What exactly is "data science" these days? (P...

Mat Ryer is back and he brought his impromptu musical abilities with him! We discuss Rob Pike vs thankful AI, Microsoft's GitHub monopoly (and what it means for open source), and Tom Tunguz' 12 predictions for 2026: agent-first design, the rise of vector databases, and are we abo ...  Show more

Linus Torvalds pushes AI generated code, Jordan Fulghum thinks this is the year of self-hosting, FracturedJson formats for compact / human readability, Scott Werner believes a flood of adequate software is coming, and Sean Goedecke explains why generic software design advice is u ...  Show more

Everyone working in data science and AI knows about Anaconda and has probably “conda” installed something. But how did Anaconda get started and what are they working on now? Peter Wang, CEO of Anaconda and creator of PyData and popular packages like Bokeh and DataShader, joins us ...  Show more

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

We have been building platforms and workflows to store, process, and analyze data since the earliest days of computing. Over that time there have been countless architectures, patterns, and "best practices" to ...

We’ve mentioned ML/AI in the browser and in JS a bunch on this show, but we haven’t done a deep dive on the subject… until now! Victor Dibia helps us understand why people are interested in porting models to the browser and how people are using the functionality. We discuss Tenso ...  Show more

The data science field is expanding because so many businesses and other institutions require skilled workers who can manage data as well as provide insights. Companies and students are clamoring for more academic programs. There is great need, but academic institutions are st ...