emphasizes agentic AI’s potential in manufacturing.
Chris Penrose, NVIDIA vp, forecast the blooming of the manufacturing AI period via agentic synthetic intelligence (AI) and suggested that Korea must also pursue AI full-stack ecosystem cooperation in preparation for this improvement.
In an interview performed via SK Telecom Newsroom on Nov. 5, Penrose said, “The subsequent large step within the AI business is the rise of agentic AI, which can evolve into AI that may perceive context, assume independently, make plans, and act autonomously by combining generative fashions with superior reasoning capabilities.” He stated, “By means of this improvement, AI will set up itself as ‘digital workforce’ that leads productiveness and innovation throughout industries, past being a easy ‘software,’” and added, “Manufacturing AI primarily based on agentic AI will take a leap ahead.”
Penrose forecast that corporations will convert information into intelligence and automate advanced enterprise processes via agentic AI. Such modifications will drive the leap of producing AI. Manufacturing AI is a expertise that permits robots and machines to understand, assume, and act inside bodily environments, extending the area of agentic AI to the true world. He stated, “Manufacturing AI will open a brand new period of business innovation the place autonomous methods able to studying and adaptation will increase human capabilities throughout numerous industries together with manufacturing, automotive, and healthcare.”
Amid these speedy modifications, NVIDIA is reworking into an organization that focuses on full-stack AI infrastructure past present accelerated computing. Penrose emphasised, “Producing intelligence at giant scale requires an ‘AI manufacturing unit’ that tightly integrates high-density computing and secure networking, going past merely growing process pace,” and “As agentic AI methods turn into extra subtle, reasoning capabilities are anticipated to explosively enhance computational demand, making environment friendly {hardware}, versatile scaling, and elastic useful resource allocation essential in next-generation AI factories.” NVIDIA continues to take a position throughout {hardware} stack (Blackwell GPU, BlueField DPU, Spectrum-X Ethernet) and full-stack inference platform (NIM microservices, Dynamo, TensorRT) to reply to such demand. Penrose emphasised, “NVIDIA’s objective is to assist builders in all business sectors to construct, customise, and deploy agent AI at scale,” and “For this function, we’re constantly investing in turnkey blueprints for speedy answer improvement, open-source fashions for specialised inference, sturdy frameworks for coaching and lifecycle administration, and pre-built microservices that may be quickly utilized to enterprise environments,” including, “Korea additionally wants steady efforts in expertise, expertise, and full-stack ecosystem cooperation to keep up its present management.”
He stated, “Korea’s AI ecosystem is in an advantageous place to guide innovation throughout all business sectors via strategic investments spanning AI infrastructure, fashions, and platforms,” and “As agent AI and superior reasoning methods mature, the AI ecosystem will face new challenges akin to increasing AI factories, effectively offering low-latency inference, integrating AI agent workflows, and strengthening workforce deployment and administration capabilities.” He additionally added, “I imagine Korea has many alternatives in all areas together with digital twins, robotics, semiconductor design, and AI brokers.”
He additionally talked about SK Telecom’s telecommunications-based AI technique. He stated, “SK Telecom’s AI technique implements acceptable investments and partnerships needed to understand NVIDIA’s envisioned ‘AI native’ telecommunications firm imaginative and prescient and is solidifying its function as a sovereign AI platform firm,” and “Telecommunications corporations like SK Telecom will encounter alternatives in constructing clever edge inference platforms akin to AI-RAN and utilizing agent AI to handle the complexity and uncertainty of inter-agent communication inside networks.”
