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Sisällön tarjoaa Pamela Gupta. Pamela Gupta tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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Building Trustworthy Generative AI and LLMS

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Manage episode 404858567 series 3501747
Sisällön tarjoaa Pamela Gupta. Pamela Gupta tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

In this episode of "Trustworthy AI: De-risk business adoption of AI" your host Pamela Gupta is talking with a authority on Trustworthy Generative AI and LLMS, Krishnaram Kenthapadi.

Chief AI Officer & Chief Scientist of Fiddler AI, Krishnaram is leading initiatives on generative AI, on AI safety, and trustworthiness, as well as the technical strategy, customer-driven innovation, and thought leadership for Fiddler. He received his Ph.D. in Computer Science from Stanford University, went on to research at Microsoft, represented LinkedIn at Microsoft's AI Ethics Advisory Board, was the Principal Scientist at Amazon, where he led the responsible AI initiatives in AWS ML, and shaped new initiatives such as Amazon SageMaker Clarify from inception to launch.
Join us for a in depth discussion on:

1. What is trustworthiness of LLMS

2. Trustworthy AI Challenges for LLMs; Are they different from predictive AI?

3. How does it impact businesses – is it different between organizations creating than those implementing?

4. What are some ways of deplying Trustworthy LLMS? Is testing LLM pre deployments sufficient and effective for production performance?

5. What can companies do to prepare for Responsible AI by design;

6. Incentives for different stakeholders.

7. Prepare for current and upcoming future by drawing parallels with synthetic biology?

Can Trustworthy AI help De-Risk adoption of AI? ‘Can Trustworthy AI can be instrumental in helping organizations gain a competitive edge and promote better business outcomes, including accelerated innovation with AI’.?
With extensive experience in global industry leadership in areas of Business Strategy, Technology, and Cybersecurity, Pamela helps clients in creating a strategic approach to achieving business value with AI by adopting a holistic risk based approach to AI Trust. She defined 8 essential pillars of trustworthy AI. Read more details at Trustedai.ai website.

Her insights have shaped the way we look at the impact of Cyberwarfare on Business, strategies for efficient digital transformation, and governance views on Algorithmic failures.

Join Pamela as she delves into her signature framework, AI TIPS, standing for Artificial Intelligence Trust, Integrity, Pillars and Sustainability. This podcast is all about operationalizing governance and building Trustworthy AI systems from the ground up.

For questions or comments on this podcast reach out to me.
To request an AI adoption assessment

  continue reading

29 jaksoa

Artwork
iconJaa
 
Manage episode 404858567 series 3501747
Sisällön tarjoaa Pamela Gupta. Pamela Gupta tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

In this episode of "Trustworthy AI: De-risk business adoption of AI" your host Pamela Gupta is talking with a authority on Trustworthy Generative AI and LLMS, Krishnaram Kenthapadi.

Chief AI Officer & Chief Scientist of Fiddler AI, Krishnaram is leading initiatives on generative AI, on AI safety, and trustworthiness, as well as the technical strategy, customer-driven innovation, and thought leadership for Fiddler. He received his Ph.D. in Computer Science from Stanford University, went on to research at Microsoft, represented LinkedIn at Microsoft's AI Ethics Advisory Board, was the Principal Scientist at Amazon, where he led the responsible AI initiatives in AWS ML, and shaped new initiatives such as Amazon SageMaker Clarify from inception to launch.
Join us for a in depth discussion on:

1. What is trustworthiness of LLMS

2. Trustworthy AI Challenges for LLMs; Are they different from predictive AI?

3. How does it impact businesses – is it different between organizations creating than those implementing?

4. What are some ways of deplying Trustworthy LLMS? Is testing LLM pre deployments sufficient and effective for production performance?

5. What can companies do to prepare for Responsible AI by design;

6. Incentives for different stakeholders.

7. Prepare for current and upcoming future by drawing parallels with synthetic biology?

Can Trustworthy AI help De-Risk adoption of AI? ‘Can Trustworthy AI can be instrumental in helping organizations gain a competitive edge and promote better business outcomes, including accelerated innovation with AI’.?
With extensive experience in global industry leadership in areas of Business Strategy, Technology, and Cybersecurity, Pamela helps clients in creating a strategic approach to achieving business value with AI by adopting a holistic risk based approach to AI Trust. She defined 8 essential pillars of trustworthy AI. Read more details at Trustedai.ai website.

Her insights have shaped the way we look at the impact of Cyberwarfare on Business, strategies for efficient digital transformation, and governance views on Algorithmic failures.

Join Pamela as she delves into her signature framework, AI TIPS, standing for Artificial Intelligence Trust, Integrity, Pillars and Sustainability. This podcast is all about operationalizing governance and building Trustworthy AI systems from the ground up.

For questions or comments on this podcast reach out to me.
To request an AI adoption assessment

  continue reading

29 jaksoa

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