Nvidia CEO Jensen Huang took the stage at the company’s annual GTC 2026 conference to introduce a new wave of AI chips and software innovations, reinforcing the company’s focus on the rapidly growing artificial intelligence market. The announcements highlighted Nvidia’s strategic shift toward AI inference, the phase where trained models are deployed to generate real-time responses.
During the keynote, Huang revealed new technologies including the Vera central processor and AI chips developed in collaboration with startup Groq. These chips are designed to enhance performance in inference workloads, which are becoming increasingly important as AI applications expand across industries.
Nvidia also outlined a new approach to inference computing by dividing the process into two stages: “prefill,” handled by its Vera Rubin architecture, and “decode,” managed by Groq-powered chips. This structure aims to improve efficiency and speed in handling AI-generated outputs, particularly in real-time applications.
In addition to hardware, the company introduced new software initiatives, including NemoClaw, a platform focused on enabling secure and scalable AI agents. This reflects Nvidia’s broader ambition to support the growing ecosystem of autonomous AI systems that can perform tasks independently.
Huang also presented the company’s future roadmap, including upcoming chip architectures such as Feynman, signaling continued innovation in AI infrastructure. These developments come amid increasing competition from other tech giants building custom processors, as demand for AI computing continues to surge.
Overall, Nvidia’s GTC 2026 announcements underline its commitment to leading the next phase of AI evolution, combining advanced hardware with integrated software solutions to capture opportunities in both training and inference markets.
