Both @ericmjl and I are firm believers that Probabilistic Programming has a bright and huge future.

I know other people believe the same. @springcoil has said toe me previously that "PP is the new deep learning" and I understand that @twiecki feels similarly.

What I'd like to do here is amass evidence of the bright future of PP and why we think it will garner increasing adoption.

A few things I've thought of

• FB uses Bayesian techniques and PP, such as Prophet
• PyMC3 has ~5K stars on github: https://github.com/pymc-devs/pymc3
• Bayesian quant methods Quantopian (see here, for example)
• Nate Silver using Bayesian methods for 538
• FFLabs (usually ahead of the curve) had a WP on PPL in 2017
• Growth of academic conferences: PROBPROG2019 and 2020, whole conferences dedicated to the study and application of probabilistic programming languages.
• In 2013, O’Reilly itself published a blog post introducing probabilistic programming.

I appreciate this is very limited!

What other evidence/data is there for the future of PPL?

Note: @ericmjl and I are currently drafting a book proposal for O'Reilly, which motivated this question.

Tagging @fonnesbeck, @ericmjl, @betanalpha, @FrizzleFry, @springcoil, @twiecki, @justinbois, @AllenDowney as you all may have thoughts here. Do feel free to tag anybody else you think may have ideas.

thanks!