most advanced systems are using as many as eight GPUs to one CPU. Nvidia currently dominates the market for AI GPUs.

“The data center of the past, which was largely CPUs for file retrieval, is going to be, in the future, generative data,” Huang said. “Instead of retrieving data, you’re going to retrieve some data, but you’ve got to generate most of the data using AI.”

“So instead of instead of millions of CPUs, you’ll have a lot fewer CPUs, but they will be connected to millions of GPUs,” Huang continued.

For example, Nvidia’s own DGX systems, which are essentially an AI computer for training in one box, use eight of Nvidia’s high-end H100 GPUs, and only two CPUs.

Google’s A3 supercomputer pairs eight H100 GPUs alongside a single high-end Xeon processor made by Intel.

That’s one reason why Nvidia’s data center business grew 14% during the first calendar quarter versus flat growth for AMD’s data center unit and a decline of 39% in Intel’s AI and Data Center business unit.

Plus, Nvidia’s GPUs tend to be more expensive than many central processors. Intel’s most recent generation of Xeon CPUs can cost as much as $17,000 at list price. A single Nvidia H100 can sell for $40,000 on the secondary market.

Nvidia will face increased competition as the market for AI chips heats up. AMD has a competitive GPU business, especially in gaming, and Intel has its own line of GPUs as well. Startups are building new kinds of chips specifically for AI, and mobile-focused companies like Qualcomm and Apple keep pushing the technology so that one day it might be able to run in your pocket, not in a giant server farm. Google and Amazon are designing their own AI chips.

But Nvidia’s high-end GPUs remain the chip of choice for current companies building applications like ChatGPT, which are expensive to train by processing terabytes of data, and are expensive to run later in a process called “inference,” which uses the model to generate text, images, or make predictions.

Analysts say that Nvidia remains in the lead for AI chips because of its proprietary software that makes it easier to use all of the GPU hardware features for AI applications.

Huang said on Wednesday that the company’s software would not be easy to replicate.

“You have to engineer all of the software and all of the libraries and all of the algorithms, integrate them into and optimize the frameworks, and optimize it for the architecture, not just one chip but the architecture of an entire data center,” Huang said on a call with analysts.

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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.

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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.

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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.

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