During the GTC 2025 conference, Nvidia CEO Jensen Huang discussed the rise of agentic AI and reasoning models, which he believes will revolutionize the computer industry. Agentic AI refers to autonomous applications that make decisions for humans, while reasoning models improve task automation. Huang emphasized that software engineers will soon rely on AI assistance, with the demand for GPUs skyrocketing due to the increased computational needs for inference tasks. He highlighted the shift from traditional coding to generative-based computing, predicting that data centers will evolve into AI factories optimized for generating diverse outputs. This major transformation marks a new era in computing, driven by Nvidia’s innovations in hardware and software.
In his recent keynote at the GTC 2025 conference, Nvidia CEO Jensen Huang highlighted the transformative power of agentic AI, a technology that has the potential to revolutionize not just software development but the entire data center industry. According to Huang, the rise of agentic AI and reasoning models will change how industries automate processes.
Agentic AI refers to AI applications that can make decisions and take actions independently, acting on behalf of humans. Reasoning models, like DeepSeek-R1, enhance this capability by using advanced techniques such as model distillation and a mixture of experts approach. These innovations are seen as the driving force behind the next wave of artificial intelligence, laying the groundwork for intelligent agents that can automate complex tasks across various sectors.
Huang noted that software engineers would be among the first to feel the impact of this shift, with predictions that every engineer will be AI-assisted by the end of the year. “Agents will be everywhere,” he stated, emphasizing the need for new types of computers to support this evolving landscape. As demands for GPU acceleration grow, the infrastructure will need to adapt, moving from traditional data centers to AI-focused environments that Huang referred to as “AI factories”.
In this new paradigm, computers will not just execute software, but also generate code autonomously. Huang explained, “It’s gone from retrieval-based computing to generative-based computing,” indicating a fundamental shift in how software is written and executed.
Nvidia is making strides in optimizing performance and efficiency in data centers, including introducing water cooling systems and advancing to optical networking technologies. As Huang explained, the emergence of agentic AI will require significant computational resources—potentially up to 100 times more than current models utilize for inference tasks.
As companies increasingly adopt these emerging technologies, they will face challenges in balancing factors like accuracy, speed, and power consumption. Huang’s vision is clear: the future of computing lies in machine learning software running on advanced GPUs, shifting the industry into a new era of data center architecture.
In summary, the rise of agentic AI and reasoning models marks a pivotal moment in the tech industry, with Nvidia at the forefront, driving innovations that promise to reshape how we interact with technology.
Tags: agentic AI, reasoning models, Nvidia, GTC 2025, data centers
What is Nvidia doing about inference workloads?
Nvidia is preparing for a big increase in inference workloads. They are focusing on developing technology to support reasoning AI agents, which are becoming more popular.
Why are reasoning AI agents important?
Reasoning AI agents help in making decisions based on data. They use complex algorithms to understand and analyze information, making them valuable in areas like healthcare, finance, and more.
How does this affect Nvidia’s products?
Nvidia will enhance its hardware and software to better handle these AI tasks. This includes improving GPUs and AI frameworks to ensure they can manage the growing demand for quick and accurate inference.
What does “inference” mean in AI?
Inference in AI is the process of making predictions or decisions based on data that has been analyzed. It helps machines understand and react to information, which is essential for many AI applications.
How can businesses benefit from Nvidia’s developments?
Businesses can benefit from improved AI capabilities, leading to faster decision-making and better insights. This can enhance efficiency and productivity, giving them a competitive edge.