[1_over_n]

At our company, we are working with "mechanistic" or mathmatical models rather than stastical approches. I have observed :

1. It is hard than it should be to explain the concept to people (particularly VCs) 2 . people struggle to understand that a mechanistic model could have more utlity than a machine learning black box 3. people think you are doing something wrong if you are not using a neural network 4. The less people understand about neural networks, the more they seem to believe they are appropriate for all predictive / modelling problems 5. There is generally quite a low understanding of scientific method in the startup / VC space (speaking as someone who has worked in and around academia for years) vs how "scientific" people believe they are because it sounds good to be data driven and scientific about running startups and funding them.

[deepnotderp]

Do you mean like symbolic regression or algorithmic information theory based stuff?

If so, I'd love to get in touch, shoot me an email

[1_over_n]

We are using biophysics based approaches. Will send an email over :)

[nickpsecurity]

Send me one, too, if you don't mind. I like collecting these techniques to give to researchers or practitioners wanting to try new things.