#gtc2026

As local AI adoption accelerates, traditional cloud-only inference is no longer sufficient. This article explores how hybrid inference architecture—combining local models with cloud-scale intelligence—enables a new paradigm: the “token factory.”

Instead of treating AI as a monolithic service, this approach distributes token generation across edge devices and centralized systems, optimizing for latency, cost, and scalability. Local models handle high-throughput, low-latency token production, while larger models refine outputs only when necessary—dramatically reducing compute overhead and enabling real-time AI at scale.

With enterprises facing rising inference costs and privacy constraints, hybrid architectures are emerging as a practical solution—delivering near cloud-level performance while maintaining control over data and infrastructure.

If you are building or scaling AI systems, this is a critical architectural shift you cannot ignore.

GTC 2026 made something click for me: AI isn’t just software anymore — it’s infrastructure for producing tokens at scale.

Jensen Huang literally framed future data centers as “factories” whose output is tokens, with metrics like tokens/sec and tokens/watt becoming the new KPIs.

This article explores what that means economically — when compute becomes a consumable and tokens start behaving like a new kind of resource.

🐾😹

GTC 2026에서 삼성전자가 반도체 공정에 AI 에이전트와 디지털 트윈을 적용하겠다는 혁신 비전을 발표했습니다. AI가 공정을 실시간 최적화하고 가상 공장에서 시뮬레이션하는 시대, 한국 반도체의 미래가 더욱 밝아지고 있습니다.

Looks great as always with the jacket #JensenHuang

what a crazy life...