America is experiencing one of the greatest technological investment booms in our history. Yet an enormous amount of the equipment we're using to support our Super Intelligence boom is coming from countries that spent the last several decades building the manufacturing industries we allowed, and often encouraged, to slip away.
Anthropic is touting its ability to use different AI chips in its initial public offering filing.
Analysts say a multichip strategy could weaken Nvidia's pricing power.
Switching chips is hard and expensive, putting it out of reach for smaller players.
Anthropic is hedging its bets by using multiple chips to handle its AI work — a strategy that could eventually erode Nvidia's dominance.
The AI lab says it manages compute "as a single, fungible pool from multiple strategic partners" — with software that can direct its work to different chips depending on where they're most productive, according to Anthropic's S-1 filing, which came out Monday as the company prepares to go public.
Anthropic says it uses hardware from four chip families: Amazon Trainium, Google TPUs, Nvidia GPUs, and AMD GPUs.
That flexibility, which Anthropic said "took years and significant investment to build," could make major AI companies less dependent on Nvidia over time and give them more negotiating leverage, analysts said.
"The real exposure could be Nvidia's pricing power," said Patrick Moorhead, founder and CEO of Moor Insights & Strategy, "because a customer that can shift work across four platforms negotiates very differently than one that can't."
Ashish Nadkarni, an analyst at IDC, added that a multichip approach also makes Anthropic less vulnerable to fluctuations in Nvidia's chip supply.
Breaking Nvidia's grip isn't easy
Although Anthropic's chip mix isn't new, the company is now pitching it as a core advantage to investors, Moorhead said.
The threat has its limits. Switching between chips is still difficult — especially when it comes to training AI models as opposed to running them, Moorhead said — and only the biggest AI companies have the resources to do it.
Anthropic also continues to spend billions on Nvidia compute, Moorhead said.
Gil Luria, head of technology research at D.A. Davidson, said that while other major companies like OpenAI likely take a multichip approach, it may not be worth the effort and investment for smaller players.
Brad Gastwirth, global head of research and market intelligence at Circular Technology, said Anthropic's strategy doesn't represent a major near-term threat. Having more chip options doesn't erase Nvidia's advantages in performance, networking, and software, he said.
There's a broader risk for Nvidia if AI compute becomes more of a commodity.
Citadel CEO Ken Griffin has warned that if supply overtakes demand, it could drive down rental prices.
"GPUs, like airlines, have a very low marginal cost to run," he told Bloomberg last week. "The moment you have overcapacity, pricing goes into freefall."
Nvidia did not immediately respond to a request for comment from Business Insider.
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Upadhyaya is a supply chain program manager at Intel.
Courtesy of Mihirkant Upadhyaya
Mihirkant Upadhyaya has a Ph.D. and more than 10 years of experience at Intel.
But at age 41, he embarked on gaining another degree to level up in his career.
Upadhyaya says that doing an MBA equips him with skills that AI lacks.
This as-told-to essay is based on a conversation with Mihirkant Upadhyaya, 42, who works at Intel and lives in Oregon. The following has been edited for length and clarity. Business Insider has verified his employment and education.
After studying computer engineering for my bachelor's, I pivoted into physics.
Two master's degrees and a Ph.D. in nanoscale science and engineering later, I got my dream job in the semiconductor industry at Intel in 2015.
As my career evolved, I realized I also wanted to do an MBA to step up my game.
My Ph.D. gave me relevant skills to take on the workforce
During my Ph.D., I focused on a semiconductor manufacturing technology called EUV lithography. I was excited to work at Intel because it does both chip design and manufacturing, so I knew I'd get a good overview of the chip-making process.
You don't need a Ph.D. to work in semiconductors, as there are so many areas outside the lab you can work in, like finance and legal.
On a personal level, though, having a Ph.D. helped me feel prepared to step into the workforce. It gave me discipline and the ability to be comfortable with ambiguity. My research mindset and technical background gave me the confidence to take ownership of outcomes and tasks.
There were definitely moments where I had self-doubt doing a Ph.D. You watch your peers go on to earn big bucks after their bachelor's and master's while you live on a modest stipend. However, the experience shaped me into who I am. I'd say I'm more patient, sharper, and more resilient.
I reached a stage where I felt I needed more education to thrive in my job
After about five years in research and development at Intel, I moved into supply chain roles, which have involved managing relationships and negotiating contracts. At this point, I realized I was missing certain skills.
My current role has a greater emphasis on executive communication and financial analysis. When I presented to an executive team, my manager had to step in on a number of occasions to get the room to respond, making what I was saying more high-level using business-driven terms. I also didn't quite understand certain things when I worked with the finance teams on contract negotiations.
To step up my game, I started a two-year hybrid MBA course in September 2025, alongside my full-time job. It was energizing to get back to the classroom at age 41.
I take one week off a quarter to do in-person sessions, and the rest of the time I'm doing online learning three days a week. My company is partly funding this, which is useful since MBAs can carry a $100,000 price tag.
Upadhyaya estimates that he's invested $100,000 into his post-graduate education.
Courtesy of Mihirkant Upadhyaya
By the time I've finished my MBA, I'll have done nine years of postgraduate study, investing an estimated $100,000 into that education, aside from scholarships and tuition waivers. Without question, it's been worth it. I haven't pursued the degrees to accumulate credentials, but to serve my career at various stages of my life. The MBA is addressing a concrete skills gap I identified after years in my industry.
I believe higher education is helping me become more irreplaceable in the age of AI
The AI boom made me take a hard look at what I bring to the table. I saw that some of what I did could eventually be automated. That realization was humbling.
Instead of trying to compete with what AI is already good at, I wanted to strengthen the areas where I knew it fell short. AI is great at processing and analyzing information. It has scale and speed, but it lacks the truly insightful judgment that a person can gain from years of learning a skill.
Upadhyaya said he's encountered limits to AI's capabilities.
Courtesy of Mihirkant Upadhyaya
In my previous role at Intel, I found that AI couldn't tell me how to troubleshoot issues involving new or custom-made equipment because the context was so unique to my situation.
Meanwhile, in my current role, while AI could probably help me generate financial models, it can't read the room, build relationships, or have synergy with another person. My MBA course benefits me in this regard because we do lots of group activities, even online through Zoom, where we can interact with each other.
I think that in the age of AI, finding a field you really care about, becoming an expert in it, and staying curious to keep learning can help you become irreplaceable.
Intel declined to comment in response to a request from Business Insider.
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