I thought it was too early to pick long-term winners in the quantum computing space, and maybe it is. I'm growing fond of D-Wave Quantum's (QBTS +1.16%) unique position in this emerging industry, though.
D-Wave's focus on quantum annealing could make its products a helpful co-processor next to some other commercial-scale developer's quantum gates. If that sentence made as much sense as Finnish poetry (kansassa kasuavassa), let me explain the basics of the two quantum computing models. I think you'll see what I mean about D-Wave's standing apart from the other specialists.
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Key Data Points
The two main flavors of quantum computing, in plain English
Think of quantum annealing as the slow cooker in the quantum computing kitchen of tomorrow.
The other core method involves gate-based quantum computing, seeking precise answers to a wide range of computing problems. These systems are like temperamental molecular gastronomy equipment -- theoretically capable of making anything but requiring perfect conditions. There is almost no margin for error, and the calculation fails completely on the slightest challenge.
Annealing, on the other hand, reliably churns through optimization problems without constant supervision. Errors are hiccups, not the automatic end of the calculation. In a hybrid quantum system, annealing becomes the scout that finds promising solution territories for gate-based systems to explore in detail. It's not trying to solve everything; it's finding an approximate answer to a complex problem.
A 99.9% accurate answer may be good enough for the classic Traveling Salesman routing problem, but it won't break encryption. Rivals like IonQ (IONQ +5.12%), Rigetti Computing (RGTI +0.00%), and Alphabet's (GOOG 0.05%) (GOOGL +0.07%) Google Quantum Labs focus on the more obviously commercial quantum gates, while D-Wave is pretty much alone in the business-style quantum annealing field.
Image source: Getty Images.
Every quantum calculation is a translation problem
Here's where things get interesting: Every quantum computation is really a translation problem.
You've got a business question in English, but the universe's answer exists in quantum mechanics. Like any good translation, you need to understand both languages and what gets lost in the translation process between them. This message-quality challenge is why human translators still have a job despite the sudden appearance of ChatGPT and other AI-based alternatives. Human fluency is essential to convey the right idea.
Annealing excels at preparatory translation work. While precision-hungry gate-based systems parse every quantum syllable for exact meaning, annealing catches the gist, the vibe, the general direction. It's reading the room before the detailed conversation begins.
For optimization problems -- finding the best route, portfolio, or molecular combination -- that's often exactly what you need. But for cryptography or precise simulations? That's when you hand off annealing's rough draft to the gate-based systems for their grammatical perfection. In this hybrid model, D-Wave's initial analysis could help another company's quantum gates start their analysis a lot closer to the correct result.
Real-world uses for D-Wave's approximation engine
Take drug discovery, for example. Annealing rapidly "speed dates" millions of molecular combinations, reading their chemical body language to identify promising couples. Gate-based systems take those matched pairs for deeper analysis -- the difference between analytic chemistry and calculating atomic bond angles (Perkele! -- a Finnish profanity approximate to the English God damn!)
In financial analysis, annealing finds the sweet spot of portfolio optimization, while gates calculate the precise risk metrics around it. It's not either-or; it's both-and, with each approach handling what it does best.
You can also imagine D-Wave's preparatory annealing analysis as a popular component of a larger system. You know the supercomputers that train ChatGPT today? They rely on server-class central processing units (CPUs) from Intel (INTC +10.16%) or Advanced Micro Devices (AMD +1.52%) to run the show and direct data to the right processes. That's where a different set of number-crunching graphics processing units (GPUs), like Nvidia (NVDA 1.83%) Blackwell or AMD Instinct chips, take over. Terabytes of memory chips and high-speed data storage surround the whole process.
In this metaphor, D-Wave's products would take data from the CPUs and prepare it for more efficient GPU analytics. This helper should save both time and money for the system as a whole.
Is D-Wave stock a no-brainer buy today, then? Not so fast.
Does this make D-Wave a slam-dunk buy today? Well, that's a totally different question. I could use a quantum annealing processor to get started on that analysis and finish up with some high-end quantum gate logic.
You see, investors were quick to pounce on D-Wave and its rivals (aka long-term "frenemies") last year when Google presented an impressive error-correcting proof of concept. Despite a 51% drawdown from October's all-time highs, D-Wave's stock is still up 1,312% since Nov. 8, 2024 based almost purely on long-term hopes and dreams.
Sure, D-Wave has sold a few early systems, but it's still more of a research outfit than a revenue-generating business. With a $7.2 billion market cap today, the stock trades at 331 times trailing sales. Profits are miles and years away. And D-Wave stands alone as a business-oriented quantum annealing expert so far, but others could very well enter the space later.
So it's much too early to bet the quantum-realm farm on D-Wave today, because its competitive advantage may not last until quantum computing actually achieves supremacy over digital systems.
I might consider a small, speculative position in this wildly overvalued stock just to get some skin in the quantum game, but that's about it. D-Wave Quantum is the only pure-play quantum computing stock I'd consider right now. Still, it remains a risky bet at these lofty share prices and in this early stage of the industry.
