AI Explained

By: Fiddler AI
  • Summary

  • AI Explained is a series hosted by Fiddler AI featuring industry experts on the most pressing issues facing AI and machine learning teams. Learn more about Fiddler AI: www.fiddler.ai
    Copyright 2023 All rights reserved.
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Episodes
  • Inference, Guardrails, and Observability for LLMs with Jonathan Cohen
    Nov 9 2024

    In this episode of AI Explained, we are joined by Jonathan Cohen, VP of Applied Research at NVIDIA.

    We will explore the intricacies of NVIDIA's NeMo platform and its components like NeMo Guardrails and NIMS. Jonathan explains how these tools help in deploying and managing AI models with a focus on observability, security, and efficiency. They also explore topics such as the evolving role of AI agents, the importance of guardrails in maintaining responsible AI, and real-world examples of successful AI deployments in enterprises like Amdocs. Listeners will gain insights into NVIDIA's AI strategy and the practical aspects of deploying large language models in various industries.

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    53 mins
  • What the EU AI Act Really Means with Kevin Schawinski
    Oct 25 2024

    On this episode, we’re joined by Kevin Schawinski, CEO and Co-Founder at Modulos AG

    The EU AI Act was passed to redefine the landscape for AI development and deployment in Europe. But what does it really mean for enterprises, AI innovators, and industry leaders?

    Schawinski will share actionable insights to help organizations stay ahead of the EU AI Act, and discuss risk implications to meeting transparency requirements, while advancing responsible AI practices.

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    46 mins
  • Productionizing GenAI at Scale with Robert Nishihara
    Jul 29 2024

    In this episode, we’re joined by Robert Nishihara, Co-founder and CEO at Anyscale.

    Enterprises are harnessing the full potential of GenAI across various facets of their operations for enhancing productivity, driving innovation, and gaining a competitive edge. However, scaling production GenAI deployments can be challenging due to the need for evolving AI infrastructure, approaches, and processes that can support advanced GenAI use cases.

    Nishihara will discuss reliability challenges, building the right AI infrastructure, and implementing the latest practices in productionizing GenAI at scale.

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    48 mins

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