San Francisco: Nvidia is planning to introduce a new computer chip designed to make artificial intelligence systems respond faster and more efficiently, according to a report published by The Wall Street Journal and cited by Reuters.
The upcoming processor is expected to focus on AI inference, the stage when artificial intelligence systems generate answers and perform tasks for users. This is the part of AI that runs continuously when people use chatbots, virtual assistants, search tools and other smart applications.
The chip may be unveiled at Nvidia’s annual GTC developer conference. Reports indicate that the technology will include elements from Groq, a startup known for designing processors that handle language processing tasks at high speed.
Industry experts say the move reflects a shift in the AI industry. While companies have spent heavily on training large AI models, the growing demand now is for faster and more energy efficient systems that can deliver real time results to millions of users.
The new chip could help reduce costs and energy consumption for companies running AI services at scale. This is becoming increasingly important as global demand for AI driven applications continues to grow.
The development also comes amid rising competition. Major cloud providers and technology companies are investing in their own AI chips to lower costs and reduce reliance on external suppliers. Companies such as Google and Amazon are building custom processors, while startups are offering alternatives designed specifically for AI workloads.
Reports also suggest that OpenAI and other major AI developers have been exploring different hardware options to improve performance and efficiency. Nvidia’s new processor could become part of future AI infrastructure for large technology firms.
Nvidia remains the leading supplier of chips used to train artificial intelligence models. With this new effort focused on inference processing, the company aims to strengthen its position as demand shifts toward faster, more affordable AI services worldwide.
The announcement highlights how the AI industry is moving from building powerful models to deploying them at global scale, where speed, efficiency and cost are becoming the most important priorities.