In this episode, we talk with Cameron Pfeiffer, a (recent) ultra-marathoner and GenAI enthusiast, who shares his unique journey from alpaca ranching and theater arts to obtaining a PhD in financial economics and working in a generative AI startup. 

Cameron dives into the strengths of Julia, benefits of structured text generation, the evolution of his programming skills, his favourite GenAI use cases and what he thinks the future of coding might look like.

Chapters

[03:35] Cameron’s background

[07:00] Path to programming

[11:50] Path to Julia language

[18:10] First GenAI use cases

[23:00] On JuliaGenAI and the benefits of Julia

[33:10] Daily GenAI use cases

[39:05] Use cases for students

[41:40] On structured text generation

Links

• TV show recommendations: Game Changer from College Humour, Make some noise

• Outlines package and Cookbook with structured generation use cases

• Blog on some of the advantages of structured generation:  Coalescence: making LLM inference 5x faster

• Dottxt and Sign up form for dotjson

• Cameron’s favourite package: Turing.jl

• On Julia’s esthetic beauty: BeautifulAlgorithms.jl

• Project Euler for computational problems

• JuliaGenAI org and the Awesome Julia GenAI List⁠

• V0 for playing with Generative UI

• Book: Singularity by sky

Interested to join the community? Join the ⁠Julia Slack⁠ and channel #generative-ai

To stay informed about the various GenAI projects, check out the ⁠Awesome Julia GenAI List⁠

If you have any feedback for me or the podcast in general, please share it via DM on Julia Slack (@svilup / Jan Siml) or in the ⁠Discourse announcement post⁠

Thank you for listening!