In this episode, Peter Wang from Anaconda joins us again to go over their latest “State of Data Science” survey. The updated results include some insights related to data science work during COVID along with other topics including AutoML and model bias. Peter also tells us a bit about the exciting new partnership between Anaconda and Pyston (a fork of the standard CPython interpreter which has been extensively enhanced to improve the execution performance of most Python programs).
Anaconda CEO (and Practical AI guest) Peter Wang:
I am excited to announce the Anaconda Dividend Program, which formalizes our commitment to direct a portion of our revenue to open-source projects that help advance innovation in data science. We are launching the program in partnership with NumFOCUS, and will kick off with a seed donation of $10,000, as well as an additional 10% of single-user Commercial Edition subscription revenue through the end of this year. Going forward, we will fund the dividend with at least 1% of our revenue in 2021, with a minimum of $25,000 committed for the year.
We’ve been beating the successful-businesses-that-thrive-in-large-part-due-to-open-source-software-should-set-aside-revenues-to-support-those-projects drum for years now, so it’s exciting to see forward-looking companies like Anaconda step up and do just that. More like this! 🙏
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 to discuss that and much more. Peter gives some great insights on the Python AI ecosystem and very practical advice for scaling up your data science operation.