Challenges in Adopting Quantum Technology

Quantum Computing’s Roadblocks: The 3 Barriers Holding Back the Revolution ⸻ Why Quantum Isn’t Mainstream—Yet Quantum computing promises to revolutionize industries—from drug discovery to AI—by solving problems conventional computers can’t touch. Yet despite the buzz, practical quantum computing is not widely adopted. The reason? The field still faces three major barriers—technical, societal, and infrastructural—that must be overcome before it can fulfill its transformative potential. ⸻ The Three Major Barriers to Adoption 1. Technical Complexity • Qubit Stability: Qubits are highly sensitive to their environment and can lose coherence (i.e., stability) after mere milliseconds. • Error Rates: Even short computations often introduce significant errors, making output unreliable. • Scalability: While small-scale quantum devices exist, scaling them to thousands or millions of qubits with sufficient fidelity is a massive engineering challenge. 2. Security and Privacy Risks • Quantum Threat to Encryption: Once quantum computers are powerful enough, they could break today’s encryption standards—posing risks to global cybersecurity. • Need for Quantum-Safe Protocols: Organizations must invest now in post-quantum cryptography to protect long-term sensitive data. 3. Societal and Economic Integration • Workforce Gap: Few engineers and scientists are trained in quantum computing, creating a bottleneck for growth. • Infrastructure and Cost: Quantum computers often require ultra-low temperatures and specialized environments, making them expensive to develop and maintain. • Ethical and Regulatory Uncertainty: Societal impacts—such as AI acceleration and surveillance—raise questions that lack regulatory clarity. ⸻ Why It Matters: Timing the Leap For businesses and governments, the quantum era is not a question of “if,” but “when.” The race is on to develop applications and frameworks that will thrive once the barriers fall. Early movers who understand these challenges—and prepare accordingly—stand to gain outsized competitive advantages. Moreover, investments in workforce training, secure infrastructure, and ethical frameworks now will pay dividends as quantum breakthroughs emerge. The companies and countries best prepared for the coming quantum shift will define the future of technology, economics, and geopolitics. https://lnkd.in/gEmHdXZy

The era of quantum computing is closer than we think, and it’s going to change the foundations of digital security. NIST’s recent draft publication, NIST IR 8547 (link in 1st comment), outlines critical steps organizations must take to transition to post-quantum cryptography (PQC). Why This Matters Now ⏩ Quantum computers will eventually break traditional encryption algorithms like RSA and ECC. While secure today, these systems won’t be once quantum systems mature. NIST’s Post-Quantum Standards ⏩ NIST has selected algorithms like CRYSTALS-Kyber (for key establishment) and CRYSTALS-Dilithium (for digital signatures) to lead the transition. What Organizations Should Do ⏩ Inventory Cryptography: Assess where and how cryptographic algorithms are used. ⏩ Test PQC Algorithms: Experiment with hybrid solutions combining classical and quantum-safe algorithms. ⏩ Engage with Vendors: Ensure tech partners are preparing for PQC compatibility. Challenges Ahead ⏩ Performance trade-offs: Some PQC algorithms require more computational resources. ⏩ Interoperability: Integrating new cryptographic methods into legacy systems isn’t trivial. ⏩ Timeline pressure: The longer you delay, the harder it will be to catch up. The message is clear: preparation can’t wait. The organizations that start now will be in a much better position when the quantum era fully arrives.

Everyone seems to have a #HotTake on #quantum stocks and which CEO said what. So naturally, I feel inclined to add to that noise with my own two cents… When will a quantum computer become “useful”? The short answer: nobody knows. The long answer comes down to a discussion of noise and scale. Conventional computers are quite robust to noise. Modern CPUs with their billions of transistors are so robust that you can run one nonstop for millions of hours (at least) before expecting to see even a single transient bit fault occurring. Consequently, most CPUs don’t require any error correction and treat their bits as “essentially perfect.” Quantum operations, on the other hand, are error prone. Engineers & physicists continue to work miracles to drive down noise, but we will never get close to the “essentially perfect” operations we see classically. However, we can encode a “qubit of information” across many physical qubits to create a “logical qubit.” As long as the physical error rates are low enough, error correction techniques on these logical qubits can drive down noise to ultimately create “essentially perfect” logical qubits and gates. Currently, many quantum companies are racing to improve logical qubits and run logical gates on them. Despite the media focus around “demonstrating evidence of the multiverse,” the biggest breakthrough on Google’s new Willow chip was to demonstrate unequivocally that their physical qubits were “good enough” for quantum error correction to take care of the rest. The community now knows with certainty that, with enough physical qubits, it is indeed possible to create “essentially perfect” logical qubits. The other challenge is scale. We are still a long way from a quantum chip with enough qubits to compete with the billions of transistors on a classical chip. Furthermore, if a single logical qubit requires hundreds or even thousands of physical qubits, then treating logical qubits as the quantum analog of transistors in a CPU requires that much more overhead. In our current quantum computing landscape, there are architectures with a few hundred to a few thousand physical qubits. The challenges with scale and noise thus introduce an interesting question for quantum practitioners: Do I work on a larger problem with noisy qubits, or a smaller problem with “perfect” logical qubits? Some companies are focusing heavily on the first option, and believe we are more likely to demonstrate utility scale advantages in quantum computing sooner this way. I would argue that more quantum practitioners are of the opinion that logical qubits are the way to go, even if it means we need to wait longer to work on larger problems. Scaling up a logical qubit quantum computer remains a massive challenge, and there are a lot of “known unknowns” and undoubtedly many "unknown unknowns” to be discovered. As for whether scaling takes 5 years, 15 years, or 30 years… If we knew that answer, then quantum stocks would look very different!

🚀 What Quantum Computing Can Learn from the Semiconductor Industry When I started my career in Japan’s semiconductor industry in the early 1990s, I had a front-row seat to an industry that was rapidly evolving. Semiconductors weren’t always the global powerhouse they are today. In the early days, scaling was uncertain, standardization was non-existent, and commercial adoption was slow. Sound familiar? 🔬 Quantum computing is facing the same challenges today. Multiple architectures, lack of standardization, and uncertainty about commercial viability—these are all hurdles that semiconductors successfully overcame. So, what lessons can quantum computing learn from the semiconductor industry's journey? ✔ Standardization drives adoption. The rise of x86 and RISC in semiconductors created a common ground for mass production and software development. Quantum computing must follow suit. ✔ Scalability breakthroughs define industry success. CMOS technology unlocked exponential semiconductor growth. Quantum computing needs its CMOS moment—whether that’s through error correction, new qubit materials, or better fabrication techniques. ✔ An ecosystem is everything. The semiconductor industry didn’t just make chips—it built a global network of software, manufacturing, and enterprise solutions. Quantum computing must focus on building a developer-friendly and business-ready ecosystem. ✔ Commercial viability is the real test. The world adopted semiconductors because they solved real business problems. Quantum computing must find its “killer application” beyond academic research to truly scale. 🚀 Quantum computing has the potential to revolutionize industries, but only if it learns from the past. Will it follow the semiconductor playbook, or will it remain trapped in the lab? Read my full insights below and I’d love to hear your thoughts! 💬 How do you see quantum computing evolving? What challenges do you think it needs to overcome first? Drop a comment below! 👇 #QuantumScaling #QuantumBreakthrough #QuantumCommercialization #QuantumFuture #SemiconductorRevolution #MooresLaw #TechEcosystem #IndustryGrowth #QuantumComputing #SemiconductorIndustry #TechInnovation #FutureOfComputing