The Joe Reis Show

I've spent the last three weeks visiting the UK, Australia, and New Zealand. Here are my observations and anecdotes about the data and ML/AI industry from countless chats with executives, practitioners, and pundits.

Ilya Reznik, an experienced leader in machine learning with a rich background at Adobe, Twitter, and Meta, shares his insights on building effective ML teams. He discusses the challenges of hiring in unfamiliar tech environments and the importance of robust data pipelines. The conversation also touches on the rapid adoption of large language models across industries and the complexities of AI implementation. Ilya highlights the need for innovative thinking and transparency in evaluating machine learning practices while fostering community engagement in Utah's tech scene.

As I travel this Fall, I'm reminded that most people don't work at fancy tech companies. Most people work at traditional companies with "boring" data and tech stacks. And that's OK. Boring is good.

Jordan Morrow has written a ton, including four books. We chat about the process of writing books, the ins and outs of working with a publisher, the role of AI in writing, and much more. If you're interested in writing a book, this is a crash course in what you should know. Enjoy!

Venkat Subramaniam, a renowned programmer, author, and founder of Agile Developer, shares insights from his wealth of experience in software development. He tackles the misconceptions surrounding microservices and emphasizes the importance of truly understanding agile methodologies beyond superficial practices. Venkat discusses the balance of knowledge and wisdom in tech, along with personal journeys in teaching and programming. He also reflects on the joy of hiking, connecting with nature, and the community around it.

Uncle Rico is a character in the movie Napoleon Dynamite, who is stuck in the past, reminiscing about his days as a high school football star. If only he'd won the game and went to the state championship. Some of the data industry reminds me of Uncle Rico. During a recent panel, there was a question about whether AI can help with data management (governance, modeling, etc). Some people were quick to dismiss this, saying that machines are no substitute for humans in their understanding and translating of "the business" to data. Yet why are we still perpetually stuck in the mode of "80% of data projects fail"? Might AI/ML help data management move out of its rut? Or will it stay stuck in the past? Also, please check out my new data engineering course on Coursera! https://www.coursera.org/learn/intro-to-data-engineering

Paco Nathan is a national treasure. He's not only an OG in the field of AI, but he's also instrumental in early hacker and cyberpunk culture. When I first met Paco, it suddenly clicked that I'd seen his name in various cyberpunk and alternative zines back in the 1990s. We have a chat all sorts of crazy stuff, and I feel like we only got to 5% of the stories..

Bethany Lyons, an expert in disrupting the recruitment industry, dives into her innovative approach to hiring. She critiques traditional methods, advocating for personal networks and niche expertise over generic searches. The discussion also covers the challenges of startups and how AI is reshaping job roles, emphasizing the importance of deep problem-solving skills in tech. Additionally, Lyons highlights the significance of reputational capital in influencer marketing and the need for tailored engagement strategies to build trust with audiences.

Dive into the fascinating world of AI and its impact on the workforce. Discover how OpenAI's new reasoning model could revolutionize programming and scientific tasks. The discussion jumps into the historical evolution of technology and its effects on jobs, suggesting a major shift in work dynamics. Plus, get insights into the future of large language models and the host's personal ventures, including upcoming travels and an exciting new data engineering course on the horizon.

Ergest Xheblati, a data architect and author of Minimum Viable SQL Patterns, dives into the timeless elements of tech and data. He shares his journey from software engineering to data architecture, emphasizing the need for strong networking. The conversation highlights key challenges in SQL query writing and the evolution towards modern technologies like Python and MongoDB. Ergest also discusses the shift to self-publishing, sharing insights on engaging an audience and the importance of foundational principles in navigating a rapidly changing landscape.