I am delighted to have Julian Wiffen to talk about some of the latest breakthroughs in generative AI and their application to data engineering.

Julian is Director of Data Science for the Product team at Matillion.

·       To start, Julian could you share a little about your background in Data Science and introduce us to Matillion and its mission?

·       How does an independent services solutions company leverage while adding value to the models generated by the large LLM developers?

·       Can you share your some of the learning and discoveries you’ve made by researching and applying Gen AI to data engineering? 

·       Can you share your thoughts on its impact on the way data science is done? [

·       What do you consider to be the entry-level skillset? 

·       How do you approach teaching and learning skills in the area and what tips would you give a university educator?

·       On the topic of regulation and ethics for data scientists working with Gen AI. There is talk of mandating the 'human in the loop' approach for safety, that may even become regulation. How you see ‘human in the loop’ working?

·       Who are the key data science authors and media you refer to? [books, blogs, pods] 

·       Is there anything you’d like add?

Notes:

Julian’s blogs at Matillion

·       Matillion: The Data Engineer’s Guide to Prompt Engineering part 1 (link)

·       Matillion: The Data Engineer’s Guide to Prompt Engineering part 2 (link)

·       Matillion: The Data Engineer’s Guide to Prompt Engineering part 3 (link)

·       Matillion: Evaluating the performance of different LLMs (link) 

Recommended to follow Andrew Ng, researcher-entrepreneur (homepage)

Acknowledgements

Music 

Title: The World

Artist: Ben Prunty (2012)

Source:  https://www.benpruntymusic.com/

License: Non-transferable license. Permission granted by Ben Prunty

Cover Art 

Title: Complex collaboration for BAEF

Artist: Nuno Machado and Allen Higgins

Source: vignette_version.pptx

License: CC BY-NC-SA 4.0

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