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Trustworthy A.I.

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Inhalt bereitgestellt von Jerry Cuomo. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Jerry Cuomo oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.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 Episoden

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Trustworthy A.I.

Wild Ducks

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Manage episode 372291675 series 2876740
Inhalt bereitgestellt von Jerry Cuomo. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Jerry Cuomo oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.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 Episoden

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