Hugo speaks with Dan Becker and Hamel Husain, two veterans in the world of data science, machine learning, and AI education. Collectively, they’ve worked at Google, DataRobot, Airbnb, Github (where Hamel built out the precursor to copilot and more) and they both currently work as independent LLM and Generative AI consultants.

Dan and Hamel recently taught a course on fine-tuning large language models that evolved into a full-fledged conference, attracting over 2,000 participants. This experience gave them unique insights into the current state and future of AI education and application.

In this episode, we dive into:

The evolution of their course from fine-tuning to a comprehensive AI conference
The unexpected challenges and insights gained from teaching LLMs to data scientists
The current state of AI tooling and accessibility compared to a decade ago
The role of playful experimentation in driving innovation in the field
Thoughts on the economic impact and ROI of generative AI in various industries
The importance of proper evaluation in machine learning projects
Future predictions for AI education and application in the next five years
We also touch on the challenges of using AI tools effectively, the potential for AI in physical world applications, and the need for a more nuanced understanding of AI capabilities in the workplace.

During our conversation, Dan mentions an exciting project he's been working on, which we couldn't showcase live due to technical difficulties. However, I've included a link to a video demonstration in the show notes that you won't want to miss. In this demo, Dan showcases his innovative AI-powered 3D modeling tool that allows users to create 3D printable objects simply by describing them in natural language.

LINKS

Episode 33: What We Learned Teaching LLMs to 1,000s of Data Scientists

Vanishing Gradients