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Trustworthy A.I.

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Content provided by Jerry Cuomo. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jerry Cuomo or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Welcome to the inaugural episode of the rebranded "Art of Automation" podcast, now titled "The Art of AI." Join your host, Jerry Cuomo, IBM Fellow and VP for Technology, and guest Dr. Ruchir Puri, IBM Fellow and Chief Scientist at IBM Research, as they explore the fundamental theme of this series: "Trustworthy AI for Business." Listen in as they discuss the importance of data governance, responsible AI practices, and transparent model training to ensure that AI systems earn trust and deliver reliability in the business landscape.

In this episode, Ruchir's analogy of a blender illustrates "Un-Trustworthy AI." Just as a blender turns ingredients into an unrecognizable smoothie, AI can consume data without retaining its origin. To ensure trust, proper data governance and attribution are vital. AI models should provide clear sources for their recommendations, fostering credibility and informed decision-making. Trustworthy AI combines responsible practices and transparency, empowering users to harness its potential with confidence.

Ruchir introduces IBM's pioneering watsonx platform as a data and AI platform that’s built for business. He explains that enterprises turning to AI today need access to a full technology stack that enables them to train, tune and deploy AI models, including foundation models and machine learning capabilities, across their organization with trusted data, speed, and governance - all in one place and to run across any cloud environment.

The conversation explores the challenge of reducing AI model "hallucinations," where systems generate incorrect information with unwarranted confidence. The hosts discuss ongoing research efforts to address this issue and elevate the overall accuracy of AI outputs.

This episode sets the stage for a thought-provoking series that explores AI's transformative potential for businesses while highlighting the significance of ethics and trust in shaping the AI-driven future.

Key Takeaways:

  • [03:42 - 06:37] What it means for AI to be trustworthy
  • [11:13 - 15:15] The IBM WatsonX Platform
  • [15:25 - 18:15] Addressing AI Model hallucinations

References:

Improving Factuality and Reasoning in Language Models through Multiagent Debate

Watsonx platform

Watsonx; Generative AI for business by Dario Gil, THINK 2023

* Coverart was created with the assistance of DALL·E 2 by OpenAI. ** Music for the podcast created by Mind The Gap Band - Cox, Cuomo, Haberkorn, Martin, Mosakowski, and Rodriguez 
  continue reading

70 episodes

Artwork

Trustworthy A.I.

Wild Ducks

published

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Fetch error

Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on October 02, 2024 12:32 (1M ago)

What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.

Manage episode 372291675 series 2876740
Content provided by Jerry Cuomo. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jerry Cuomo or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Welcome to the inaugural episode of the rebranded "Art of Automation" podcast, now titled "The Art of AI." Join your host, Jerry Cuomo, IBM Fellow and VP for Technology, and guest Dr. Ruchir Puri, IBM Fellow and Chief Scientist at IBM Research, as they explore the fundamental theme of this series: "Trustworthy AI for Business." Listen in as they discuss the importance of data governance, responsible AI practices, and transparent model training to ensure that AI systems earn trust and deliver reliability in the business landscape.

In this episode, Ruchir's analogy of a blender illustrates "Un-Trustworthy AI." Just as a blender turns ingredients into an unrecognizable smoothie, AI can consume data without retaining its origin. To ensure trust, proper data governance and attribution are vital. AI models should provide clear sources for their recommendations, fostering credibility and informed decision-making. Trustworthy AI combines responsible practices and transparency, empowering users to harness its potential with confidence.

Ruchir introduces IBM's pioneering watsonx platform as a data and AI platform that’s built for business. He explains that enterprises turning to AI today need access to a full technology stack that enables them to train, tune and deploy AI models, including foundation models and machine learning capabilities, across their organization with trusted data, speed, and governance - all in one place and to run across any cloud environment.

The conversation explores the challenge of reducing AI model "hallucinations," where systems generate incorrect information with unwarranted confidence. The hosts discuss ongoing research efforts to address this issue and elevate the overall accuracy of AI outputs.

This episode sets the stage for a thought-provoking series that explores AI's transformative potential for businesses while highlighting the significance of ethics and trust in shaping the AI-driven future.

Key Takeaways:

  • [03:42 - 06:37] What it means for AI to be trustworthy
  • [11:13 - 15:15] The IBM WatsonX Platform
  • [15:25 - 18:15] Addressing AI Model hallucinations

References:

Improving Factuality and Reasoning in Language Models through Multiagent Debate

Watsonx platform

Watsonx; Generative AI for business by Dario Gil, THINK 2023

* Coverart was created with the assistance of DALL·E 2 by OpenAI. ** Music for the podcast created by Mind The Gap Band - Cox, Cuomo, Haberkorn, Martin, Mosakowski, and Rodriguez 
  continue reading

70 episodes

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