# #248: Navigating the Frontier of Generative AI in Business

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Text version: https://stenobird.com/podcast/data-futurology-leadership-and-strategy/248-navigating-the-frontier-of-generative-ai-in-business.md
Podcast: [Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science](https://stenobird.com/podcast/data-futurology-leadership-and-strategy)
Published: 2023-10-23T00:17:13+00:00
Episode link: https://podcasters.spotify.com/pod/show/datafuturology/episodes/248-Navigating-the-Frontier-of-Generative-AI-in-Business-e2au09m
Audio file: https://anchor.fm/s/3fab060/podcast/play/77577974/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2023-9-23%2F352283146-44100-2-67b81694dbb0a.mp3
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Duration seconds: 2354

## Resource

Enterprises must shift focus from chasing rapidly evolving LLM models to identifying high-value, practical use cases. Success depends on integrating generative AI with existing machine learning workflows and robust data governance.

## Highlights
- Main idea: Prioritize finding specific business use cases over chasing the latest model releases
- Practical takeaway: Use Retrieval-Augmented Generation (RAG) to turn cumbersome documentation into searchable, actionable knowledge
- Failure mode: Overlooking the infrastructure costs, such as GPU requirements and API scaling, when moving beyond local experimentation
- Strategic insight: Leverage the current interest in LLMs to secure funding and momentum for broader, traditional machine learning initiatives
- Governance requirement: Implement strict management of PII and data privacy when sending information to cloud-based models

## Topics

Generative AI, Large Language Models, Retrieval-Augmented Generation, Enterprise AI Strategy, Data Governance, Machine Learning, AI Infrastructure, Business Automation

## Chapters
- 4:00 — The Infrastructure Challenge: The necessity of cloud scaling and the significant hardware/GPU costs associated with enterprise-grade LLM deployment.
- 6:50 — Risks and Governance: Addressing the complexities of API costs, data privacy, and managing PII in the cloud.
- 9:50 — The Reality of Production: A perspective on the current state of GenAI, noting that few organizations have achieved large-scale production yet.
- 18:30 — The Power of RAG: Exploring Retrieval-Augmented Generation as a solution for querying massive internal document stores.
- 21:30 — Industry Use Cases: Real-world applications in supply chain, medical, and insurance sectors.
- 30:10 — Governance and Responsibility: The importance of structured methodology and responsible deployment in the era of open-source and proprietary models.
- 36:00 — Strategy Over Technology: Why leaders should focus on organizational change and use cases rather than the rapid cycle of model updates.

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## Transcript

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