Nvidia is the king of artificial intelligence, but staying stuck in one tech trend is not a smart move.
We’ve seen the company pivot from gaming to crypto and from crypto to AI. Predicting the next big trend is key to its success, and Nvidia CEO Jensen Huang has consistently demonstrated his ability to do so.
The moves Nvidia has been making signal that the next trend will be quantum computing, as its venture capital arm, NVentures, has started investing in quantum computing companies.
NVentures invested in Honeywell’s (HON) quantum computing unit, Quantinuum, in September; in QuEra in February; and in PsiQuantum in September.
Investing isn’t enough, and Nvidia has teamed up with researchers from supercomputing centers at national laboratories including Brookhaven National Laboratory, Fermi Laboratory, Lawrence Berkeley National Laboratory (Berkeley Lab), Los Alamos National Laboratory, MIT Lincoln Laboratory, the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratories to design new tech that will speed up development of quantum computers.
Nvidia unveils NVQLink at GTC
At the GTC conference in Washington, D.C., Nvidia (NVDA) launched NVQLink, a new open architecture that integrates Quantum Processing Units (QPUs) with classical GPUs. The platform provides an open approach to quantum integration, supporting 17 QPU builders, five controller builders, and nine U.S. national labs.
Quantum computers are prone to errors and require quantum error correction and other control algorithms to operate correctly.
Error correction algorithms can be implemented on specialized hardware, such as field-programmable gate arrays (FPGAs). For example, IBM is using AMD’s FPGAs to run its error correction algorithm.
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Ideally, these error correction algorithms should be run on a supercomputer. However, to accomplish that, we would need an extremely low-latency, high-throughput connection from a quantum computer to a conventional supercomputer.
That badly needed interconnect is exactly what NVQLink provides, and this breakthrough has the potential to significantly shorten the time required for the development of useful quantum computers.
“In the near future, every NVIDIA GPU scientific supercomputer will be hybrid, tightly coupled with quantum processors to expand what is possible with computing,” said Jensen Huang, founder and CEO of NVIDIA.
“NVQLink is the Rosetta Stone connecting quantum and classical supercomputers — uniting them into a single, coherent system that marks the onset of the quantum-GPU computing era.”
Companies that contributed to NVQLink creation
Quantum hardware builders:
- Alice & Bob
- Anyon Computing
- Atom Computing
- Diraq
- Infleqtion
- IonQ
- IQM Quantum Computers
- ORCA Computing
- Oxford Quantum Circuits
- Pasqal
- Quandela
- Quantinuum
- Quantum Circuits, Inc.
- Quantum Machines
- Quantum Motion
- QuEra
- Rigetti
- SEEQC
- Silicon Quantum Computing
Quantum control system builders:
- Keysight Technologies
- Quantum Machines
- Qblox
- QubiC
- Zurich Instruments
For investors concerned about AI being a bubble, these quantum developments may be seen as a signal that Nvidia is also worried, and Bank of America analysts have recently commented on the issue.
Bank of America addresses AI bubble
Bank of America analysts Vivek Arya and his team addressed “AI doom headlines” in a recent note, providing their opinion on Nvidia shares.
The team said that large-scale infrastructure rollouts inherently carry some risk of overbuilding, adding that it’s difficult to match capacity to future demand. In addition, there’s often a technological race to build and protect existing moats or establish new revenue streams.
Analysts noted four key differences between the ongoing AI build and the prior dot-com bust:
- High utilization of AI computing power is different from the underused “dark fiber” of the dot-com bust.
- Capex intentions of top cloud service providers are on track, unlike debt-driven financing during the dot-com days.
- The U.S. Fed is more likely to lower than raise rates, unlike prior market crashes, which coincided with rising interest rates.
- Nvidia’s valuation differs from more than 100 multiple price-to-earnings ratios of dot-com leaders (such as Cisco, Nortel, and Yahoo).
Arya reiterated a buy rating and the target price of $235, based on 37 multiple his estimate for price-to-earnings ratio. This excludes cash for calendar year 2026, which is in the middle of Nvidia’s historical forward year price-to-earnings range of 25 to 56.
Analysts noted downside risk factors for Nvidia:
- Weakness in the consumer-driven gaming market
- Competition with major public firms
- Larger-than-expected impact from restrictions on compute shipments to China
- Lumpy and unpredictable sales in new enterprise, data center, and autos markets
- Potential for decelerating capital returns
- Enhanced government scrutiny of Nvidia’s dominant market position in AI chips
