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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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How black boxes became key to solving airplane crashes

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How black boxes became key to solving airplane crashes

After the search for survivors and recovery of victims in tragic aviation accidents — like that of a UPS cargo plane shortly after takeoff from Louisville Muhammad Ali International Airport in Kentucky last month — comes the search for flight data and a cockpit voice recorder often called the “black box.”

Every commercial plane has them. Aerospace giants GE Aerospace and Honeywell are among a few companies that design them to be nearly indestructible so they can help investigators understand the cause of a crash.

“They’re very crucial because it’s one of the few sources of information that tells us what happened leading up to the accident,” said Chris Babcock, branch chief of the vehicle recorder division at the National Transportation Safety Board. “We can get a lot of information from parts and from the airplane.”

Commercial aircraft have become very complex. A Boeing 787 Dreamliner records thousands of different pieces of information. In the case of the Air India crash in June, data revealed both engine fuel switches were put into a cutoff position within one second of each other. A voice recording from inside the cockpit captured the pilots discussing the cutoffs.

“All of those parameters today can have a very huge impact on the investigation,” said former NTSB member John Goglia. “It’s our goal to to provide information back to our investigators who are on scene as quick as we can to help move the investigation forward.”

This crucial data can also help prevent future accidents. A crash can cost airlines or plane manufacturers hundreds of millions of dollars and leave victims’ families with a lifetime of grief.

But in some circumstances black boxes were destroyed or never found. Experts say further developments such as cockpit video recorders and real-time data streaming are needed.

“The technology is there. Crash worthy cockpit video recorders are already being installed in a lot of helicopters and other types of airplanes, but they’re not required,” said Jeff Guzzetti, aviation analyst and former accident investigator for the Federal Aviation Administration and NTSB. “There’s privacy and cost issues involving cockpit video recorders but the NTSB has been recommending that the FAA require them for years now.”

Watch the video to learn more.

CNBC’s Leslie Josephs contributed to this report.

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Stocks end November with mixed results despite a strong Thanksgiving week rally

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Stocks end November with mixed results despite a strong Thanksgiving week rally

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Palantir has worst month in two years as AI stocks sell off

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Palantir has worst month in two years as AI stocks sell off

CEO of Palantir Technologies Alex Karp attends the Pennsylvania Energy and Innovation Summit, at Carnegie Mellon University in Pittsburgh, Pennsylvania, U.S., July 15, 2025.

Nathan Howard | Reuters

It’s been a tough November for Palantir.

Shares of the software analytics provider dropped 16% for their worst month since August 2023 as investors dumped AI stocks due to valuation fears. Meanwhile, famed investor Michael Burry doubled down on the artificial intelligence trade and bet against the company.

Palantir started November off on a high note.

The Denver-based company topped Wall Street’s third-quarter earnings and revenue expectations. Palantir also posted its second-straight $1 billion revenue quarter, but high valuation concerns contributed to a post-print selloff.

In a note to clients, Jefferies analysts called Palantir’s valuation “extreme” and argued investors would find better risk-reward in AI names such as Microsoft and Snowflake. Analysts at RBC Capital Markets raised concerns about the company’s “increasingly concentrated growth profile,” while Deutsche Bank called the valuation “very difficult to wrap our heads around.”

Adding fuel to the post-earnings selloff was the revelation that Burry is betting against Palantir and AI chipmaker Nvidia. Burry, who is widely known for predicting the housing crisis that occurred in 2008 and the portrayal of him in the film “The Big Short,” later accused hyperscalers of artificially boosting earnings.

Palantir CEO Alex Karp vocally hit the front lines, appearing twice in one week on CNBC, where he accused Burry of “market manipulation” and called the investor’s actions “egregious.”

“The idea that chips and ontology is what you want to short is bats— crazy,” Karp told CNBC’s “Squawk Box.”

Despite the vicious selloff, Palantir has notched some deal wins this month. That included a multiyear contract with consulting firm PwC to speed up AI adoption in the U.K. and a deal with aircraft engine maintenance company FTAI.

But those announcements did little to shake off valuation worries that have haunted all AI-tied companies in November.

Across the board, investors have viciously ditched the high-priced group, citing fears of stretched valuations and a bubble.

In November, Nvidia pulled back more than 12%, while Microsoft and Amazon dropped about 5% each. Quantum computing names such as Rigetti Computing and D-Wave Quantum have shed more than a third of their value.

Apple and Alphabet were the only Magnificent 7 stocks to end the month with gains.

Sill, questions linger over Palantir’s valuation, and those worries aren’t a new concern.

Even after its steep price drop, the company’s stock trades at 233 times forward earnings. By comparison, Nvidia and Alphabet traded at about 38 times and 30 times, respectively, at Friday’s close.

Karp, who has long defended the company, didn’t miss an opportunity to clap back at his critics, arguing in a letter to shareholders that the company is making it feasible for everyday investors to attain rates of return once “limited to the most successful venture capitalists in Palo Alto.”

“Please turn on the conventional television and see how unhappy those that didn’t invest in us are,” Karp said during an earnings call. “Enjoy, get some popcorn. They’re crying. We are every day making this company better, and we’re doing it for this nation, for allied countries.”

Palantir declined to comment for this story.

WATCH: Palantir CEO Alex Karp: We’ve printed venture results for the average American

Palantir CEO Alex Karp: We've printed venture results for the average American

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