Apple, Microsoft, Amazon and Google were the four leading global brands at the end of 2023, according to consulting firm Interbrand. They’re are also four of the world’s five most valuable companies.

The other is Nvidia, which for a time this week, surpassed Microsoft to become the largest company in the world by market cap.

But despite its $3.1 trillion valuation (it reached $3.3 trillion before a two-day slide), Nvidia doesn’t even crack the top 100 most iconic names on Interbrand’s most recent list, which is populated by such companies as McDonald’s, Starbucks, Disney and Netflix.

Nvidia’s historic rise in valuation — the stock has climbed almost ninefold since the end of 2022 — has been driven almost entirely by demand for its graphics processing units (GPUs) that are at the heart of the boom in generative artificial intelligence and, more broadly, by the hype over AI. Nvidia has over 80% of the market for chips used to train and deploy AI software like ChatGPT. A handful of huge tech companies are the primary buyers of its chips.

The speed of Nvidia’s ascent and its relative lack of contact with consumers along the way combines to put the 31-year-old company’s brand recognition on Main Street far behind its allure on Wall Street. No. 100 on Interbrand’s list for 2023 is Japanese camera maker Canon, with Dutch brewer Heineken at No. 99.

“As a product company recently moving onto a global stage, Nvidia has not had time, nor has it dedicated resources, to change its role of brand and strengthen its brand to protect future revenue,” Greg Silverman, Interbrand’s global director of brand economics, said in an email. The risk for Nvidia, Silverman added, is that its “weak brand strength will limit how valuable it will be, despite its market cap heights.”

A spokesperson for Nvidia declined to comment.

Nvidia’s annual revenue growth has exceeded 200% in each of the past three quarters. For fiscal 2025, revenue is expected to almost double from a year earlier to over $120 billion, according to LSEG.

The company’s data center GPUs, which made up 85% of sales in the most recent quarter, are installed in massive facilities, and typically require a team of expensive data science and supercomputing experts to configure them to efficiently create AI software.

By contrast, Apple, ranked No. 1 by Interbrand, makes the vast majority of its money by selling iPhones and other devices to consumers across the globe. Microsoft, ranked second, is an enterprise sales giant, but is ubiquitously known for its Windows and Office software. Third-ranked Amazon strives to be consumers’ everything store, and No. 4 Google is, for many people, the front door to the internet.

Rounding out Interbrand’s top 10 are South Korean electronics giant Samsung, along with three car companies (Toyota, Mercedes-Benz and BMW), Coca-Cola and Nike.

Further down the list, at No. 24, is Nvidia rival Intel, which is best known for making the processor at the heart of laptops and PCs and for its long-running “Intel Inside” advertising campaign. Even Hewlett Packard Enterprise, a company that builds servers, made the list at No. 91.

However, a competing survey shows that Nvidia’s brand value is catching up to that of its peers.

In a ranking of the 100 most valuable global brands published this month by Kantar BrandZ, Nvidia landed at No. 6, leaping 18 places from its prior survey. The brand’s overall valued jumped 178% in a year to an estimate of about $202 billion. Kantar surveys enterprise buyers to evaluate brands that primarily sell to other businesses to come up with a total estimate of brand value.

“Nvidia is pound for pound as relevant and meaningful to that B2B buyer that’s looking to make big, large purchases in-house for their company as Apple is to the consumer who’s buying an iPad or a Mac,” Marc Glovsky, senior brand strategist at Kantar, told CNBC.

And while Nvidia may not be a name known to your parents — or your kids — it does have resonance in a particular corner of the consumer world. Just ask your hard-core gaming buddy.

When Nvidia was founded in 1991, AI was a nascent field. The company’s primary focus was on designing chips that could draw digital triangles quickly, a basic capability that led to a huge expansion in 3D games.

For years, Nvidia, and its GeForce brand and green logo were well known to the type of people who tweaked their computers to run the most advanced games. Nvidia provides the chips for the Nintendo Switch console, which has shipped over 140 million units around the world.

Unlike Intel, Nvidia never put its name in front of consumers with flashy ad campaigns. And gaming is now just a nice side business for chipmaker. In the latest quarter, it accounted for $2.6 billion of revenue, or 10% of total sales, rising 18% year over year.

When it comes to Nvidia’s most important products, companies and institutions vying for its AI chips have to go through an extensive quoting and sales process, often through a computer-equipment company, like Dell or HPE. Those vendors sell complete systems, including memory, a central processor and other parts. Even experts who want to train AI models are more likely to rent Nvidia access through a cloud provider than build their own server clusters.

Still, Nvidia’s name recognition is rapidly increasing. Among retail investors, Nvidia has emerged as the most widely held stock, according to data collected and published last month by Vanda Research.

And while the name didn’t make Interbrand’s top 100 list for 2023, the firm’s data shows its brand awareness quadrupled in the past 12 months, which will help when it’s time for the next ranking, Silverman said.

Maybe by then people will know how to say its name, a topic that’d been the source of debate on obscure gaming forums. The company pronounces it en-VID-ia.

WATCH: The ‘Magnificent Seven’ should have another good earnings season

The entire value of the S&P 500 currently stands at $45.5 trillion, according to FactSet. Tesla CEO Elon Musk claimed on Thursday that his company’s Optimus humanoid robots could eventually make the automaker worth more than half of that.

Musk, who characterized himself as “pathologically optimistic” at the 2024 annual shareholder meeting in Austin, Texas, said Tesla is embarking on not just a “new chapter” in its life, but is about to write an entirely “new book.” Optimus appears to be one of the main characters.

Tesla first revealed its plans to work on humanoid robots in 2021 at an AI Day event, trotting out a dancer in a unitard that looked like a sleek, androgynous robot.

In January, Tesla showed off Optimus robots folding laundry in a demo video that was immediately criticized by robotics engineers for being deceptive. The robots were not autonomous, but were rather being operated with humans at the controls.

At the shareholder event on Thursday, Musk didn’t divulge exactly what Optimus can do today. He suggested the robots some day will perform like R2-D2 and C-3PO in Star Wars. They could cook or clean for you, do factory work, or even teach your children, Musk suggested.

As for shareholder value, Musk said Optimus could be the catalyst for lifting Tesla’s market cap to $25 trillion someday.

Speaking to a crowd consisting mostly of fawning fanboys in an auditorium at the Gigafactory, Musk promised Tesla would move into “limited production” of Optimus in 2025 and test out humanoid robots in its own factories next year.

The company, he predicted, will have “over 1,000, or a few thousand, Optimus robots working at Tesla” in 2025.

This is all far-out stuff even for Musk, who is notorious for making ambitious promises to investors and customers that don’t pan out — from developing software that can turn an existing Tesla into a self-driving vehicle with an upload, to EV battery swapping stations.

Getting to a $25 trillion market cap would mean that Tesla would be worth about eight times Apple’s value today. The iPhone maker is currently the world’s biggest company by market cap, just ahead of Microsoft.

At Thursday’s close, Tesla was valued at about $580 billion, making it the 10th most valuable company in the S&P 500.

Musk didn’t provide a timeframe for reaching $25 trillion. He did say that autonomous vehicles could get the company to a market cap of $5 trillion to $7 trillion.

Musk said he agreed with numbers from long-time Tesla bull Cathie Wood, the CEO of ARK Invest. This week, ARK put a $2,600 price target on Tesla’s stock by 2029, betting on a commercial robotaxi business that the company has yet to enter.

Wood’s price target equals a market cap for Tesla of over $8 trillion.

Musk’s comments at the annual meeting followed the shareholder vote to reinstate the CEO’s $56 billion pay plan, five months after a Delaware court ordered the company to rescind the package. The crowd cheered when the proposal was read aloud, and when preliminary results were announced.

Taking the stage following the readout of the shareholder votes, Musk said, “I just want to start off by saying hot d—! I love you guys.”

Tesla shares have dropped 27% this year as the company reckons with a sales decline that’s tied in part to an aging lineup of electric vehicles and increased competition in China. The company has also implemented steep layoffs. Musk has encouraged investors to look past the current state of the business and more toward a future of autonomous driving, robots and artificial intelligence.

Among his boldest claims on Thursday was Musk’s declaration that Tesla had advanced so far in developing silicon that it’s surpassed Nvidia when it comes to inference, or the process that trained machine learning models use to draw conclusions from new data.

Nvidia shares have soared almost nine-fold since the end of 2022, driven by demand for its AI chips. The company is now worth about $3.2 trillion.

One concern swirling around Musk is his focus on Tesla given all of his other commitments. He owns and runs social media company X, is CEO of SpaceX, and founded The Boring Co. and Neuralink. He launched another startup, xAI, in March last year and the company recently raised $6 billion in venture funding.

Musk was asked by a shareholder at the meeting how important he is, personally, to the future of Tesla.

“I’m a helpful accelerant to that future,” he said, emphasizing his role in innovation.

He said that, when it comes to humanoid robots, other companies, including tech startups, are going after the market. Competitors include Boston Dynamics, Agility, Neura and Apptronik.

“What really matters is, can we be much faster than everyone else and our product be done a few years before theirs and be better,” Musk said.

WATCH: Tesla shareholders approve Musk’s $56 billion pay package

For years, Apple avoided using the acronym AI when talking about its products. Not anymore.

The boom in generative artificial intelligence, spawned in late 2022 by OpenAI, has been the biggest story in the tech industry of late, lifting chipmaker Nvidia to a $3 trillion market cap and causing a major shifting of priorities at Microsoft, Google and Amazon, which are all racing to add the technology into their core services.

Investors and customers now want to see what the iPhone maker has in store.

New AI features are coming at Apple’s Worldwide Developers Conference (WWDC), which takes place on Monday at Apple’s campus in Cupertino, California. Apple CEO Tim Cook has teased “big plans,” a change of approach for a company that doesn’t like to talk about products before they’re released.

WWDC isn’t typically a major investor attraction. On the first day, the company announces annual updates to its iOS, iPadOS, WatchOS and MacOS software in what’s usually a two-hour videotaped keynote launch event emceed by Cook. This year, the presentation will be screened at Apple’s headquarters. App developers then get a week of parties and virtual workshops where they learn about the new Apple software.

Apple fans get a preview of the software coming to iPhones. Developers can get to work updating their apps. New hardware products, if they appear at all, are not the showcase.

But this year, everyone will be listening for the most hyped acronym in tech.

With more than 1 billion iPhones in use, Wall Street wants to hear what AI features are going to make the iPhone more competitive against Android rivals and how the company can justify its investment in developing its own chips.

Investors have rewarded companies that show a clear AI strategy and vision. Nvidia, the primary maker of AI processors, has seen its stock price triple in the past year. Microsoft, which is aggressively incorporating OpenAI into its products, is up 28% over the past year. Apple is only up 9% over that same period, and has seen the other two companies surpass it in market cap.

“This is the most important event for Cook and Cupertino in over a decade,” Dan Ives, an analyst at Wedbush, told CNBC. “The AI strategy is the missing piece in the growth puzzle for Apple and this event needs to be a showstopper and not a shrug-the-shoulders event.”

Taking the stage will be executives including software chief Craig Federighi, who will likely address the real-life uses of Apple’s AI, whether it should be run locally or in massive cloud clusters and what should be built into the operating system versus distributed in an app.

Privacy is also a key issue, and attendees will likely want to know how Apple can deploy the data-hungry technology without compromising user privacy, a centerpiece of the company’s marketing for over half a decade.

“At WWDC, we expect Apple to unveil its long-term vision around its implementation of generative AI throughout its diverse ecosystem of personal devices,” wrote Gil Luria, an analyst at D.A. Davidson, in a note this week. “We believe that the impact of generative AI to Apple’s business is one of the most profound in all of technology, and unlike much of the innovation in AI that’s impacting the developer or enterprise, Apple has a clear opportunity to reach billions of consumer devices with generative AI functionality.”

Last month, OpenAI revealed a voice mode for its AI software called ChatGPT-4o.

In a short demo, OpenAI researchers held an iPhone and spoke directly to the bot inside the ChatGPT app, which was able to do impressions, speak fluidly and even sing. The conversation was snappy, the bot gave advice and the voice sounded like a human. Further demos at the live event showed the bot singing, teaching trigonometry, translating and telling jokes.

Apple users and pundits immediately understood that OpenAI had demoed a preview of what Apple’s Siri could be in the future. Apple’s voice assistant debuted in 2011 and since has gained a reputation for not being useful. It’s rigid, only able to answer a small proportion of well-defined queries, partially because it’s based on older machine learning techniques.

Apple could team up with OpenAI to upgrade Siri next week. It’s been discussing licensing chatbot technology from other companies, too, including Google and Cohere, according to a report from The New York Times.

Apple declined to comment on an OpenAI partnership.

One possibility is that Apple’s new Siri won’t compete directly with fully featured chatbots, but will improve its current features, and toss off queries that can only be answered by a chatbot to a partner. It’s close to how Apple’s Spotlight search and Siri work now. Apple’s system tries to answer the question, but if it can’t, it turns to Google. That agreement is part of a deal worth $18 billion per year to Apple.

Apple might also shy away from a full-throated embrace of an OpenAI partnership or chatbot. One reason is that a malfunctioning chatbot could generate embarrassing headlines, and could undermine the company’s emphasis on user privacy and personal control of user data.

“Data security will be a key advantage for the company and we expect them to spend time talking about their privacy efforts during the WWDC as well,” Citi analyst Atif Malik said in a recent note.

OpenAI’s technology is based on web scraping, and ChatGPT user interactions are used to improve the model itself, a technique that could violate some of Apple’s privacy principles.

Large language models like OpenAI’s still have problems with inaccuracies or “hallucinations,” like when Google’s search AI said last month that President Barack Obama was the first Muslim president. OpenAI CEO Sam Altman recently found himself in the middle of a thorny societal debate about deepfakes and deception when he denied accusations from actress Scarlett Johansson that OpenAI’s voice mode had ripped off her voice. It’s the kind of conflict that Apple executives prefer to avoid.

Outside of Apple, AI has become reliant on big server farms using powerful Nvidia processors paired with terabytes of memory to crunch numbers.

Apple, by contrast, wants its AI features to run on iPhones, and iPads, and Macs, which operate on battery power. Cook has highlighted Apple’s own chips as superior for running AI models.

“We believe in the transformative power and promise of AI, and we believe we have advantages that will differentiate us in this new era, including Apple’s unique combination of seamless hardware, software, and services integration, groundbreaking Apple Silicon with our industry-leading neural engines, and our unwavering focus on privacy,” Cook told investors in May on an earnings call.

Samik Chatterjee, an analyst at JPMorgan, wrote in a note this month that, “We expect Apple’s presentation at WWDC keynote to be focused on the features and the on-device capabilities as well as the GenAI models being run on-device to enable those features.”

In April, Apple published research about AI models it calls “efficient language models” that would be able to run on a phone. Microsoft is also publishing research on the same concept. One of Apple’s “OpenELM” models has 1.1 billion parameters, or weights — far smaller than OpenAI’s 2020 GPT-3 model which has 175 billion parameters, and smaller even than the 70 billion parameters in one version of Meta’s Llama, which is one of the most widely used language models.

In the paper, Apple’s researchers benchmarked the model on a MacBook Pro laptop running Apple’s M2 Max chip, showing that these efficient models don’t necessarily need to connect to the cloud. That can improve response speed, and provide a layer of privacy, because sensitive questions could be answered on the device itself, rather than being sent back to Apple servers.

Some of the features built into Apple’s software could include providing users a summary of their missed text messages, image generation for new emojis, code completing in the company’s development software Xcode, or drafting email responses, according to Bloomberg.

Apple could also decide to load up its M2 Ultra chips in its data centers to process AI queries that need more horsepower, Bloomberg reported.

WWDC won’t strictly be about AI.

The company has more than 2.2 billion devices in use, and customers want improved software and new apps.

One potential upgrade could be Apple’s adoption of RCS, an improvement to the older system of text messaging known as SMS. Apple’s messages app diverts texts between iPhones to its own iMessage system, which displays conversations as blue bubbles. When an iPhone texts an Android phone, the bubble is green. Many features such as typing notifications aren’t available.

Google led development of RCS, adding encryption and other features to text messaging. Late last year Apple confirmed that it would add support for RCS alongside iMessage. The debut of iOS 18 would be the logical time to show its work.

The conference will also be the first anniversary of Apple’s reveal of the Vision Pro, its virtual and augmented reality headset, which was released in the U.S. in February. Apple could announce its expansion to more countries, including China and the U.K.

Apple said in its WWDC announcement that the Vision Pro would be in the spotlight. Vision Pro is currently on the first version of its operating system, and core features, such as its Persona videoconferencing simulation, are still in beta.

For users with a Vision Pro, Apple will offer some of its virtual sessions at the event in a 3D environment.

AUSTIN — For five years, bitcoin miner Core Scientific has quietly been diversifying out of mining and into artificial intelligence, a market that will require immense amounts of power to handle the training of AI models and the massive workloads that follow.

The move is no longer a secret.

On Monday, Core Scientific announced a 12-year deal with cloud provider CoreWeave to provide infrastructure for use cases like machine learning. Core Scientific said the agreement, which expands upon an existing partnership between the two companies, will add revenue of more than $3.5 billion over the course of the contract.

CoreWeave, backed by Nvidia, rents out graphics processing units (GPUs), which are needed for training and running AI models. CoreWeave was valued at $19 billion in a funding round last month. Core Scientific will deliver about 200 megawatts of infrastructure to CoreWeave’s operations.

Core Scientific, which emerged from bankruptcy in January, has been mining a mix of digital assets since 2017. The company began to diversify into other services in 2019.

“The best way to think about bitcoin mining facilities is that we are essentially power shells to the data center industry,” Core Scientific CEO Adam Sullivan told CNBC.

Sullivan jumped into the role of CEO while the company was still in the throes of bankruptcy, which resulted from the collapse of bitcoin in 2022. Since then, the former investment banker has settled debts with angry lenders and further beefed up the company’s non-bitcoin business as it reentered the public market.

Though Core is up more than 40% since relisting earlier this year, its market capitalization of around $865 million is significantly lower than its valuation of $4.3 billion in July 2021.

Demand for AI compute and infrastructure surged after OpenAI unveiled ChatGPT in Nov. 2022, setting off a rush of investment in AI models and startups. Meanwhile, Core Scientific and other miners like Bit Digital, Hive, Hut 8, and TeraWulf have been looking to bolster their revenue streams after the so-called bitcoin halving in April cut rewards paid out to bitcoin miners by 50%.

Many have been retrofitting their massive facilities to meet the needs of the market.

“Bitcoin miners, often stationed in energy-secure and energy-intensive data centers, find these facilities ideal for AI operations as well,” said James Butterfill, head of research at digital asset firm CoinShares.

Butterfill said the the overlap is leading to a competition for rack space between bitcoin mining and AI activities. While AI operations require up to 20 times the capital expenditure of bitcoin mining, they’re more profitable, according to a report from CoinShares.

“The introduction of AI activities leads to increased depreciation and amortization, which can enhance gross profit margins,” Butterfill said.

According to CoinShares, Bit Digital derives 27% of its revenue from AI. Hut 8 generates 6% of sales from AI, and Hive, which has data centers in Canada and Sweden, gets 4% of its revenue from these services.

Hut 8 said in its first-quarter earnings report that it had purchased its first batch of 1,000 Nvidia GPUs and secured a customer agreement with a venture-backed AI cloud platform as part of its expansion into new technologies offering higher returns.

“We finalized commercial agreements for our new AI vertical under a GPU-as-a-service model, including a customer agreement which provides for fixed infrastructure payments plus revenue sharing,” said Hut 8 CEO Asher Genoot.

Genoot added that the company expects to begin generating revenue in the second half of the year at an annual rate of about $20 million.

Bit Digital had 251 servers actively generating revenue from its first AI contract as of the end of April, and the company said it earned about $4.1 million of revenue from the operation that month.

Iris Energy expects to generate between $14 million and $17 million in annual revenue from its AI cloud services. Core Scientific’s expanded arrangement with CoreWeave is expected to produce annual revenue of $290 million.

“While we intend to remain one of the largest and most productive bitcoin miners, we expect to have a diversified business model and more predictable cash flows,” Sullivan said.

Bitcoin’s volatility has made mining a challenging business.

Though bitcoin is currently up more than 150% in the past year to around $69,000, the bear market of 2022 sent many miners into bankruptcy or forced them to shutter altogether.

Pivoting to AI isn’t as simple as repurposing existing infrastructure and machines, because high-performance computing (HPC) data center requirements are different, as are the needs of the data network.

“Besides transformers, substations, and some switch gear nearly all infrastructure miners currently have would need to be bulldozed and built from the ground up to accommodate HPC,” Needham analysts wrote in a report on May 30.

The rigs used to mine bitcoin are called Application-Specific Integrated Circuits (ASICs). They’re built specifically for crypto mining and can’t be used to do other things.

Needham estimates that HPC data centers run at $8 million to $10 million per megawatt in capex, excluding GPUs, whereas bitcoin mining sites typically operate at $300,000 to $800,000 per megawatt in capex, not including ASICs.

Core’s Sullivan says there’s a lot of synergy between the two businesses.

“One of the most exciting parts about the bitcoin mining business is we have access to large amounts of power across the United States with access to fiber lines,” he said.

Beyond its partnership with CoreWeave, Core Scientific has also announced that over the next three to four years, it’s working to convert 500 megawatts of its bitcoin mining infrastructure across the country to HPC data centers.

Sullivan said the retrofit is manageable because the company owns and controls all of its data center infrastructure.

“There are components that we have to purchase to retrofit for HPC, but it is things that we can easily acquire,” he said.

In the next one to two years, Needham analysts estimate that large publicly traded bitcoin miners are expected to more than double power capacity, including both their mining and HPC business expansion plans.

Clean energy is a popular choice because it’s the cheapest power source in many markets. Miners at scale compete in a low-margin industry, where their only variable cost is typically energy, so they’re incentivized to migrate to the world’s cheapest sources of power. An industry report estimates the bitcoin network is 54.5% powered by sustainable electricity.

The Electric Power Research Institute estimates that data centers could take up to 9% of the country’s total electricity consumption by 2030, up from around 4% in 2023. Tapping into nuclear energy is seen by many as the answer to meeting that demand.

TeraWulf powers its mining sites with nuclear energy, and is looking to get into machine learning. So far, the firm has two megawatts dedicated to HPC capacity, though it has plans to transition its energy infrastructure toward AI and HPC.

OpenAI CEO Sam Altman told CNBC last year that he’s a big believer in nuclear when it comes to serving the needs of AI workloads.

“I don’t see a way for us to get there without nuclear,” Altman said. “I mean, maybe we could get there just with solar and storage. But from my vantage point, I feel like this is the most likely and the best way to get there.”

WATCH: Nvidia closes at another record high

Nvidia reported fourth fiscal quarter earnings that beat Wall Street’s forecast for earnings and sales, and said revenue during the current quarter would be better than expected, even against elevated expectations for massive growth.

Nvidia shares rose about 10% in extended trading.

Here’s what the company reported compared with what Wall Street was expecting for the quarter ending in January, based on a survey of analysts by LSEG, formerly known as Refinitiv:

• Earnings per share: $5.16 adjusted vs. $4.64 expected
• Revenue: $22.10 billion vs. $20.62 billion expected

Nvidia said it expected $24.0 billion in sales in the current quarter. Analysts polled by LSEG were looking for $5.00 per share on $22.17 billion in sales. 

Nvidia has been the primary beneficiary of the recent technology industry obsession with large artificial intelligence models, which are developed on the company’s pricey graphics processors for servers.

Nvidia CEO Jensen Huang addressed investor fears that the company may not be able to keep up this growth or level of sales for the whole year on a call with analysts.

“Fundamentally, the conditions are excellent for continued growth” in 2025 and beyond, Huang told analysts. He says demand for the company’s GPUs will remain high due to generative AI and an industry-wide shift away from central processors to the accelerators that Nvidia makes.

Nvidia reported $12.29 billion in net income during the quarter, or $4.93 per share, up 769% versus last year’s $1.41 billion or 57 cents per share. 

Nvidia’s total revenue rose 265% from a year ago, based on strong sales for AI chips for servers, particularly the company’s “Hopper” chips such as the H100, it said.

“Strong demand was driven by enterprise software and consumer internet applications, and multiple industry verticals including automotive, financial services and health care,” the company said in commentary provided to investors.

Those sales are reported in the company’s Data Center business, which now comprises the majority of Nvidia’s revenue. Data center sales were up 409% to $18.40 billion. Over half the company’s data center sales went to large cloud providers.

Nvidia said its data center revenue was hurt by recent U.S. restrictions on exporting advanced AI semiconductors to China.

“We understood what the restrictions are, reconfigured our products in a way that is not software hackable in any way, and that took some time so we reset our product offering to China,” Huang said. “Now we’re sampling to customers in China.”

Nvidia Chief Financial Officer Colette Kress said that while the company had improved supply of its AI GPUs, it still expected them to be in short supply, especially the next-generation chip, called B100, expected to ship later this year.

“We are delighted that supply of Hopper architecture products is improving,” Kress said on a call with analysts. “Demand for Hopper remains very strong. We can expect our next-generation products to be supply constrained as demand far exceeds supply.”

“Whenever we have new products, as you know, it ramps from zero to a very large number and you can’t do that overnight,” Huang said.

The company’s gaming business, which includes graphics cards for laptops and PCs, was merely up 56% year over year to $2.87 billion. Graphics cards for gaming used to be Nvidia’s primary business before its AI chips started taking off, and some of Nvidia’s graphics cards can be used for AI.

Nvidia’s smaller businesses did not show the same meteoric growth. Its automotive business declined 4% to $281 million in sales, and its OEM and other business, which includes crypto chips, rose 7% to $90 million. Nvidia’s business making graphics hardware for professional applications rose 105% to $463 million.

A year ago, there was little holiday cheer at Affirm. The point-of-sale lender was confronting rising interest rates, recession fears and weakening consumer spending. Affirm shares ended 2022 down 90%, wiping out billions of dollars in market value.

Affirm investors are wrapping up 2023 in a much different mood.

The stock skyrocketed 430% in 2023, as of Wednesday’s close, outperforming all other U.S. tech companies valued at $5 billion or more. The next-best performer was Coinbase, which shot up 423% largely because of bitcoin’s rebound.

With the Federal Reserve setting the stage for interest rate cuts in the year ahead and more retailers signing onto Affirm’s buy now, pay later offerings, or BNPL, fear of a doomsday scenario for the company has faded. Shares of Affirm got a big boost in November after the company inked an expanded partnership with Amazon, and BNPL purchases hit an all-time high on Cyber Monday.

“The expectation was the consumer was going to be toast, unemployment was going to pick up and higher interest rates would destroy everything, and the exact opposite has happened on all fronts,” said Tom Hayes, chairman at Great Hill Capital, which doesn’t have a position in the stock. “So that’s why you have a scenario where Affirm can start to perform.”

Created in 2012 by PayPal co-founder Max Levchin, Affirm is competing with companies including Klarna, Block’s Afterpay and Zip in the burgeoning BNPL market. Shoppers who choose to pay with a BNPL service split their purchase into four or more installments typically over a period of three months to a year, without accruing compounding interest. The lenders make money from interest payments and by charging merchants fees to offer their lending services.

Retailers benefit by giving consumers another option for purchasing a skateboard, watch or a gift for a family member, and one that can come with less sticker shock, resulting in fewer abandoned carts.

Affirm made its public market debut on the Nasdaq in January 2021, as the Covid-19 pandemic was driving a surge in adoption of BNPL services. Shoppers flush with stimulus checks used the small loans when buying clothes, electronics and Peloton exercise bikes, which at one point accounted for 30% of Affirm’s revenue. Online storefronts rushed to add BNPL as an option at checkout.

But by early 2022, Affirm’s share price had fallen more than 60% from its 2021 peak. The rest of the year was just as gloomy as soaring interest rates made it more expensive for Affirm to borrow money to fund installment loans. In February 2023, Affirm cut 19% of its workforce, and executives said macro headwinds and “negative consumer sentiment” would likely persist for the remainder of the fiscal year.

As it turns out, they were overly bearish.

Affirm shares started climbing higher in August after the company’s fiscal fourth-quarter earnings report. The company picked up new merchant deals in sectors beyond retail, such as travel, wireless, ticketing and health care. The stock has more than doubled in the fourth quarter, boosted by an announcement last week that Affirm would offer BNPL loans at Walmart‘s self-checkout kiosks.

Even with their dramatic bounce back, Affirm shares are about 70% below their high in November 2021.

Heading into 2024, BNPL lenders face cooling inflation and an optimistic interest rate environment.

Dan Dolev, managing director at Mizuho Securities, said Affirm is in a strong position to retain users. He pointed to new merchant deals and the expanding market for BNPL offerings in physical stores. Affirm says 16.9 million people have used its services, and the company counts more than 266,000 merchant partners.

Affirm is eyeing international expansion and has launched a debit card that lets customers pay upfront or in installments. Affirm announced at its investor day last month that it plans to introduce a spending account tied to its debit card that will allow for ATM access and direct deposit capability.

“The next year or two years are going to be something very different,” said Dolev, who has a buy rating on Affirm shares. “Now they’ve got the brand, and what are they going to do with it? They’re going to turn it into a full-fledged financial services firm.”

Hayes sees more cause for skepticism. He said Affirm faces an “uphill battle” competing with entrenched operators such as PayPal and Block, as well as credit card companies such as American Express, Citi and Chase that have jumped into installment loans.

“It’s David against Goliath, and Goliath is going to win,” Hayes said.

Hayes said Affirm is going down a similar path to online lender SoFi, trying to “have a thousand different projects, and say we’re as big as JPMorgan, but at the end of the day, it’s just simply not going to work.”

BNPL lenders also face heightened risk of users failing to make payments on time. A March report by the Consumer Financial Protection Bureau found BNPL users were on average more likely to have higher levels of credit card debt. BNPL borrowers also tend to have lower credit scores, the CFPB said, with an average score in the subprime range of 580 to 669.

An Affirm spokesperson didn’t provide a comment for this story but pointed to past comments from company executives.

“As our network grows, our moats get deeper,” Levchin said at the company’s investor forum in November. “We get more data. We underwrite more transactions. We meet more people.”

Affirm’s defaults remain low by industry standards. Average delinquency rates for peers, such as LendingClub, SoFi, Upstart and OneMain Financial, increased from 5.7% to 6.3% between January and November, while Affirm’s delinquency rate fell from 2.8% to 2.6%, Jefferies analysts wrote in a report last month.

Affirm says it bases loan decisions on a variety of data points in addition to a user’s credit score.

“Our process involves looking at credit report data, but could also involve some Affirm-specific stuff, like what we know about the merchant and the thing they are about to sell you,” Levchin said in a release last year.

As BNPL adoption grows, regulators are keeping a close eye on the space. Last week, three U.S. senators penned a letter to the CFPB urging the agency to monitor the uptick in BNPL usage during the holidays, saying it could leave consumers overextended. The CFPB announced in September 2022 that it would subject BNPL to greater oversight, in line with credit card companies.

Wells Fargo issued a report earlier this month that described BNPL loans as “phantom debt” that may be lulling “consumers into a false security in which many small payments add up to one big problem.” As it stands today, the industry is “not a major problem for consumer spending yet,” Wells Fargo economists Tim Quinlan and Shannon Seery Grein wrote.

Since BNPL loans are not currently reported to major credit reporting agencies, they wrote, there is “no way to know when this phantom debt could create substantial problems for the consumer and the broader economy.”

WATCH: Payments trends for 2024

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It’s not just human life that will be remade by the rapid advance in generative artificial intelligence. NPCs (non-playable characters), the figures who populate generated worlds in video games but have to date largely run on limited scripts — think the proprietor of the store you enter — are being tested as one of the first core gaming aspects where AI can improve gameplay and immersiveness. A recent partnership between Microsoft Xbox and Inworld AI is a prime example.

Better dialogue is just the first step. “We’re creating the tech that allows NPCs to evolve beyond predefined roles, adapt to player behavior, learn from interactions, and contribute to a living, breathing game world,” said Kylan Gibbs, chief product officer and co-founder of Inworld AI. “AI NPCs are not just a technological leap. They’re a paradigm shift for player engagement.”

It’s also a big opportunity for the gaming companies and game developers. Shifting from scripted dialogue to dynamic player-driven narratives will increase immersion in a way that drives replayability, retention, and revenue.

The interaction between powerful chips and gaming has for years been part of the success story at Nvidia, but there is now a clear sense in the gaming industry that it is just beginning to get to the point where AI will take off, after some initial uncertainty. 

“All developers are interested in how artificial intelligence can impact game development process,” John Spitzer, vice president of developer and performance technology at Nvidia, recently told CNBC, and he cited powering non-playable characters as a key test case. 

It’s always been true that technological limits and possibilities overdetermine the gaming worlds developers can create. The technology behind AI NPCs, Gibbs says, will become a catalyst for a new era of storytelling, creative expression, and innovative gameplay. But much of what is to come will be “games we have yet to imagine,” he said.

Bing Gordon, an Inworld advisor and former chief creative officer at Electronic Arts, said the biggest advancements in gaming in recent decades have been through improvements in visual fidelity and graphics. Gordon, who is now chief product officer at venture capital firm Kleiner Perkins and serves on the board of gaming company Take-Two Interactive, believes AI will remake the world of both the gamer and game designer.

“AI will enable truly immersive worlds and sophisticated narratives that put players at the center of the fantasy,” Gordon said. “Moreover, AI that influences fundamental game mechanics has the potential to increase engagement and draw players deeper into your game.”  

The first big opportunity for gen AI may be in gaming production. “That’s where we expect to see a major impact first,” said Anders Christofferson, a partner within Bain & Company’s media & entertainment practice.

In other professional tasks, such as creating presentations using software like PowerPoint and first drafts of speeches, gen AI is already doing days of work in minutes. Initial storyboard design and NPC dialogue creation are made for gen AI, and that will free up developer time to focus on the more immersive and creative parts of game making, Christofferson said.

Creating unpredictable worlds

A recent Bain study noted that AI is already taking on some tasks, including preproduction and planning out of game content. Soon it will play a larger role in developing characters, dialogue, and environments. Gaming executives, Bain’s research shows, expect AI to manage more than half of game development within five years to a decade. This may not lead to lower production costs — blockbuster games can run up total development costs of $1 billion — but AI will allow games to be delivered more quickly, and with enhanced quality.

Ultimately, the proliferation of gen AI should allow the development process of games to include the average gamer in content creation. This means that more games will offer what Christofferson calls a “create mode” allowing for increased user-generated content — Gibbs referred to it as “player-driven narratives.” 

The current human talent shortage, a labor issue that exists across the software engineering space, isn’t something AI will solve in the short-term. But it may free developers up to put more time into creative tasks and learn how best to use the new technology as they experiment. A recent CNBC study found that across the labor force, 72% of workers who use AI say it makes them more productive, consistent with research Microsoft has conducted on the impact of its Copilot AI in the workplace.

“GenAI is very nascent in gaming and the emerging landscape of players, services, etc. is very dynamic – changing by the day,” Christofferson said. “As with any emerging technologies, we expect lots of learning to take place regarding GenAI over the next few years.”

Given how much change is taking place in gaming, it may simply be too difficult to forecast AI’s scale at the moment, says Julian Togelius, associate professor of computer science and engineering at New York University. He summed up the current state of AI implementation as a “medium-size deal.”

“In the game development process, generative AI is already in use by lots of people. Programmers use Copilot and ChatGPT to help them write code, concept artists experiment with Stable Diffusion and Midjourney, and so on,” said Togelius. “There is also a big interest in automated game testing and other forms of AI-augmented QA,” he added. 

The Microsoft and Inworld partnership will test two of the key AI implications in the video game industry: design-time and assistance with narrative generation. If a game has thousands of NPCs in it, having AI generate individual backstories for each of them can save enormous development time — and having generative AI working while players interact with NPCs could also enhance gameplay.

The latter will be trickier to achieve, Togelius said. “I think this is much harder to get right, partly because of the well-known hallucination issues of LLMs, and partly because games are not designed for this,” he said. 

Hallucinations occur when large language models (LLMs) generate responses that deviate from context or rational meaning — they speak nonsensically but grammatically, about things that don’t make sense or have any relation to the given context. “Video games are designed for predictable, hand-crafted NPCs that don’t veer off script and start talking about things that don’t exist in the game world,” Togelius said.

Traditionally, NPCs behave in predictable ways that have been hand-authored by a designer or design team. Predictability, in fact, is a core tenant of the video game world and its design process. Open-ended games are thrilling because of their sense of infinite possibility, but to function reliably there is great control and predictability built into them. Unpredictability in the gaming world is a new realm, and could be a barrier to having AI gain wider use. Working out this balance will be a key to moving forward with AI.

“I think we are going to see modern AI in more and more places in games and game development very soon,” Togelius said. “And we will need new designs that work with the strengths and weaknesses of generative AI.”

Oracle shares dropped more than 9% in extended trading Monday after the software company reported fiscal second-quarter revenue and quarterly revenue guidance that fell short of Wall Street expectations.

Here’s how the company did, compared with consensus estimates from LSEG, formerly known as Refinitiv:

• Earnings per share: $1.34 per share, adjusted, vs. $1.32 per share, expected
• Revenue: $12.94 billion, vs. $13.05 billion expected

Revenue grew 5% year over year in the quarter, which ended Nov. 30, according to a statement. Net income increased 44% to $2.5 billion, or 89 cents per share, from $1.74 billion, or 63 cents a share, a year ago.

With respect to guidance, Oracle called for adjusted net income for the fiscal third quarter of $1.35 to $1.39 per share and 6% to 8% revenue growth. Analysts polled by LSEG had predicted $1.37 in adjusted earnings per share and $13.34 billion in revenue, which implies 7.6% revenue growth.

Oracle’s revenue from cloud services and license support totaled $9.64 billion, up 12% and below the StreetAccount consensus of $9.71 billion.

Revenue from cloud and on-premises licenses fell 18% to $1.18 billion, slightly lower than the $1.21 billion StreetAccount consensus.

Services revenue, at $1.37 billion, also missed consensus, which was $1.40 billion.

Oracle said cloud infrastructure revenue reached $1.6 billion during the period, up 52%. Clients included Elon Musk’s artificial intelligence startup xAI, Halliburton and Samsung.

The Musk company wanted considerably more AI chips than Oracle could supply, Oracle co-founder Larry Ellison said on a conference call with analysts. Nvidia’s graphics processing units have been in short supply across the board, and the chipmaker has been working to address the shortage.

“We did not bring up as much capacity as we could have used this past quarter, Oracle CEO Safra Catz said on the call. The company had to choose between building something small and recognizing revenue in the quarter, or going ahead with a larger buildout and waiting for capacity to become available, she said.

During the quarter, Oracle said it had picked up cloud business from larger rival Microsoft and announced that its database software will be available on Microsoft’s Azure public cloud. The company will turn on 20 data centers connected with Azure in the next few months, Oracle co-founder Larry Ellison said in the statement.

“I expect the OCI growth rate to be over 50% for a few years,” Ellison said on the conference call. OCI is the Oracle Cloud Infrastructure, the company’s answer to Microsoft Azure and the market-leading Amazon Web Services.

Also in the quarter, Oracle’s NetSuite division bought Australian company Next Technik, which makes field service software, for undisclosed terms.

Oracle shares are up about 41% so far this year, outperforming the S&P 500 index, which has gained 20% during the same period.

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Nvidia on Monday unveiled the H200, a graphics processing unit designed for training and deploying the kinds of artificial intelligence models that are powering the generative AI boom.

The new GPU is an upgrade from the H100, the chip OpenAI used to train its most advanced large language model, GPT-4. Big companies, startups and government agencies are all vying for a limited supply of the chips.

H100 chips cost between $25,000 and $40,000, according to an estimate from Raymond James, and thousands of them working together are needed to create the biggest models in a process called “training.”

Excitement over Nvidia’s AI GPUs has supercharged the company’s stock, which is up more than 230% so far in 2023. Nvidia expects around $16 billion of revenue for its fiscal third quarter, up 170% from a year ago.

The key improvement with the H200 is that it includes 141GB of next-generation “HBM3” memory that will help the chip perform “inference,” or using a large model after it’s trained to generate text, images or predictions.

Nvidia said the H200 will generate output nearly twice as fast as the H100. That’s based on a test using Meta’s Llama 2 LLM.

The H200, which is expected to ship in the second quarter of 2024, will compete with AMD’s MI300X GPU. AMD’s chip, similar to the H200, has additional memory over its predecessors, which helps fit big models on the hardware to run inference.

Nvidia said the H200 will be compatible with the H100, meaning that AI companies who are already training with the prior model won’t need to change their server systems or software to use the new version.

Nvidia says it will be available in four-GPU or eight-GPU server configurations on the company’s HGX complete systems, as well as in a chip called GH200, which pairs the H200 GPU with an Arm-based processor.

However, the H200 may not hold the crown of the fastest Nvidia AI chip for long.

While companies like Nvidia offer many different configurations of their chips, new semiconductors often take a big step forward about every two years, when manufacturers move to a different architecture that unlocks more significant performance gains than adding memory or other smaller optimizations. Both the H100 and H200 are based on Nvidia’s Hopper architecture.

In October, Nvidia told investors that it would move from a two-year architecture cadence to a one-year release pattern due to high demand for its GPUs. The company displayed a slide suggesting it will announce and release its B100 chip, based on the forthcoming Blackwell architecture, in 2024.

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Semiconductor technology company Arm reported its first post-initial public offering earnings on Wednesday that beat Wall Street expectations for sales and showed that the company’s lucrative licensing business doubled in size over the past year.

Arm shares fell over 7% in extended trading after the company’s revenue guidance was short of expectations.

Here’s how the semiconductor licensing company did versus consensus expectations by LSEG, formerly known as Refinitiv, for Arm’s second fiscal quarter ending Sept. 30:

• Earnings per share: 36 cents, adjusted
• Revenue: $806 million vs. $744.3 million expected

Arm said it was expecting earnings per share between 21 cents and 28 cents on sales of between $720 million and $800 million in the current quarter. That’s a little lighter than what Wall Street was looking for, which was 27 cents per share on revenue between $730 million and $805 million.

Arm reported a net loss of $110 million, or 11 cents per share. The company said the loss was due to more than $500 million in one-time share-based compensation triggered by the recent IPO, and that share-based compensation would land between $150 million and $250 million in future quarters.

Total revenue was up 28% on an annual basis during the quarter.

Arm’s intellectual property is in nearly every smartphone, many PCs and other miscellaneous chips. Arm says more than 7.1 billion Arm-based chips were shipped during the quarter.

It makes money through royalties, or when chipmakers pay Arm for access to build Arm-compatible chips, typically a small percentage of the final chip price. It also sells licenses to more complete chip designs, saving chipmakers time and effort, which are recorded as licensing revenue.

Arm royalty revenue was $418 million, a 5% decline from the same period last year. But Arm licensing sales were $388 million, up 106% from the same period last year. It’s a sign that Arm may be able to sell increasing amounts of technology to its current customers, which is a key metric watched by analysts.

Arm attributed licensing sales to multiple long-term agreements with technology companies, suggesting the segment’s growth could continue in future quarters, but warned that the broader economy could affect future licensing growth.

Arm went public in an IPO in September. Before that, it was owned by SoftBank, which reached a deal to sell the firm to Nvidia before the transaction was scuttled by regulators in 2022. It was founded in 1990 to develop technology for low-power chips.

Arm said that firms including Google, Meta and Nvidia were developing artificial intelligence-capable chips with its technology.

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