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Luke Kawa

Why Jensen Huang should be embarrassed that he didn’t know quantum computing companies were publicly traded

During Nvidia’s Quantum Day at GTC, CEO Jensen Huang admitted that he didn’t know quantum computing companies were publicly traded when he remarked in early January that it would likely be decades before the technology was “useful.”

Those remarks prompted very publicly traded quantum computing companies to lose billions in market value thereafter.

If I were one of the handful of executives from a publicly traded quantum computing company sitting there on Thursday, I’d be faking a smile through gritted teeth at hearing Huang’s story. Why?

They’re not only buyers of the chip designer’s high-powered products and software. In some cases, they’re also partners, as Nvidia has been supporting the development of these companies and their technology.

To take Huang at his own words, from those same early January remarks on the utility of quantum computing: “Just about every quantum computing company in the world is working with us now.”

Their executives have even been cited in press releases together!

From a joint press release from Rigetti Computing and Quantum Machines in December announcing how they were able to calibrate a quantum computer using the help of AI:

“AI is a critical tool for advancing quantum computing,” said Tim Costa, senior director of CAE, EDA, and Quantum at Nvidia. “This latest work shows how the scalable control of quantum hardware needed for useful applications hinges on advances in AI.”

And from an IonQ press release in November:

“Useful quantum applications will need to draw on both quantum hardware and AI supercomputing resources,” said Elica Kyoseva, director of Quantum Algorithm Engineering at Nvidia. “The CUDA-Q platform is allowing researchers and developers to explore these paradigms by accessing Nvidia accelerated computing alongside IonQ’s quantum processors.”

I get that Huang has had a lot of things on his mind (mainly the Blackwell ramp and the product road map to come), and that “useful” quantum computing is even further away in his mental timeline than the most advanced stuff Nvidia’s dreaming up right now, but still, yeesh.

Those remarks prompted very publicly traded quantum computing companies to lose billions in market value thereafter.

If I were one of the handful of executives from a publicly traded quantum computing company sitting there on Thursday, I’d be faking a smile through gritted teeth at hearing Huang’s story. Why?

They’re not only buyers of the chip designer’s high-powered products and software. In some cases, they’re also partners, as Nvidia has been supporting the development of these companies and their technology.

To take Huang at his own words, from those same early January remarks on the utility of quantum computing: “Just about every quantum computing company in the world is working with us now.”

Their executives have even been cited in press releases together!

From a joint press release from Rigetti Computing and Quantum Machines in December announcing how they were able to calibrate a quantum computer using the help of AI:

“AI is a critical tool for advancing quantum computing,” said Tim Costa, senior director of CAE, EDA, and Quantum at Nvidia. “This latest work shows how the scalable control of quantum hardware needed for useful applications hinges on advances in AI.”

And from an IonQ press release in November:

“Useful quantum applications will need to draw on both quantum hardware and AI supercomputing resources,” said Elica Kyoseva, director of Quantum Algorithm Engineering at Nvidia. “The CUDA-Q platform is allowing researchers and developers to explore these paradigms by accessing Nvidia accelerated computing alongside IonQ’s quantum processors.”

I get that Huang has had a lot of things on his mind (mainly the Blackwell ramp and the product road map to come), and that “useful” quantum computing is even further away in his mental timeline than the most advanced stuff Nvidia’s dreaming up right now, but still, yeesh.

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Oil tumbles below $80 to 3-month low on US-Iran deal

Oil prices slid to their lowest levels in more than three months today after a preliminary ceasefire agreement between the US and Iran raised expectations that more crude could return to global markets and key shipping routes through the Strait of Hormuz could reopen.

Brent crude fell below $78 a barrel while West Texas Intermediate dropped to $73.31, extending losses as traders priced in lower geopolitical risk premiums tied to Middle East supply disruptions.

The preliminary pact announced by President Donald Trump and Iranian leaders establishes a 60-day ceasefire to end the active hostilities that have choked the Middle East since late February. A formal memorandum of understanding is scheduled to be officially signed in Switzerland this Friday, according to Bloomberg report.

Trump said on Sunday that the Strait of Hormuz would be opened when the agreement is signed in Switzerland on Friday, writing on Truth Social, “Ships of the World, start your engines. Let the oil flow!

US Energy Department data, meanwhile, showed that Americas strategic oil stockpiles sank last week to their lowest level since 1983, indicating sustained demand to rebuild them even if the Mideast conflict ends.

Stocks that moved lower:

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Eos Energy surges on commercial launch of second battery production line

Eos Energy Enterprises is surging in early trading after announcing the official start of commercial production at its second automated battery manufacturing line.

In a statement, the company said this milestone positions it to scale production of its proprietary zinc-based long-duration energy storage systems to meet rising commercial demand.

Management touted the enhanced efficiency of this facility, with design upgrades slashing raw material travel by 86% and shortening the physical production line length by 40% compared to Line 1.

“Battery Line 2 demonstrates our ability to continuously improve as we scale,” said John Mahaz, Chief Operating Officer of Eos. “It validates that our manufacturing system can be replicated and scaled with discipline.”

The battery energy storage company confirmed that while subassemblies will continue coming online through the early third quarter, full production capacity is targeted for the fourth quarter of 2026. The ultimate goal is to hit an aggregate 4 gigawatt-hours of annual manufacturing capacity by the end of 2026. Management also highlighted that Battery Line 1 already surpassed its full-year 2025 output within the first 164 days of 2026.

Today’s announcement builds on recent operational momentum for Eos, which posted better-than-expected Q1 sales and announced a joint venture with Cerberus Capital Management in May. However, shares are still down 37% year to date.

For the full year, Eos still expects to achieve revenues between $300 million and $400 million, in line with its previously provided guidance.

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Qualcomm reportedly in talks to acquire AI chip design company Tenstorrent

Qualcomm is in talks to acquire AI chip design firm Tenstorrent for $8 billion to $10 billion, according to The Information.

This transaction, if completed, would be another concrete signal of the San Diego-based chip company’s attempt to carve out a niche in the upstream AI space (data centers), rather than focusing on end-user devices.

Qualcomm’s key business of handset chips has fallen on hard times, particularly in China, due to the memory chip shortage.

Less than eight weeks ago, the chip company was the lowlight in the Philadelphia Semiconductor Index, down about 20% year to date.

Shares proceeded to surge over 60%, buoyed by optimism that the rising AI tide will lift all boats. With the release of Q2 earnings, CEO Cristiano Amon said that initial shipments of AI chips to a “leading hyperscaler” were on track for later this year, and to expect more on the company’s AI growth plans at its investor day on June 24 (next week). Last month, Bloomberg reported that Qualcomm is poised to sell “millions” of AI chips to TikTok parent ByteDance.

Established AI chip giants and hyperscalers alike have reached agreements with or gobbled up burgeoning AI chip companies as the boom rolls on. In December, Nvidia announced a major licensing deal with AI inference specialist Groq, while Meta bought AI chip startup Rivos in September.

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