Santosh Kumar Radha

Santosh Kumar Radha

Head of Product/Research at

    Santosh is the Head of Product/Research at Agnostiq, where he plays a pivotal role in shaping the company's product strategy, particularly through the development of Covalent which is designed to significantly enhance the scalability and performance of next-generation AI applications and large-scale scientific simulations across multi-cloud environments. Santosh holds a Ph.D in theoretical physics from Case Western Reserve University.

    All Sessions by Santosh Kumar Radha

    Day 1 04/23/2024
    11:00 am - 11:30 am

    From Gen AI to Digital Twins: Powering the Next AI Revolution

    <span class="etn-schedule-location"> <span class="firstfocus">Generative AI</span> </span

    Ai X Talk: In the dawn of the AI industrial revolution, advanced technologies like digital twins, generative AI and multi-agents are revolutionizing industries, predicting weather, training humanoid robots, accelerating drug discovery, and redefining design and manufacturing processes. The vision of multi-agent systems that can mobilize an army of specialized agents to work hand in hand in harmony with humans is rapidly becoming a reality, promising enhanced efficiency and innovation. Yet, these transformative advancements entail a significant surge in computational requirements, straining our existing infrastructures to their limits and necessitating a shift towards a novel infrastructure paradigm. Unlike traditional cloud applications, the compute-intensive AI landscape requires a fundamental rethinking of compute interaction. AI applications necessitate a flexible, hybrid infrastructure to handle their dynamic training and inference needs, diverse resource requirements, and complex queue management stemming from limited, finite resources. This shift introduces challenges for organizations. Custom scripts, disjointed team efforts, and unpredictable cloud expenses can lead to inefficient compute management, increased costs, and delayed time-to-market. Organizations struggle to choose between hyperscale clouds, specialized microclouds, or dedicated AI-centric compute clusters, all while navigating the complexities of a new infrastructure software stack. The main challenges include increased costs due to inefficient compute management, delays in time to market, and the potential for missed opportunities stemming from the complex infrastructure software stack required to support these new computational needs. To address these challenges, the new era of AI needs a unified platform. This requires infrastructure capable of orchestrating high-performance computing, specialized hardware, and cloud resources. Join Santosh as he navigates the complexities of the AI compute landscape, offering practical strategies for success amidst evolving technological frontiers.

    Open Data Science




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