If you're interested in investing in quantum computing, my guess is you're already familiar with trendy stocks such as IonQ, Rigetti Computing, or D-Wave Quantum. Don't get me wrong -- there's potentially a lot of money to be made in those stocks. The caveat is that timing is everything when it comes to owning smaller, speculative players such as these.
If you're interested in gaining exposure to quantum computing as part of your broader artificial intelligence (AI) portfolio but are also looking to mitigate risk, then I'd suggest looking to the "Magnificent Seven." Amazon (AMZN -1.12%), Microsoft (MSFT 0.04%), and Alphabet (GOOGL -0.72%) are three of my top picks when it comes to the quantum computing revolution.
Investing in quantum computing is harder than you think
The chart below illustrates the price action for IonQ, D-Wave Quantum, and Rigetti Computing over the past six months. Despite some notable selling in recent weeks, all three are materially higher than they were just six months ago.
Clearly, some people were fortunate enough to make some money in these stocks. However, a lot of people followed the momentum into them and are now sitting on losses.
Given that IonQ, D-Wave, and Rigetti aren't generating much in the way of revenue and will likely need to seek liquidity to stay afloat, I'm less inclined to think their respective share prices will climb at such rapid rates again anytime soon. In my opinion, generating profits from such speculative stocks is mostly a matter of luck.
Moreover, Nvidia CEO Jensen Huang recently proclaimed that quantum computing applications likely won't be operating usefully at scale for another 20 years. Given this outlook, I wouldn't want to invest in a small company with low sales and virtually no concrete path to profitability.
Instead, I'd encourage investors to seek out diversified businesses that are already generating recurring cash flow that they can invest into new areas such as quantum computing.
1. Amazon
In classical computing, binary code (0's and 1's) is also referred to as classical bits. While quantum computing also leverages 0's and 1's, this technology relies on quantum bits (qubits) -- essentially a property that allows code to exist in multiple states at once. The theory here is that qubits can solve complex problems much faster than even the most sophisticated supercomputers.
However, a big drawback on quantum computing is that qubits are highly sensitive to external factors such as vibrations or heat. For this reason, error correction is a major challenge for those developing quantum computing applications. Historically, a common method to troubleshoot this issue is to use a high volume of qubits in an effort to suppress errors in calculations. As you might imagine, integrating more qubits into computing protocols comes at a high price. This is where Amazon is looking to make a difference.
Recently, Amazon announced that its new chip, Ocelot, "can reduce the costs of implementing quantum error correction by up to 90%".
The company claims to have achieved this milestone by implementing error correction in its quantum architecture. In other words, Amazon's approach is not to wait for an application to crash and simply integrate more qubits into its architecture. By building "fault-tolerant" computers, Amazon believes the Ocelot architecture could help significantly reduce the costs of developing quantum computing compared to today's traditional approaches.
To me, the real value-add of Amazon being able to reduce the costs of quantum computing development is that the company can layer this service underneath the Amazon Web Services (AWS) umbrella. Given AWS is a highly profitable business for Amazon, I think the company's differentiated approach to quantum computing could help further accelerate demand for the company's cloud infrastructure and lead to widening margins and profits down the road, once quantum computing becomes more commercially available.
Image source: Getty Images.
2. Microsoft
As I alluded to above, qubits are sensitive to external properties. A big reason for this is that the foundation for qubits tend to be basic particles such as ions, photons, or electrons. Microsoft's Majorana 1 quantum chip leverages what's called a topological qubit architecture. The company's research indicates that topological qubits are more reliable and scalable than traditional qubits as this infrastructure is less susceptible to external forces. Similar to Amazon's approach, Microsoft is seeking to build quantum applications that can be scaled more efficiently compared to mainstream solutions available today.
Microsoft calls its topoconductor a quantum processing unit (QPU) -- a piece of hardware that is "designed to scale to a million qubits on a single chip".
While this is exciting news for Microsoft and intriguing for quantum computing enthusiasts, investors should know that the Majorana 1 is still operating as a prototype -- making the topoconductor hardware still more of an ambition than a firm reality at this point.
3. Alphabet
A few months ago, Google Quantum unveiled its latest breakthrough -- the Willow quantum computing chip.
The big news regarding Willow was that the chip solved a benchmark computational problem in roughly five minutes that would take an advanced classical supercomputer 10 septillion years to figure out. While such a feat was an intriguing demonstration of Willow's power, the "random circuit sampling" test is an esoteric problem designed to showcase the sorts of things that a quantum computer can do that a classical one can't. Practical uses for quantum computers in which they can deliver superior results to today's supercomputers are still over the horizon.
Nevertheless, I think Alphabet's achievements in quantum computing underscore the idea that today's most advanced computers will need to be augmented with processing power beyond that provided by graphics processing units (GPU) as AI applications become more sophisticated -- especially in fields such as medicine or financial services.
For example, a common use case that quantum computing executives often tout is how the technology can be leveraged for analyze clinical trial data and drug discovery. Moreover, as fraud becomes increasingly prevalent in the financial services world, I see quantum computing playing a major role in improving security protocols -- specifically in the area of cryptography. In addition, hedge funds and traders may be able to apply quantum computing methods in sophisticated risk analysis such as Monte Carlo simulations.
Given Willow's ability to process problems better than today's most capable supercomputers, I'm optimistic that Alphabet could emerge as a leader in the quantum landscape down the road.
Think about the long run
NASDAQ: AMZN
Key Data Points
The common thread stitching Amazon, Alphabet, and Microsoft together is that all of these companies have built diverse ecosystems spanning areas such as e-commerce, cloud computing, streaming, gaming, software applications, social media, advertising, consumer electronics, and more.
All three have already shown that they intend for AI to help shape their respective futures, which could lead to accelerated revenue growth and widening profit margins. A good example here is that Microsoft occasionally bifurcates how much growth AI is generating within its core services.
With that said, current trends suggest that demand should remain high for AI applications in cloud computing, workplace productivity software, and some other major use cases. By contrast, quantum computing is still more of a theoretical component of the AI narrative -- and for that reason, it's admittedly tough to gauge how profitable it will be for these companies' overall AI ecosystems.
Nevertheless, I think quantum computing represents another layer to the broader AI foundation -- and one that could be bundled into each of these companies' product suites down the road, further diversifying their ecosystems against the competition and solidifying these magnificent businesses as long-term winners in the AI revolution.
