Alphabet’s recent market performance has been driven by investor confidence in the company’s ability to compete with OpenAI’s ChatGPT, as well as its development of specialized chips for AI that can compete with Nvidia’s. Nvidia recently reached a world-first $5 trillion valuation due to making GPUs that can accelerate the matrix math at the heart of AI computations.
Despite acknowledging that no company would be immune to a potential AI bubble burst, Pichai argued that Google’s unique position gives it an advantage. He told the BBC that the company owns what he called a “full stack” of technologies, from chips to YouTube data to models and frontier science research. This integrated approach, he suggested, would help the company weather any market turbulence better than competitors.
Pichai also told the BBC that people should not “blindly trust” everything AI tools output. The company currently faces repeated accuracy concerns about some of its AI models. Pichai said that while AI tools are helpful “if you want to creatively write something,” people “have to learn to use these tools for what they’re good at and not blindly trust everything they say.”
In the BBC interview, the Google boss also addressed the “immense” energy needs of AI, acknowledging that the intensive energy requirements of expanding AI ventures have caused slippage on Alphabet’s climate targets. However, Pichai insisted that the company still wants to achieve net zero by 2030 through investments in new energy technologies. “The rate at which we were hoping to make progress will be impacted,” Pichai said, warning that constraining an economy based on energy “will have consequences.”
Even with the warnings about a potential AI bubble, Pichai did not miss his chance to promote the technology, albeit with a hint of danger regarding its widespread impact. Pichai described AI as “the most profound technology” humankind has worked on.
“We will have to work through societal disruptions,” he said, adding that the technology would “create new opportunities” and “evolve and transition certain jobs.” He said people who adapt to AI tools “will do better” in their professions, whatever field they work in.
Despite connection hiccups, we covered OpenAI’s finances, nuclear power, and Sam Altman.
On Tuesday of last week, Ars Technica hosted a live conversation with Ed Zitron, host of the Better Offline podcast and one of tech’s most vocal AI critics, to discuss whether the generative AI industry is experiencing a bubble and when it might burst. My Internet connection had other plans, though, dropping out multiple times and forcing Ars Technica’s Lee Hutchinson to jump in as an excellent emergency backup host.
During the times my connection cooperated, Zitron and I covered OpenAI’s financial issues, lofty infrastructure promises, and why the AI hype machine keeps rolling despite some arguably shaky economics underneath. Lee’s probing questions about per-user costs revealed a potential flaw in AI subscription models: Companies can’t predict whether a user will cost them $2 or $10,000 per month.
You can watch a recording of the event on YouTube or in the window below.
“A 50 billion-dollar industry pretending to be a trillion-dollar one”
I started by asking Zitron the most direct question I could: “Why are you so mad about AI?” His answer got right to the heart of his critique: the disconnect between AI’s actual capabilities and how it’s being sold. “Because everybody’s acting like it’s something it isn’t,” Zitron said. “They’re acting like it’s this panacea that will be the future of software growth, the future of hardware growth, the future of compute.”
In one of his newsletters, Zitron describes the generative AI market as “a 50 billion dollar revenue industry masquerading as a one trillion-dollar one.” He pointed to OpenAI’s financial burn rate (losing an estimated $9.7 billion in the first half of 2025 alone) as evidence that the economics don’t work, coupled with a heavy dose of pessimism about AI in general.
Donald Trump listens as Nvidia CEO Jensen Huang speaks at the White House during an event on “Investing in America” on April 30, 2025, in Washington, DC. Credit: Andrew Harnik / Staff | Getty Images News
“The models just do not have the efficacy,” Zitron said during our conversation. “AI agents is one of the most egregious lies the tech industry has ever told. Autonomous agents don’t exist.”
He contrasted the relatively small revenue generated by AI companies with the massive capital expenditures flowing into the sector. Even major cloud providers and chip makers are showing strain. Oracle reportedly lost $100 million in three months after installing Nvidia’s new Blackwell GPUs, which Zitron noted are “extremely power-hungry and expensive to run.”
Finding utility despite the hype
I pushed back against some of Zitron’s broader dismissals of AI by sharing my own experience. I use AI chatbots frequently for brainstorming useful ideas and helping me see them from different angles. “I find I use AI models as sort of knowledge translators and framework translators,” I explained.
After experiencing brain fog from repeated bouts of COVID over the years, I’ve also found tools like ChatGPT and Claude especially helpful for memory augmentation that pierces through brain fog: describing something in a roundabout, fuzzy way and quickly getting an answer I can then verify. Along these lines, I’ve previously written about how people in a UK study found AI assistants useful accessibility tools.
Zitron acknowledged this could be useful for me personally but declined to draw any larger conclusions from my one data point. “I understand how that might be helpful; that’s cool,” he said. “I’m glad that that helps you in that way; it’s not a trillion-dollar use case.”
He also shared his own attempts at using AI tools, including experimenting with Claude Code despite not being a coder himself.
“If I liked [AI] somehow, it would be actually a more interesting story because I’d be talking about something I liked that was also onerously expensive,” Zitron explained. “But it doesn’t even do that, and it’s actually one of my core frustrations, it’s like this massive over-promise thing. I’m an early adopter guy. I will buy early crap all the time. I bought an Apple Vision Pro, like, what more do you say there? I’m ready to accept issues, but AI is all issues, it’s all filler, no killer; it’s very strange.”
Zitron and I agree that current AI assistants are being marketed beyond their actual capabilities. As I often say, AI models are not people, and they are not good factual references. As such, they cannot replace human decision-making and cannot wholesale replace human intellectual labor (at the moment). Instead, I see AI models as augmentations of human capability: as tools rather than autonomous entities.
Computing costs: History versus reality
Even though Zitron and I found some common ground about AI hype, I expressed a belief that criticism over the cost and power requirements of operating AI models will eventually not become an issue.
I attempted to make that case by noting that computing costs historically trend downward over time, referencing the Air Force’s SAGE computer system from the 1950s: a four-story building that performed 75,000 operations per second while consuming two megawatts of power. Today, pocket-sized phones deliver millions of times more computing power in a way that would be impossible, power consumption-wise, in the 1950s.
The blockhouse for the Semi-Automatic Ground Environment at Stewart Air Force Base, Newburgh, New York. Credit: Denver Post via Getty Images
“I think it will eventually work that way,” I said, suggesting that AI inference costs might follow similar patterns of improvement over years and that AI tools will eventually become commodity components of computer operating systems. Basically, even if AI models stay inefficient, AI models of a certain baseline usefulness and capability will still be cheaper to train and run in the future because the computing systems they run on will be faster, cheaper, and less power-hungry as well.
Zitron pushed back on this optimism, saying that AI costs are currently moving in the wrong direction. “The costs are going up, unilaterally across the board,” he said. Even newer systems like Cerebras and Grok can generate results faster but not cheaper. He also questioned whether integrating AI into operating systems would prove useful even if the technology became profitable, since AI models struggle with deterministic commands and consistent behavior.
The power problem and circular investments
One of Zitron’s most pointed criticisms during the discussion centered on OpenAI’s infrastructure promises. The company has pledged to build data centers requiring 10 gigawatts of power capacity (equivalent to 10 nuclear power plants, I once pointed out) for its Stargate project in Abilene, Texas. According to Zitron’s research, the town currently has only 350 megawatts of generating capacity and a 200-megawatt substation.
“A gigawatt of power is a lot, and it’s not like Red Alert 2,” Zitron said, referencing the real-time strategy game. “You don’t just build a power station and it happens. There are months of actual physics to make sure that it doesn’t kill everyone.”
He believes many announced data centers will never be completed, calling the infrastructure promises “castles on sand” that nobody in the financial press seems willing to question directly.
After another technical blackout on my end, I came back online and asked Zitron to define the scope of the AI bubble. He says it has evolved from one bubble (foundation models) into two or three, now including AI compute companies like CoreWeave and the market’s obsession with Nvidia.
Zitron highlighted what he sees as essentially circular investment schemes propping up the industry. He pointed to OpenAI’s $300 billion deal with Oracle and Nvidia’s relationship with CoreWeave as examples. “CoreWeave, they literally… They funded CoreWeave, became their biggest customer, then CoreWeave took that contract and those GPUs and used them as collateral to raise debt to buy more GPUs,” Zitron explained.
When will the bubble pop?
Zitron predicted the bubble would burst within the next year and a half, though he acknowledged it could happen sooner. He expects a cascade of events rather than a single dramatic collapse: An AI startup will run out of money, triggering panic among other startups and their venture capital backers, creating a fire-sale environment that makes future fundraising impossible.
“It’s not gonna be one Bear Stearns moment,” Zitron explained. “It’s gonna be a succession of events until the markets freak out.”
The crux of the problem, according to Zitron, is Nvidia. The chip maker’s stock represents 7 to 8 percent of the S&P 500’s value, and the broader market has become dependent on Nvidia’s continued hyper growth. When Nvidia posted “only” 55 percent year-over-year growth in January, the market wobbled.
“Nvidia’s growth is why the bubble is inflated,” Zitron said. “If their growth goes down, the bubble will burst.”
He also warned of broader consequences: “I think there’s a depression coming. I think once the markets work out that tech doesn’t grow forever, they’re gonna flush the toilet aggressively on Silicon Valley.” This connects to his larger thesis: that the tech industry has run out of genuine hyper-growth opportunities and is trying to manufacture one with AI.
“Is there anything that would falsify your premise of this bubble and crash happening?” I asked. “What if you’re wrong?”
“I’ve been answering ‘What if you’re wrong?’ for a year-and-a-half to two years, so I’m not bothered by that question, so the thing that would have to prove me right would’ve already needed to happen,” he said. Amid a longer exposition about Sam Altman, Zitron said, “The thing that would’ve had to happen with inference would’ve had to be… it would have to be hundredths of a cent per million tokens, they would have to be printing money, and then, it would have to be way more useful. It would have to have efficacy that it does not have, the hallucination problems… would have to be fixable, and on top of this, someone would have to fix agents.”
A positivity challenge
Near the end of our conversation, I wondered if I could flip the script, so to speak, and see if he could say something positive or optimistic, although I chose the most challenging subject possible for him. “What’s the best thing about Sam Altman,” I asked. “Can you say anything nice about him at all?”
“I understand why you’re asking this,” Zitron started, “but I wanna be clear: Sam Altman is going to be the reason the markets take a crap. Sam Altman has lied to everyone. Sam Altman has been lying forever.” He continued, “Like the Pied Piper, he’s led the markets into an abyss, and yes, people should have known better, but I hope at the end of this, Sam Altman is seen for what he is, which is a con artist and a very successful one.”
Then he added, “You know what? I’ll say something nice about him, he’s really good at making people say, ‘Yes.’”
Benj Edwards is Ars Technica’s Senior AI Reporter and founder of the site’s dedicated AI beat in 2022. He’s also a tech historian with almost two decades of experience. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC.
As generative AI has taken off since ChatGPT’s debut, inspiring hundreds of billions of dollars in investments and infrastructure developments, the top question on many people’s minds has been: Is generative AI a bubble, and if so, when will it pop?
To help us potentially answer that question, I’ll be hosting a live conversation with prominent AI critic Ed Zitron on October 7 at 3: 30 pm ET as part of the Ars Live series. As Ars Technica’s senior AI reporter, I’ve been tracking both the explosive growth of this industry and the mounting skepticism about its sustainability.
Zitron is the host of the Better Offline podcast and CEO of EZPR, a media relations company. He writes the newsletter Where’s Your Ed At, where he frequently dissects OpenAI’s finances and questions the actual utility of current AI products. His recent posts have examined whether companies are losing money on AI investments, the economics of GPU rentals, OpenAI’s trillion-dollar funding needs, and what he calls “The Subprime AI Crisis.”
Credit: Ars Technica
During our conversation, we’ll dig into whether the current AI investment frenzy matches the actual business value being created, what happens when companies realize their AI spending isn’t generating returns, and whether we’re seeing signs of a peak in the current AI hype cycle. We’ll also discuss what it’s like to be a prominent and sometimes controversial AI critic amid the drumbeat of AI mania in the tech industry.
While Ed and I don’t see eye to eye on everything, his sharp criticism of the AI industry’s excesses should make for an engaging discussion about one of tech’s most consequential questions right now.
Please join us for what should be a lively conversation about the sustainability of the current AI boom.
Enlarge/ An ABC handout promotional image for “AI and the Future of Us: An Oprah Winfrey Special.”
On Thursday, ABC announced an upcoming TV special titled, “AI and the Future of Us: An Oprah Winfrey Special.” The one-hour show, set to air on September 12, aims to explore AI’s impact on daily life and will feature interviews with figures in the tech industry, like OpenAI CEO Sam Altman and Bill Gates. Soon after the announcement, some AI critics began questioning the guest list and the framing of the show in general.
“Sure is nice of Oprah to host this extended sales pitch for the generative AI industry at a moment when its fortunes are flagging and the AI bubble is threatening to burst,” tweeted author Brian Merchant, who frequently criticizes generative AI technology in op-eds, social media, and through his “Blood in the Machine” AI newsletter.
“The way the experts who are not experts are presented as such 💀 what a train wreck,” replied artist Karla Ortiz, who is a plaintiff in a lawsuit against several AI companies. “There’s still PLENTY of time to get actual experts and have a better discussion on this because yikes.”
The trailer for Oprah’s upcoming TV special on AI.
On Friday, Ortiz created a lengthy viral thread on X that detailed her potential issues with the program, writing, “This event will be the first time many people will get info on Generative AI. However it is shaping up to be a misinformed marketing event starring vested interests (some who are under a litany of lawsuits) who ignore the harms GenAi inflicts on communities NOW.”
Critics of generative AI like Ortiz question the utility of the technology, its perceived environmental impact, and what they see as blatant copyright infringement. In training AI language models, tech companies like Meta, Anthropic, and OpenAI commonly use copyrighted material gathered without license or owner permission. OpenAI claims that the practice is “fair use.”
Oprah’s guests
According to ABC, the upcoming special will feature “some of the most important and powerful people in AI,” which appears to roughly translate to “famous and publicly visible people related to tech.” Microsoft co-founder Bill Gates, who stepped down as Microsoft CEO 24 years ago, will appear on the show to explore the “AI revolution coming in science, health, and education,” ABC says, and warn of “the once-in-a-century type of impact AI may have on the job market.”
As a guest representing ChatGPT-maker OpenAI, Sam Altman will explain “how AI works in layman’s terms” and discuss “the immense personal responsibility that must be borne by the executives of AI companies.” Karla Ortiz specifically criticized Altman in her thread by saying, “There are far more qualified individuals to speak on what GenAi models are than CEOs. Especially one CEO who recently said AI models will ‘solve all physics.’ That’s an absurd statement and not worthy of your audience.”
In a nod to present-day content creation, YouTube creator Marques Brownlee will appear on the show and reportedly walk Winfrey through “mind-blowing demonstrations of AI’s capabilities.”
Brownlee’s involvement received special attention from some critics online. “Marques Brownlee should be absolutely ashamed of himself,” tweeted PR consultant and frequent AI critic Ed Zitron, who frequently heaps scorn on generative AI in his own newsletter. “What a disgraceful thing to be associated with.”
Other guests include Tristan Harris and Aza Raskin from the Center for Humane Technology, who aim to highlight “emerging risks posed by powerful and superintelligent AI,” an existential risk topic that has its own critics. And FBI Director Christopher Wray will reveal “the terrifying ways criminals and foreign adversaries are using AI,” while author Marilynne Robinson will reflect on “AI’s threat to human values.”
Going only by the publicized guest list, it appears that Oprah does not plan to give voice to prominent non-doomer critics of AI. “This is really disappointing @Oprah and frankly a bit irresponsible to have a one-sided conversation on AI without informed counterarguments from those impacted,” tweeted TV producer Theo Priestley.
Others on the social media network shared similar criticism about a perceived lack of balance in the guest list, including Dr. Margaret Mitchell of Hugging Face. “It could be beneficial to have an AI Oprah follow-up discussion that responds to what happens in [the show] and unpacks generative AI in a more grounded way,” she said.
Oprah’s AI special will air on September 12 on ABC (and a day later on Hulu) in the US, and it will likely elicit further responses from the critics mentioned above. But perhaps that’s exactly how Oprah wants it: “It may fascinate you or scare you,” Winfrey said in a promotional video for the special. “Or, if you’re like me, it may do both. So let’s take a breath and find out more about it.”
On Thursday, OpenAI said that ChatGPT has attracted over 200 million weekly active users, according to a report from Axios, doubling the AI assistant’s user base since November 2023. The company also revealed that 92 percent of Fortune 500 companies are now using its products, highlighting the growing adoption of generative AI tools in the corporate world.
The rapid growth in user numbers for ChatGPT (which is not a new phenomenon for OpenAI) suggests growing interest in—and perhaps reliance on— the AI-powered tool, despite frequent skepticism from some critics of the tech industry.
“Generative AI is a product with no mass-market utility—at least on the scale of truly revolutionary movements like the original cloud computing and smartphone booms,” PR consultant and vocal OpenAI critic Ed Zitron blogged in July. “And it’s one that costs an eye-watering amount to build and run.”
Despite this kind of skepticism (which raises legitimate questions about OpenAI’s long-term viability), OpenAI claims that people are using ChatGPT and OpenAI’s services in record numbers. One reason for the apparent dissonance is that ChatGPT users might not readily admit to using it due to organizational prohibitions against generative AI.
Wharton professor Ethan Mollick, who commonly explores novel applications of generative AI on social media, tweeted Thursday about this issue. “Big issue in organizations: They have put together elaborate rules for AI use focused on negative use cases,” he wrote. “As a result, employees are too scared to talk about how they use AI, or to use corporate LLMs. They just become secret cyborgs, using their own AI & not sharing knowledge”
The new prohibition era
It’s difficult to get hard numbers showing the number of companies with AI prohibitions in place, but a Cisco study released in January claimed that 27 percent of organizations in their study had banned generative AI use. Last August, ZDNet reported on a BlackBerry study that said 75 percent of businesses worldwide were “implementing or considering” plans to ban ChatGPT and other AI apps.
As an example, Ars Technica’s parent company Condé Nast maintains a no-AI policy related to creating public-facing content with generative AI tools.
Prohibitions aren’t the only issue complicating public admission of generative AI use. Social stigmas have been developing around generative AI technology that stem from job loss anxiety, potential environmental impact, privacy issues, IP and ethical issues, security concerns, fear of a repeat of cryptocurrency-like grifts, and a general wariness of Big Tech that some claim has been steadily rising over recent years.
Whether the current stigmas around generative AI use will break down over time remains to be seen, but for now, OpenAI’s management is taking a victory lap. “People are using our tools now as a part of their daily lives, making a real difference in areas like healthcare and education,” OpenAI CEO Sam Altman told Axios in a statement, “whether it’s helping with routine tasks, solving hard problems, or unlocking creativity.”
Not the only game in town
OpenAI also told Axios that usage of its AI language model APIs has doubled since the release of GPT-4o mini in July. This suggests software developers are increasingly integrating OpenAI’s large language model (LLM) tech into their apps.
And OpenAI is not alone in the field. Companies like Microsoft (with Copilot, based on OpenAI’s technology), Google (with Gemini), Meta (with Llama), and Anthropic (Claude) are all vying for market share, frequently updating their APIs and consumer-facing AI assistants to attract new users.
If the generative AI space is a market bubble primed to pop, as some have claimed, it is a very big and expensive one that is apparently still growing larger by the day.
