eadan

This is such a cynical outlook on the world. Of course there are for-profit companies -- most I would argue -- that have a positive impact on the world, and Tesla is one such example.

R + the tidyverse (dplyr, ggplot2 etc.) is easily the most elegant data analysis combo I've used. However, I tend to use Python for this usecase nowadays, primarily to reduce friction when working with others where Python is the lingua franca. Also, RMarkdown is superior to Jupyter notebooks in my opinion.

Yes, and it's a good thing. For once lately, this is the market doing what markets should be doing -- fair price discovery

This is very cool. Relatedly, as a data scientist, I wish companies would expose their APIs through SQL. I've spent a lot of time pulling data into ETL jobs from things like mixpanel, adwords etc., and having a unified interface would make things much simpler.

I'm trying to understand the architecture of Splitgraph. Are all foreign data wrappers controlled directly by you, or can third parties host a database and connect it to Splitgraph in a federation?

I think the fact that binary size has become smaller rather than larger is notable in a world where most other software seems to be increasingly more resource hungry.

The problem with vertical farming is where does the energy come from? An acre of solar panels is not capable of supplying enough energy to grow an acre of crops, even with the efficiency gains we've had in photovoltaics and lighting with wavelengths tuned to crop growth. What's the point in having fields of solar panels when we could have smaller greenhouses filled with crops? If only nuclear energy was politically viable in the west we could have vertical farming and so much more.

It seems you misunderstood the article. When a minority has an intolerant stance about which the majority has no preference towards, the minority wins. For example, the majority doesn't care if all food is kosher. But, the majority would care if all food was vegan.

I agree, the lack of stack traces can be annoying when debugging Go programs. Instead of returning raw errors everywhere, the problem can be alleviated by adding some context to returned errors:

  if err := foo(x); err != nil {
      return fmt.Errorf("foo: bad argument %s", x)
  }

Congratulations on the launch! I've been excitedly waiting for the public release since hearing about HASH on Joel's blog a few months ago. I've been playing with some models over the past few hours and I have a few questions / comments.

First, would it be possible to perform sensitivity analysis on parameters of the model? For example, with the city infection model, run a number of simulations in parallel with different infection rate values, and see how it affects the model output. Relatedly, I think it would be useful to specify a probability distribution over a parameter rather than setting a fixed value. The state space of the model would become exponential in the number of parameters which can vary, so I understand if it's infeasible, at least in the public version.

The real-time spatial and plot views are great. I would like to try some network based simulations. Any plans to add visualizations for these?