Cameron Pfeiffer: From Alpaca Ranching to Structured Text Generation

In this episode, we talk with Pere Gimenez Febrer, a data scientist and developer advocate at Genie, about his journey from studying electrical engineering to working with Julia programming and Generative AI.  Pere shares insights on how AI tools transform his coding workflow, and his personal experiences with various AI applications, including practical tips for tools like ChatGPT, Claude and Midjourney. We also muse about the future of programming and what that could look like. Chapters [05:00] About Genie.jl and his role [09:00] Favourite Julia package [13:10] First GenAI use cases [16:35] Some thoughts on GPT o1 [20:55] Experience with image generation [24:30] Fun GenAI ideas when travelling [27:50] About Genie Discount bot [32:50] Programming’s future? Links Pere’s book recommendation: The Lies of Locke Lamora (series is not finished yet)   Pere’s favourite package: MLJ.jl - swiss-army knife for data science  Genie Framework: https://genieframework.com/ - a great choice for quickly building web apps from your Julia scripts Youtube: Genie Builder Low-code editor Join the Genie Discord to talk with the developers behind Genie Sam Aaron’s keynote talk about Sonic Pi at JuliaCon 2024 Pere’s hobby project for making deployments easier: Carryall.io - the logo was developed with Midjourney 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!

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!

In this episode, we talk with Marcel and Thomas Havlik, identical twins from Budapest who are passionate about Julia programming and Generative AI.  Join us to learn about their journey from gaming hacks to developing advanced AI tools like AISH.jl and EasyContext.jl (to be used together like twins), which aim to automate and revolutionize coding and beyond. Tune in to hear their insights on the advantages of Julia, practical tips and challenges they faced, and some insights on how AI might reshape our work and lives. Chapters: - GenAI conversation starts at 0:27:05 Links Diabtrend - Smart diabetes app EasyContext.jl AISH.jl Youtube: Example of AISH in action Revise.jl Revise.jl is a MUST-HAVE for anyone using Julia, it allows you to modify code and use the changes without restarting Julia. Julia VSCode PR on re-running the last cell 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!

Jun Tian: From Small Town to Large Language Models In this episode, we chat with Jun Tian, a seasoned Julia enthusiast and software engineer at 01.ai. Jun has been working with Julia since the early days and is now at the forefront of generative AI development with the Yi models at 01.ai. Join us as Jun shares his journey in tech, discusses his go-to tools, and offers thoughts on how programming might evolve in the age of AI. Links Jun's Github Jun's personal blog "Oh Human Bandage" - Jun's book recommendation JuliaFormatter.jl HF Nanotron and Jun's (future) aspiration to create something similar for Julia Oolong.jl 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!

Welcome to Julia GenAI Jam, a new podcast hosted by Jan Siml. This teaser introduces the show's focus on the intersection of Julia programming and generative AI. Listeners can expect practical tips, real-world project discussions, and conversations with Julia developers about boosting productivity with AI. The podcast aims to help Julia enthusiasts navigate the AI landscape, tackle challenges, and leverage Julia's strengths in this field.