By Saju Sankarankutty, Senior Vice President and Unit Technology Officer, Cloud, Infosys
The growing adoption of generative AI is driving increased demand for infrastructure that supports these advanced systems. This includes AI-ready hardware and software in data centers, specialized processors, high-powered systems with GPUs, efficient storage and
memory for fast data transfers, and infrastructure to handle massive edge data.
Cloud Infrastructure for AI: Backbone for computational power and scalability
Cloud platforms are emerging as the ideal solution for businesses of all sizes to leverage AI without significant upfront hardware investments. They serve as the backbone for scalable and efficient AI operations by handling data storage, processing, and dissemination. Additionally, these platforms are being enhanced with AI capabilities, further increasing their value.
AI can be described as a catalog sitting atop any cloud platform, offering models and solutions that are customisable for various needs. This highlights the need to modernise cloud infrastructures to better manage resources, billing, and networking for the AI era. AI clouds also employ a combination of InfiniBand and IP-based networking. As the cloud evolves to support AI, it emphasizes the combined use of GPUs and CPUs.
Unparalleled computing power
Cloud infrastructure delivers the computational power required for sophisticated AI models, which were once exclusive to elite institutions. This is made possible by the advent of GPUs (Graphics Processing Units) and advanced CPUs (Central Processing Units). GPUs, particularly those from NVIDIA and AMD, offer the raw computational power necessary for AI tasks, while innovations like Intel's Gaudi simulate GPU capabilities on CPUs, creating a flexible and powerful resource layer. This combination ensures that businesses have the computational muscle needed to train and deploy AI models effectively.
Democratising access to advanced technologies
Cloud infrastructure democratizes access to AI by providing scalable, on-demand resources. This allows startups and small businesses to leverage AI technologies previously available only to large corporations, fostering innovation across industries.
Facilitating collaboration and data sharing
Cloud infrastructure supports collaboration by facilitating the sharing of AI models and datasets across diverse domains. This capability is crucial in today’s interconnected world, where cross- functional teams often need to work together seamlessly. By leveraging the cloud, businesses can easily share insights, collaborate on projects, and accelerate the development of AI solutions.
AI for Cloud: Boosting resilience, security, and efficiency
Enhancing Security
AI plays a pivotal role in enhancing the resilience of cloud infrastructure. By leveraging machine learning algorithms, cloud platforms can predict and mitigate potential failures, reducing Mean Time to Detect (MTTD) and Mean Time to Repair (MTTR). This proactive approach ensures that businesses remain operational even in the face of cybersecurity threats, thereby safeguarding sensitive data and maintaining customer trust.
Driving cost savings and efficiency with data analysis
The convergence of AI and cloud infrastructure automates crucial processes like data analysis, management, security, and decision-making, leading to substantial cost savings. Businesses can streamline their operations, reduce manual intervention, and achieve higher levels of efficiency. For example, AI-powered predictive maintenance can significantly reduce downtime and maintenance costs by proactively identifying potential issues before they become critical.
Cloud plus AI: Accelerating digital transformation
The synergy between AI and cloud computing is a powerful catalyst for digital transformation. By leveraging AI-powered cloud services, businesses can automate routine tasks, gain deeper insights from their data, and make more informed decisions. This transformation enhances operational efficiency and drives innovation, enabling businesses to stay competitive in a
rapidly evolving market.
AI and Cloud: Beating the challenges for success
Despite the clear benefits of AI and cloud integration, businesses face challenges such as setup costs, data security, privacy, and AI model complexities. With a strategic approach and expert guidance, these challenges can be overcome, enabling full realization of AI-driven cloud solutions.
Several companies have already integrated AI and cloud infrastructure to transform their businesses in a big way. For example, telecommunications firms are using AI clouds to offer advanced services. Large enterprises are adopting GPU-as-a-service models to validate AI concepts and foster innovation. These real-world applications highlight the benefits of combining AI with cloud technologies.
The relationship between AI and cloud infrastructure will strengthen as AI evolves, increasing the need for scalable, efficient, and secure cloud solutions. Businesses investing in this synergy today will lead their industries, drive innovation, and achieve sustained growth.