As AI continues to evolve, it is reshaping the cloud industry, driving demand for AI infrastructure and specialized cloud solutions. AceCloud, a company specialising in cloud computing services, is adapting to these changes by focusing on AI/ML infrastructure and expanding GPU offerings to support AI workloads, particularly in markets like India where demand is high. In a conversation with TechCircle, Co-founder and Managing Director Vinay Chhabra discussed AceCloud’s approach to simplifying IT for businesses with managed cloud services for storage, analytics, and scalable infrastructure. He also outlined the company’s strategies, expansion plans, and collaborations, aimed at staying ahead of key cloud and AI trends.
According to industry reports, AI workloads are growing at a rate of over 35%, which will significantly drive cloud adoption and expansion. When training large language models (LLMs), substantial AI compute power is required for short periods. For example, training a model may demand a cluster of GPUs for two or three days, depending on the workload size, and then may not be needed again for some time. Using the cloud for these tasks is more efficient than in-house infrastructure, which would require purchasing large amounts of hardware that would remain idle between training sessions. As a result, AI workloads are well-suited for cloud environments.
Read the complete story here: TechCircle
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