There’s something quietly electric about the idea of an industry gathering where nothing is hypothetical anymore. Tokyo in late November already has that crisp, winter-is-near sharpness in the air, and NTT’s annual R&D Forum feels perfectly timed for this moment—right when quantum computing stops sounding like academic futurism and starts looking like an industrial play. The theme this year, IOWN: Quantum Leap, has a symbolic tone to it, especially after the United Nations declared 2025 the International Year of Quantum Science and Technology, and Japan matched that energy by naming 2025 the first official year of quantum industrialization. You can feel the messaging: this isn’t a preview—this is rollout mode.
What makes this forum interesting isn’t just that NTT is showing demos; it’s that they’re connecting dots across optical computing, AI models, security, and mobility into something that looks like a full ecosystem blueprint. Their IOWN (Innovative Optical and Wireless Network) work is the foundation—moving toward a communication architecture defined by ultra-low latency, ultra-low power, and massive throughput. It’s not incremental. It’s the infrastructure for autonomous systems, agent-level AI interactions, and eventually quantum workloads running like cloud compute today—boring, routine, invisible.
One standout announcement is the partnership between NTT and OptQC. OptQC’s system already operates a world-first optical quantum computer at normal room temperature, which removes one of quantum’s biggest bottlenecks—cryogenic hardware. Together, the goal is bold bordering on cinematic: a one-million-qubit optical quantum computer by 2030. If they get anywhere close to that milestone, the entire computing stack—from cryptography to AI training—changes shape.
The AI side of the event feels more grounded, almost refreshingly pragmatic. NTT’s latest LLM, tsuzumi 2, was built from scratch—not forked, not trained from someone else’s pretrained foundation. It’s lightweight, energy-efficient, and cost-optimized, which hints at a future where enterprise AI isn’t dominated only by giant multimodal behemoths but also by models engineered for local inference, strict privacy, and predictable cost-per-query economics. Then there’s the Large Action Model (LAM), which is basically the next iteration of personalization—not just predicting what users might want, but mapping behavioral flow over time and adjusting marketing actions dynamically. It’s like recommendation engines, but with memory, intent prediction, and contextual timing. Slightly eerie, slightly impressive.
Security threads through everything like a quiet warning. As quantum capacity expands, current encryption might age overnight. This is where NTT’s research arm brings forward something significant: a Quantum-Secure Zero Trust Data Security Suite powered by attribute-based encryption. The interesting part is that ABE isn’t new—it came from an academic paper by Brent Waters and Amit Sahai nearly twenty years ago. Now, after years of being “theoretical but promising,” it finally has a moment where the need aligns with readiness.
And then there’s mobility—where NTT seems genuinely confident. The creation of NTT Mobility, Inc. feels less like a pilot and more like a national roadmap toward Level 4 autonomous driving by 2027. They’re not just building vehicles; they’re building the operating layers beneath remote supervision, sensor quality verification, and rollout logistics. One demo in particular—the system that evaluates remote monitoring video quality in real time and alerts when fidelity drops—may sound niche, but for an autonomous transport ecosystem, that feature is closer to a regulatory requirement than a technical add-on.
Walking through this forum mentally, it feels as if NTT is positioning itself not just as a telecom giant evolving with the times, but as an engineering company writing the blueprint for Japan’s technological posture in the post-classical computing world. Quantum, AI, mobility, and security aren’t presented as separate tracks—they’re converging into a future where infrastructure is intelligent, computation is near-instant, and autonomy is woven into everyday systems.
Maybe that’s the real headline here: we’ve entered a decade where progress isn’t about bigger processors or faster networks; it’s about rethinking what computing is for. And events like this—quiet, technical, slightly understated—are where that shift actually becomes real.
