50 min
Unleashing the Power of Private GPTs with Skyflow’s Manny Silva Partially Redacted: Data, AI, Security, and Privacy
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- Technology
Manny Silva, Skyflow’s Head of Documentation, joins the podcast to share his journey of tinkering with generative AI systems and building a private GPT trained on internal Skyflow documents.
Manny discusses his first impression of ChatGPT, how he got interested in this space as a technical writer, and the non-obvious insights he gained along the way. He addresses common misconceptions about GPT, particularly regarding privacy and security. Manny explains the concept of creating a private GPT and explores the reasons why organizations would want to implement it. He provides valuable insights into effectively integrating a private GPT into existing workflows and systems, along with the challenges and considerations companies should be aware of.
Manny shares best practices for training and fine-tuning a private GPT to ensure optimal performance and accuracy. He delves into the impact of his work at Skyflow and the enhanced productivity observed in the field. Finally, Manny looks ahead to future advancements and trends in the field of private GPTs and discusses their transformative potential in the realms of documentation, product launches, and marketing.Topics:
When you first saw ChatGPT, what was your first impression?
As a technical writer, how did you get so interested in this space and start tinkering with the Open AI platform and APIs?
What are some of the non-obvious things you learned as you dove into this?
What are some of the common misconceptions you’re seeing when it comes to GPT, in particular when talking about privacy and security?
What’s it mean to create a private GPT and why would someone want to do that?
How can organizations effectively implement and integrate a private GPT into their existing workflows and systems?
What are some common challenges or considerations that companies should be aware of when building and utilizing a private GPT?
What are some best practices and strategies for training and fine-tuning a private GPT to ensure optimal performance and accuracy?
Can you describe what you built at Skyflow that leverages private GPT?\
What kind of impact are you seeing in terms of yours or other people’s productivity?
Looking ahead, what advancements or trends can we expect to see in the field of private GPTs, and how will they continue to transform the way we work with documentation, product launches, and marketing?
Resources:
Privacy-First AI: Harnessing Snowflake and Skyflow to Customize GPT
Generative AI Data Privacy with Skyflow GPT Privacy Vault
Manny Silva, Skyflow’s Head of Documentation, joins the podcast to share his journey of tinkering with generative AI systems and building a private GPT trained on internal Skyflow documents.
Manny discusses his first impression of ChatGPT, how he got interested in this space as a technical writer, and the non-obvious insights he gained along the way. He addresses common misconceptions about GPT, particularly regarding privacy and security. Manny explains the concept of creating a private GPT and explores the reasons why organizations would want to implement it. He provides valuable insights into effectively integrating a private GPT into existing workflows and systems, along with the challenges and considerations companies should be aware of.
Manny shares best practices for training and fine-tuning a private GPT to ensure optimal performance and accuracy. He delves into the impact of his work at Skyflow and the enhanced productivity observed in the field. Finally, Manny looks ahead to future advancements and trends in the field of private GPTs and discusses their transformative potential in the realms of documentation, product launches, and marketing.Topics:
When you first saw ChatGPT, what was your first impression?
As a technical writer, how did you get so interested in this space and start tinkering with the Open AI platform and APIs?
What are some of the non-obvious things you learned as you dove into this?
What are some of the common misconceptions you’re seeing when it comes to GPT, in particular when talking about privacy and security?
What’s it mean to create a private GPT and why would someone want to do that?
How can organizations effectively implement and integrate a private GPT into their existing workflows and systems?
What are some common challenges or considerations that companies should be aware of when building and utilizing a private GPT?
What are some best practices and strategies for training and fine-tuning a private GPT to ensure optimal performance and accuracy?
Can you describe what you built at Skyflow that leverages private GPT?\
What kind of impact are you seeing in terms of yours or other people’s productivity?
Looking ahead, what advancements or trends can we expect to see in the field of private GPTs, and how will they continue to transform the way we work with documentation, product launches, and marketing?
Resources:
Privacy-First AI: Harnessing Snowflake and Skyflow to Customize GPT
Generative AI Data Privacy with Skyflow GPT Privacy Vault
50 min