Samsung logo displayed on a glass door at the company’s Seocho building in Seoul on July 7, 2022. Samsung Electronics has begun applications for tax breaks for 11 potential chip plants in Texas adding up to investments of about $192 billion, according to documents filed with Texas authorities.
The South Korean chip giant claimed the HBM3E 12H “raises both performance and capacity by more than 50%.”
“The industry’s AI service providers are increasingly requiring HBM with higher capacity, and our new HBM3E 12H product has been designed to answer that need,” said Yongcheol Bae, executive vice president of memory product planning at Samsung Electronics.
“This new memory solution forms part of our drive toward developing core technologies for high-stack HBM and providing technological leadership for the high-capacity HBM market in the AI era,” said Bae.
Samsung Electronics is the world’s largest maker for dynamic random-access memory chips, which are used in consumer devices such as smartphones and computers.
Generative AI models such as OpenAI’s ChatGPT require large numbers of high-performance memory chips. Such chips enable generative AI models to remember details from past conversations and user preferences in order to generate humanlike responses.
During a call with analysts, Nvidia CEO Jensen Huang said the company may not be able to maintain this level of growth or sales for the whole year.
“As AI applications grow exponentially, the HBM3E 12H is expected to be an optimal solution for future systems that require more memory. Its higher performance and capacity will especially allow customers to manage their resources more flexibly and reduce total cost of ownership for datacenters,” said Samsung Electronics.
Samsung said it has started sampling the chip to customers and mass production of the HBM3E 12H is planned for the first half of 2024.
“I assume the news will be positive for Samsung’s share price,” SK Kim, executive director of Daiwa Securities, told CNBC.
“Samsung was behind SK Hynix in HBM3 for Nvidia last year. Also, Micron announced mass production of 24GB 8L HBM3E yesterday. I assume it will secure leadership in higher layer (12L) based higher density (36GB) HBM3E product for Nvidia,” said Kim.
In September, Samsung secured a deal to supply Nvidia with itshigh-bandwidth memory 3 chips, according to a Korea Economic Daily report, which cited anonymous industry sources.
The report also said that SK Hynix, South Korea’s second-biggest memory chipmaker, was leading the high-performance memory chip market. SK Hynix was previously known as the sole mass producer of HBM3 chips supplied to Nvidia, the report said.
Samsung said the HBM3E 12H has a 12-layer stack, but applies advanced thermal compression non-conductive film which allows the 12-layer products to have the same height specification as 8-layer ones to meet current HBM package requirements. The result is a chip that packs more processing power, without increasing its physical footprint.
“Samsung has continued to lower the thickness of its NCF material and achieved the industry’s smallest gap between chips at seven micrometers (µm), while also eliminating voids between layers,” said Samsung. “These efforts result in enhanced vertical density by over 20% compared to its HBM3 8H product.”
The slump in stocks can partly be traced to a turnaround in sentiment regarding artificial intelligence. Tech behemoths such as Nvidia, Broadcom and Oracle slumped, with the last losing more than one-third in value since it rocketed 36% in September.
Investors, it seems, are growing worried over the high valuations of tech names, as well as the gigantic amount of capital expenditure they are committing to — with some, like Oracle, having to take on debt to fulfil those obligations.
Uncertainty over an interest rate cut in December is also putting a downer on Wall Street. It’s a coin toss as to whether the U.S. Federal Reserve will ease monetary policy then, according to the CME FedWatch tool. That’s a huge difference from a month ago, when traders were pricing in a 95.5% chance of a December cut.
Not having October’s employment and inflation numbers, and possibly never getting them, means the Fed lacks visibility into the state of the economy — and whether it should try to support the labor market or continue reining in inflation.
After all, flying blind makes it hard to see where you’ll land. As of now, that applies both to the Fed and investors trying to navigate the still-hazy ambitions of tech companies.
What you need to know today
And finally…
Tan Su Shan, chief executive officer of DBS Group Holdings Ltd., speaking at the Singapore Fintech Festival in Singapore, on Nov. 12, 2025.
“The proliferation of generative AI has been transformative for us,” DBS CEO Tan Su Shan told CNBC on the sidelines of Singapore Fintech Week. She adding that the company was experiencing a “snowballing effect” of benefits thanks to machine learning.
Tan expects AI adoption to bring DBS an overall revenue bump of more than 1 billion Singapore dollars (about $768 million) this year, compared to SG$750 million in 2024. That assessment is based on about 370 AI use cases powered by over 1,500 models throughout its business.
LISBON, Portugal — Top tech executives told CNBC they’re concerned about a bubble forming in the artificial intelligence sector, underscoring growing unease within the industry over soaring valuation.
In recent weeks, markets have been reckoning with the notion that too much capital is pouring into the AI boom, clouding the outlook on revenue and actual profit and putting high valuations into question.
Up to now, warnings around overstretched valuations have mostly come from investors and leaders in the world of finance. Goldman Sachs’ David Solomon and Morgan Stanley’s Ted Pick have warned of potential corrections as valuations of some major tech firms reached historic highs.
The concerns have been crystallized by famed ‘Big Short’ investor Michael Burry, who this week accused major AI infrastructure and cloud providers, or ‘hyperscalers’ of understating depreciation expenses on chips. Burry warned that profits at the likes of Oracle and Meta may be vastly overstated. He recently disclosed put options that bet against Nvidia and Palantir.
However, CEOs of companies who are themselves developing AI, expressed their concerns this week during interviews with CNBC at the Web Summit tech conference in Lisbon.
“I think the evaluations are pretty exaggerated here and there, and I think there is signs of a bubble on the horizon,” Jarek Kutylowski, CEO of German AI firm DeepL, told CNBC on Tuesday.
The sentiment was echoed by Picsart CEO Hovhannes Avoyan.
“We see lots of AI companies raising … tremendous valuations … without any revenue,” Avoyan told CNBC on Tuesday, adding that it is a “concern.”
The market values smaller startups with “just some noise and vibe revenue,” he said, referring to companies being backed even though they have minimal sales.
Vibe revenue is a play on “vibe coding,” a term that refers to using AI to code without needing deep technical expertise.
AI demand growing
Even with concerns over valuations, the technology industry remains bullish on the long term potential of AI.
Lyft CEO David Risher said there are reasons to be optimistic given the potential impact of AI but acknowledged the risks.
“Let’s be clear, we are absolutely in a financial bubble. There is no question, right? Because this is incredible, transformational technology. No one wants to be left behind.”
Risher went on to argue that there is a difference between the financial bubble and the industrial outlook.
“The data centers and all the model creation, all of that is going to have a long, long life, because it’s transformational. It makes people’s lives easier. It makes people’s lives better… On the other hand, you know, the financial side, it’s a little risky right now.”
The tech CEOs also addressed their outlook on AI demand for 2026 from businesses, as investors look for any clues as to what this will look like.
“I think there’s a lot of demand, and there’s a lot of interest. I think everybody understands that AI can do magical things to businesses, and… we can all operate on another level when it comes to efficiency,” Kutylowski said.
Still, businesses are “strugging in adopting” AI. “We’re going to get further, but I don’t think we’re that we’re going to be in a place where we can say, like every enterprise, every organization, has it figured out totally,” Kutylowski said.
DeepL’s core product is an AI translation tool but it recently launched a more general purpose “agent” designed to be able to carry out tasks on behalf of employees.
Francois Chadwick, the chief financial officer of Cohere, a company that is also focused on enterprise AI, told CNBC on Tuesday that “demand is definitely there.”
$4 trillion capex outlook
Despite the concerns over overstretched valuations and huge capex spend, the investment into artificial intelligence doesn’t appear to be slowing down. A report from venture capital group Accel released this week showed that the buildout of new AI data center capacity is forecast to reach 117 gigawatts by 2030 which translates into about $4 trillion worth of capital expenditure over the next 5 years.
About $3.1 trillion worth of revenue is required to pay back that capex, according to the Accel report.
Already this year, there have been a slew of deals worth billions announced by the likes of Nvidia and OpenAI as they look to develop data center capacity around the world in a bid to keep up with demand.
Philippe Botteri, a partner at Accel, said that three major factors will drive that revenue — more powerful AI models that require capacity to be trained, the use of new AI services and the “agentic revolution in the enterprise.”
“Agentic” is often a term used to describe a type of AI tool that can automatically carry out tasks on behalf of users.
But not everyone believes that the large amount of spending is necessary.
Ben Harburg, managing partner at Novo Capital says the figures being discussed by large tech firms for future investment may be overblown.
“We hear these crazy headline numbers about how much energy is going to be needed, how many chips are going to be needed, although, again, I think that there is probably more of a bubble brewing there than on kind of the front end, the actual product front,” Harburg told CNBC on Tuesday.
“I think we’re starting to realize that there’s been probably over exuberance around data centers. Even Sam [Altman], I think, would privately admit that they need fewer chips than they originally set out, they need less capital than they originally set out. They need less energy than they originally set out.”
Tan Su Shan, chief executive officer of DBS Group Holdings Ltd., speaking at the Singapore Fintech Festival in Singapore, on Nov. 12, 2025.
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SINGAPORE – Amid fears of an artificial intelligence bubble, much has been made of recent reports suggesting that AI has yet to generate returns for companies investing billions into adopting the tech.
But that’s not what the chief executive of Southeast Asia’s largest bank is seeing — she says her firm is already reaping the rewards of its AI initiatives, and it’s only just the beginning.
“It’s not hope. It’s now. It’s already happening. And it will get even better,” DBS CEO Tan Su Shan told CNBC on the sidelines of Singapore Fintech Week, when asked about the promise of AI adoption.
DBS has been working to implement artificial intelligence across its bank for over a decade, which helped prepare its internal data analytics for recent waves of generative and agentic AI.
Agentic AI is a type of artificial intelligence that relies on data to proactively make independent decisions, plan and execute tasks autonomously, with minimal human oversight.
Tan expectsAI adoption to bring DBS an overall revenue bump of more than 1 billion Singapore dollars (about $768 million) this year, compared to SG$750 million in 2024. That assessment is based on about 370 AI use cases powered by over 1,500 models throughout its business.
“The proliferation of generative AI has been transformative for us,” Tan said, adding that the company was experiencing a “snowballing effect” of benefits thanks to machine learning.
A major area in which DBS has applied AI is in its financial services to institutional clients, with AI used to collect and leverage data for clients in order to better contextualize and personalize offerings.
According to Tan, this has resulted in “faster and more resilient” teams. The CEO believes that these uses of AI have contributed to a recent uptick in the bank’s deposit growth as compared to competitors’.
The company also recently launched a newly enhanced AI-powered assistant for corporate clients known as “DBS Joy,” which assists clients with unique corporate banking queries around the clock.
ROI concerns
Despite Tan’s strong convictions about AI, recent evidence suggests that many companies are struggling to turn their AI investments into tangible profits.
MIT released a report in July that found 95% of 300 publicly disclosed AI initiatives, encompassing generative AI investments of $30–$40 billion, had failed to achieve real returns.
However, at least in the banking sector, there are signs that the tides are turning.
While DBS doesn’t differentiate spending in generative AI from other in-house investments, other major banks have recently offered this comparison.
JPMorgan Chase CEO Jamie Dimon stated in an interview with Bloomberg TV last month that the bank is already breaking even on its approximately $2 billion of annual investments in AI adoption. That represents “just the tip of the iceberg,” he added.
Those expectations are shared by DBS, which plans to continue to accelerate its AI development to become an AI-powered bank.
The ultimate goal, according to Tan, is for its generative AI to develop into a trusted financial advisor for clients, including retail users who are expected to interact with personalized AI agents through the DBS banking app.
The bank already has over 100 AI algorithms that analyze users’ data to provide them with personalized “nudges,” such as alerts on incoming shortfalls, product recommendations, and other insights.
Continued AI investments
While DBS may already be reaping rewards from its AI adoption, Tan acknowledged that it will require continued investments, not only in capital, but in the time needed to reskill employees.
The company has launched several AI reskilling initiatives across departments this year and has even deployed a generative AI-powered coaching tool to support these efforts.
This will help the company automate mundane work and refocus its staff on building and maintaining human-to-human relationships with customers, rather than reducing headcount, Tan said.
“We’re not freezing hiring, but it does mean reskilling. And that’s a journey. It’s a never-ending journey … a constant evolution.”