We live in an era where AI feels like the final frontier of disruption \u2014 but according to a Nobel Prize-winning physicist, there is something far more consequential waiting just behind it. A features a rare, candid conversation between content creator Ziad Ahmed and John Martinis<\/strong>, the physicist whose 1985 discovery of quantum tunneling in macroscopic electrical circuits effectively laid the hardware foundation for quantum computing. Martinis, who won the 2025 Nobel Prize in Physics for this work and was appointed to President Trump’s science advisory council alongside names like Zuckerberg, Brin, and Jensen Huang, delivers a grounded and sobering timeline: 5 to 10 years<\/strong> before the quantum era arrives in full force. The interview was held at the World Economic Forum in Davos<\/strong>, giving it a distinctly high-stakes geopolitical backdrop<\/a>.<\/p>\n\n\n\n The honest answer is: not one thing \u2014 a convergence of several<\/strong>. The pattern from history is that the next wave doesn’t replace the previous one; it runs on top of it<\/em> while simultaneously making parts of it obsolete. AI is the platform. What’s coming uses AI as infrastructure.<\/p>\n\n\n\n This is where the 5\u201310 year urgency is most concrete. As of right now in April 2026:<\/p>\n\n\n\n Quantum computing currently sits firmly in the NISQ era \u2014 Noisy Intermediate-Scale Quantum \u2014 where processors operate with dozens to a few hundred qubits that remain highly error-prone and fragile. Supaboard<\/a> So we are not there yet. But the milestones are accelerating fast.<\/p>\n\n\n\n IBM has publicly stated that 2026 will mark the first time a quantum computer will be able to outperform a classical computer on a problem it can solve better<\/em> than all classical-only methods \u2014 the threshold that will unlock breakthroughs in drug discovery and other domains. IBM<\/a><\/p>\n\n\n\n In October 2025, Google already demonstrated a 13,000\u00d7 speedup over the Frontier supercomputer using just 65 qubits for physics simulations. Bqpsim<\/a> That is a staggering number from a very small machine.<\/p>\n\n\n\n By 2028, IBM’s roadmap targets a “Starling” system operating 200 logical qubits requiring approximately 10,000 physical qubits \u2014 a tenfold improvement in efficiency over current surface code methods. Quantum Zeitgeist<\/a><\/p>\n\n\n\n The deeper story is the AI \u00d7 Quantum feedback loop<\/strong>: AI systems are already being used to design quantum circuits that humans cannot conceive, while quantum processors are beginning to accelerate machine learning \u2014 each technology accelerating the other’s development. Quantum Zeitgeist<\/a><\/p>\n\n\n\n This is the sleeper issue that most people outside cybersecurity and finance are not thinking about. It deserves its own spotlight.<\/p>\n\n\n\n The next decade’s central challenge for the quantum community is integrating quantum computers into broader computational workflows and building the first large-scale, fault-tolerant machines \u2014 and this must happen with an open, collaborative approach. IBM<\/a><\/p>\n\n\n\n From a security standpoint, the window to act is already open. Institutions that are not<\/em> migrating toward post-quantum cryptographic standards today are building technical debt that will become a liability. Bitcoin’s legacy wallets, government databases, financial infrastructure \u2014 all of these were built before quantum adversaries existed as a realistic threat model.<\/p>\n\n\n\n Experts predict humanoid robots will appear in industrial settings in significant numbers by 2026\u20132028, with broader adoption through the 2030s. The Innovation Mode<\/a> This is being driven directly by advances in AI \u2014 the reasoning and perception capabilities that were impossible five years ago are now available as commodity inference. The bottleneck shifted from software to hardware actuators and cost reduction, both of which are being solved at scale right now by Tesla, Figure, 1X, and others.<\/p>\n\n\n\n Brain-computer interfaces (Neuralink, Synchron, and others) are moving from medical necessity toward performance enhancement. The combination of AI interpretation layers and improved electrode density is compressing what was a 20-year timeline. Within the 5\u201310 year window, expect BCI to move from paralysis patients toward broader cognitive augmentation trials, memory prosthetics, and real-time language translation interfaces.<\/p>\n\n\n\n This one may be the least visible but potentially the most consequential. AlphaFold already collapsed decades of protein structure research into a few years. The next phase is AI-designed molecules<\/strong> \u2014 therapeutics, materials, and organisms \u2014 with quantum simulation as the eventual backend for molecular precision that classical computers cannot achieve.<\/p>\n\n\n\n The critical insight from the Martinis interview applies broadly here: the gap between theoretical readiness and practical deployment is closing fast, and the organizations acting now are the ones setting the terms<\/strong>. Organizations experimenting today gain a 3\u20135 year head start in talent, infrastructure, and algorithm development. Bqpsim<\/a><\/p>\n\n\n\n For someone in your position \u2014 spanning engineering, business strategy, and emerging tech \u2014 the 5\u201310 year window maps roughly like this:<\/p>\n\n\n\n The core takeaway from Martinis’s worldview \u2014 and from what the data is showing across all these fronts \u2014 is that the next disruption does not announce itself loudly<\/strong>. The internet did not say “libraries are about to become obsolete.” Quantum computing is not yet saying “your encryption is broken.” But the physics is already written. The hardware is catching up. And unlike the AI wave, which gave almost everyone a two-year warning window, the quantum transition will arrive with far less runway for the unprepared.<\/p>\n\n\n\n
\n\n\n\n\ud83d\udd2d What’s Actually Coming After AI?<\/h2>\n\n\n\n
\u269b\ufe0f 1. Quantum Computing \u2014 The Big One<\/h3>\n\n\n\n
\ud83d\udd10 2. The Cryptography Crisis \u2014 Urgent, Not Theoretical<\/h3>\n\n\n\n
\ud83e\udd16 3. Humanoid Robots \u2014 Closer Than You Think<\/h3>\n\n\n\n
\ud83e\udde0 4. Neurotechnology \u2014 The Long Game<\/h3>\n\n\n\n
\ud83e\uddec 5. AI-Accelerated Biotech<\/h3>\n\n\n\n
\n\n\n\n\ud83d\udcca Where This Leaves You \u2014 Practically<\/h2>\n\n\n\n
Horizon<\/th> Technology<\/th> Action Signal<\/th><\/tr><\/thead> Now \u2013 2027<\/strong><\/td> AI Agents, Agentic Workflows<\/td> Deploy, not just experiment<\/td><\/tr> 2026 \u2013 2028<\/strong><\/td> Quantum Advantage (specific tasks)<\/td> Learn the landscape, watch IBM\/Google milestones<\/td><\/tr> 2027 \u2013 2030<\/strong><\/td> Post-Quantum Cryptography<\/td> Audit any systems you manage for encryption vulnerability<\/td><\/tr> 2028 \u2013 2032<\/strong><\/td> Fault-Tolerant Quantum Computing<\/td> Competitive advantage in drug, materials, finance<\/td><\/tr> 2028+<\/strong><\/td> Humanoid Robots in Industry<\/td> Relevant for manufacturing, F&B, logistics clients<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
\n\n\n\nYouTube Review | Channel: Ziad Ahmed (Davos Interview Series):<\/h2>\n\n\n\n