162: Accelerating Enterprise AI Transformation With Open Source LLMs Featuring Mark Huang of Gradient

The Data Stack Show

Highlights from this week’s conversation include:

• The potential of AI-driven applications (1:34)
• The need for hardware infrastructure in AI experimentation (2:40)
• Oligopoly on the closed side (11:50)
• Advantages of private side vs. open source (13:18)
• Leveraging valuable data within enterprises (16:00)
• The urgency of adopting LLMs in the enterprise (24:02)
• Expansion of LLMs into new business verticals (25:06)
• The challenges of operationalizing LLMs (29:32)
• Seamless experience with OpenAI (37:29)
• Operationalizing with Gradient (38:36)
• The early genesis of Gradient (48:53)
• The democratization of AI through endpoints (51:44)
• What is the future of language models? (54:07)

The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.