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In this episode, Dipendra Kumar, Staff Research Scientist, and Alnur Ali, Staff Software Engineer at Databricks, discuss the challenges of applying AI in enterprise environments and the tools being developed to bridge the gap between research and real-world deployment.
Highlights include:
- The challenges of real-world AI—messy data, security, and scalability.
- Why enterprises need high-accuracy, fine-tuned models over generic AI APIs.
- How QuickFix learns from user edits to improve AI-driven coding assistance.
- The collaboration between research & engineering in building AI-powered tools.
- The evolving role of developers in the age of generative AI.
By Databricks4.8
2020 ratings
In this episode, Dipendra Kumar, Staff Research Scientist, and Alnur Ali, Staff Software Engineer at Databricks, discuss the challenges of applying AI in enterprise environments and the tools being developed to bridge the gap between research and real-world deployment.
Highlights include:
- The challenges of real-world AI—messy data, security, and scalability.
- Why enterprises need high-accuracy, fine-tuned models over generic AI APIs.
- How QuickFix learns from user edits to improve AI-driven coding assistance.
- The collaboration between research & engineering in building AI-powered tools.
- The evolving role of developers in the age of generative AI.

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