Quantum Computing: 2075?
I think we're in for a long wait.
Quantum Computing: 2075?
We see the giants of technology talk about quantum computing: Google, Microsoft, Amazon, IBM. We see newcomers who have dreams of greatness do the same. Why? What’s happening?
Trump recently said that the economy doesn’t work without semiconductors. That’s true, if you think about it. Computers, in general, run the world. So, it’s only natural to think about what is beyond—what’s next? Using quantum information and quantum “effects” to compute. That’s perhaps not a final frontier, but it must be pretty close. We can barely observe quantum effects, let alone harness them to do things for us. What things?
Ah, herein lies the problem. I, too, would love unlimited compute. Oh, the primes I would calculate. I was the kind of child who would sit with a calculator and spend an entire afternoon punching numbers in, gratified to see the results. Once I had a computer, all bets were off. But, over the last ten years, it has dawned on me that I am different.
We don’t need quantum computers, and this simple proposition results in a lot of unexpected downstream impacts. Impacts I didn’t really consider until now. You see, I am short stocks like IonQ (NYSE: IONQ), Rigetti (Nasdaq: RGTI) and D-Wave (NYSE: QBTS). They were fairly obviously overvalued stocks, and still are. But the implications for quantum computing in general are what this essay is about.
If you talk to quantum enthusiasts, many will tell you that quantum computing can change the world. I like changing the world. How? They mention pharmaceuticals. I know a pharmaceutical expert, a “brother” of sorts, who has invented some drug candidates. Medicinal chemistry is “shooting fish in a barrel”. There isn’t much in that field that hasn’t been reduced to trial and error. Indeed, the leader in computational chemistry software only sells around $100 million of software annually. Quantum computing wouldn’t excite me as a computational chemist. I have used every computational chemistry tool and even created my own! I talk to material science experts and they tell me the same thing. The only thing that quantum seems extremely good for is factoring and codebreaking, something that NIST has already obviated with the futuristic sounding post-quantum cryptography protocols Dilithium and Kyber.
There is no market for quantum computing. I have no doubt that we will find something interesting to do with these theoretical machines. That’s also the thesis of a few of the giant tech leaders. Just make the machine—everyone else will figure out what to do with it. Putting this optimism aside, I have a natural conjecture for you: what would you calculate if you had infinite compute? What are we calculating now? Generally, deep learning seems to require a lot of compute. But it’s nothing Nvidia can’t handle. A Chinese group recently showed us that maybe you can do it even faster and with fewer Nvidia chips than previously known. So, there is no yearning for more compute that I can think of that exists beyond our boundary. In fact, a major bottleneck for deep learning is actually data collection and data preparation. Quantum can’t help with AI—it’s too ephemeral to do the job—and we don’t need it. I think we’ll actually we will be saturated with compute before we know it. We can still collect a lot of real-world data (think video) and use that to train robots. Beyond that, I can’t think of what I would use a quantum computer for, even if I had a flawless 10,000,000-qubit machine right now.
The problem with a lack of incentive is there will be a lack of progress. The brightest minds will not work on quantum computing, because why bother? Sure, some people like me will still want to do it, just to say they can—to say they tamed the universe to their will. But there isn’t so much money in this. When times get tough (they seem to be getting tougher by the day), companies shed waste. Just the other day, “DOGE” cancelled some government quantum computing contracts. I wouldn’t be surprised if, over time, due to a lack of progress, the big tech companies run out of patience for quantum. I would be very surprised if the smaller companies didn’t run out of money. You need incentive: for brilliant co-workers, excited investors, hungry customers who want to make money with your machine.
Then winter comes. Winter means ten years of no progress. It feels rather chilly. 2035 rolls around. We dust off the old ideas. Other progress in other fields jumpstarts curiosity. Winter has thawed. We have 15 orders of magnitude (think zeros) to go before we have transistor-level errors. Knocking a few of these magnitudes out happens, but we still don’t have a great quantum computer (it can’t factor a ten-digit number without blowing up), and winter comes again by 2045. We defrost in 2055 and focus on limiting the tiniest noise that occurs at this infinitesimal level. What genius can still the roar of the cosmos? They do not reveal themselves, but we get close. The quantum computer of this age is close to the Moore’s law-continuation of Nvidia. Assume no other dynamic has arisen (thermodynamic, adiabatic, analog, DNA, etc.) One more recession caused by the burgeoning robot population gambling on robocoins hits in 2065. Only in 2075 does the market thaw for wild exuberance in quantum computing. A robohuman named Tron realizes the path, using AI, of course. Tron unveils the first gigascale quantum computer. It doesn’t even make the first page of robonews.
There’s nothing to compute.
Having “infinite” (or even just a few orders of magnitude more compute would be huge for AI. AI progress is currently bottlenecked by the number of experiments one can run on current compute budgets.
No one believes the transformer is the best possible architecture. With 10,000x more compute you could run neural architecture search to look for better transformers. With 10,000x more compute you have the resources to run to scale up the algorithms from hundreds of promising but compute starved papers.
AI progress is almost a direct function of compute. The reason we didn’t have the transformer revolution when the original paper came out in 2016 is because the compute available then was 5 or 6 orders of magnitude less than what we have today.
I’m not the quantum computing expert, but it’s my understand that quantum computers are only good for narrow domains and can never run any type of AI. If so then I agree with your thesis. But if it turns out quantum computing can be directly used in AI, I’d be very bullish about the technology.
A Qryptonic, LLC Research Team Rebuttal
Head of Quantum Computing, Qryptonic
Martin Shkreli’s recent piece, “Quantum Computing: 2075?” raises an intriguing mix of skepticism and pragmatism about this emerging field. We at Qryptonic appreciate his willingness to challenge big ideas—after all, a little doubt can drive meaningful innovation. But in the words of A Tribe Called Quest, it’s time to “Check the Rhime” on quantum computing’s true potential.
1. Demand for Quantum Is Real
While classical HPC and GPUs remain critical, quantum computing addresses problems classical systems struggle with—like large-scale optimization, certain AI subroutines, and molecule-level simulations in pharmaceuticals. Major corporations and governments aren’t investing billions in quantum R&D for novelty; they see the path to practical applications and returns.
2. Concrete Use Cases
Drug Discovery: More accurate quantum simulations of molecular interactions could shorten R&D cycles and save billions—a significant incentive for pharma giants.
Post-Quantum Security: Even with new cryptographic standards like Dilithium and Kyber, “harvest-now, decrypt-later” threats make quantum-safe solutions essential.
3. Market Timelines Aren’t All or Nothing
“Quantum winters” may come and go, but history shows us that setbacks often precede breakthroughs. IBM, Google, Microsoft, and others have released tangible roadmaps. Incremental gains in error correction, qubit fidelity, and quantum software prove we’re not simply guessing—we’re building toward real milestones.
4. The Bigger Picture
Skepticism aside, quantum computing’s lure isn’t just raw speed; it’s the unique advantage of harnessing quantum effects for complex tasks. Even if full-scale, fault-tolerant machines are still on the horizon, intermediate systems are already finding niche applications.
In closing, we appreciate Martin Shkreli’s candor and contrarian insights—much like a rare hip-hop collectible, disruptive ideas can spark excitement (or controversy!). But if we “Check the Rhime” in the quantum community, it’s clear that breakthroughs will arrive far sooner than 2075.
At Qryptonic, we remain confident that quantum computing will prove its worth in cybersecurity, pharmaceuticals, AI, and beyond—offering more than just a speculative dream, but a practical reality that’s unfolding faster than many realize.
Qryptonic, LLC Research Team
www.qryptonic.com
“Securing Tomorrow, Today.”