AI is no longer just a research experiment – it’s running in production at unprecedented speed. Workloads are shifting from training massive models to applying them in real-world tasks, while enterprises navigate GPU shortages, hybrid clouds, and sovereign data requirements.
In a conversation with TechCircle, Vinay Chhabra, Co-founder and Managing Director of AceCloud, explains how the company is focusing on efficient inference and flexible GPU utilization as the foundation for the next phase of AI adoption.
The pace of change has accelerated, especially around GPUs, as cloud and AI workloads move from experimentation to production. What has surprised you most about how this transition has unfolded?
What stands out to me is the speed at which AI is advancing. We did not expect it to move this fast. Almost every day, new AI and LLM models are being released by companies around the world.
Recently, we saw Gemini 3, followed by Mistral 3 from Europe. We are also seeing several models from China, such as DeepSeek and Qwen. This has led to strong competition across regions.
Read More: TechCircle
Vinay Chhabra is the Co-Founder & Managing Director of AceCloud (an RTDS brand), a leading provider of end-to-end cloud computing solutions to global enterprises across industries at scale. As a visionary leader, Mr. Chhabra plays a crucial role in shaping the company’s strategic direction and firmly believes that organizational success hinges on investing in talent and fostering a culture of innovation. His proactive approach involves continuously exploring new opportunities and integrating emerging technologies into AceCloud’s business framework to stay ahead in a dynamic market. Read More..
