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The Earley AI Podcast with Seth Earley - Episode #57 Understanding AI and Data Readiness with Camden Swita

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Content provided by Seth Earley & Chris Featherstone, Seth Earley, and Chris Featherstone. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Seth Earley & Chris Featherstone, Seth Earley, and Chris Featherstone 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://ro.player.fm/legal.

In this episode of the Earley AI Podcast Camden Swita, the Head of AI and ML Innovation at New Relic, joins us for an insightful discussion on the transformative role of AI in modern technology. With a rich background spanning journalism, product management, and cutting-edge AI/ML initiatives, Camden brings a unique perspective on leveraging artificial intelligence to enhance both professional and creative workflows.

Camden joins our hosts, Seth Earley and Chris Featherstone, as they navigating the complexities of data readiness and AI operations

Key takeaways:

  • Understanding Vendor Offerings and Data Infrastructure: The importance of scrutinizing vendor promises and the potential of building simpler AI solutions, like basic chatbots, in-house. Consulting legitimate data scientists and engineers to assess data readiness before plunging into AI investments was highly recommended.
  • Impact of Generative AI on Content Creation: Generative AI's role in automating content creation is rapidly evolving. While it offers incredible efficiencies in some areas, its application in creative writing is still experimental and requires a balance between traditional methods and automation.
  • Modular Retrieval Augmented Generation (RAG): The concept of Modular RAG was explored as a way to enhance language models with relevant context. This system uses specific data sources to fill knowledge gaps, making responses more accurate and targeted. The discussion included how visual tools like heatmaps can identify and improve sparse contexts.

Quote from the show:

"Understanding the actual capabilities of AI systems and the state of your own data infrastructure is crucial. Investing in foundational data work isn't glamorous, but it's the backbone of any successful AI implementation. Without it, even the most advanced algorithms can't deliver meaningful results." - Camden Swita

Links:
LinkedIn: https://www.linkedin.com/in/camden-swita-54a41aa/

Website: https://newrelic.com

Thanks to our sponsors:

  continue reading

59 episoade

Artwork
iconDistribuie
 
Manage episode 447271643 series 2984858
Content provided by Seth Earley & Chris Featherstone, Seth Earley, and Chris Featherstone. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Seth Earley & Chris Featherstone, Seth Earley, and Chris Featherstone 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://ro.player.fm/legal.

In this episode of the Earley AI Podcast Camden Swita, the Head of AI and ML Innovation at New Relic, joins us for an insightful discussion on the transformative role of AI in modern technology. With a rich background spanning journalism, product management, and cutting-edge AI/ML initiatives, Camden brings a unique perspective on leveraging artificial intelligence to enhance both professional and creative workflows.

Camden joins our hosts, Seth Earley and Chris Featherstone, as they navigating the complexities of data readiness and AI operations

Key takeaways:

  • Understanding Vendor Offerings and Data Infrastructure: The importance of scrutinizing vendor promises and the potential of building simpler AI solutions, like basic chatbots, in-house. Consulting legitimate data scientists and engineers to assess data readiness before plunging into AI investments was highly recommended.
  • Impact of Generative AI on Content Creation: Generative AI's role in automating content creation is rapidly evolving. While it offers incredible efficiencies in some areas, its application in creative writing is still experimental and requires a balance between traditional methods and automation.
  • Modular Retrieval Augmented Generation (RAG): The concept of Modular RAG was explored as a way to enhance language models with relevant context. This system uses specific data sources to fill knowledge gaps, making responses more accurate and targeted. The discussion included how visual tools like heatmaps can identify and improve sparse contexts.

Quote from the show:

"Understanding the actual capabilities of AI systems and the state of your own data infrastructure is crucial. Investing in foundational data work isn't glamorous, but it's the backbone of any successful AI implementation. Without it, even the most advanced algorithms can't deliver meaningful results." - Camden Swita

Links:
LinkedIn: https://www.linkedin.com/in/camden-swita-54a41aa/

Website: https://newrelic.com

Thanks to our sponsors:

  continue reading

59 episoade

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