zachwill

One gallon of almond milk requires 1,600+ gallons of water (likely much more — given some estimates are each almond requires up to 3 gallons of water). US almonds are almost entirely grown in California and consume 1.5T to 2T gallons of the state’s water.

It’s pretty dumb to compare AI/data center usage to water usage when something that’s actually wasteful such as almond milk exists.

There’s better metrics to make one’s anti-AI point.

Big fan of Windmill here! Use it heavily. The way you guys integrate seamlessly with Bun/DuckDB/Postgres/Python is just fantastic. Keep up the great work, Ruben!

It’s a very good post — and I do agree with the main ideas. It’s pretty remarkable how good writers like Scott Alexander and others are able to consistently pump out good writing, especially when the key does seem to always comes down to clarity (and mostly revision for me). Maybe reps are able to give that over time, but even with getting older and now being able to bounce ideas off LLMs == it still takes me so many iterations before I feel like my prose / ideas / outlines are worth sharing.

Thanks for this! I had been meaning to mark a phantom notification as read — and this snippet came in handy.

We’ve similarly had a lot of success with self-hosting Windmill.

Super insightful. I hadn’t been able to articulate the same feelings.

    Even as Next seppukus itself,
    people will likely just fall back 
    to React on Vite…

This is my exact read on the situation, as well. I’m not sure if anything can meaningful affect React’s domination in the short-term or medium-term, even with the accumulation of poor choices.

This is really well done!

I tried Deno for awhile — the ability to run Jupyter notebooks was a cool idea — but I’ve been Bun-only for around a year now. It’s just significantly faster and easier to use.

Congrats, Tom!

I’ve been primarily a Python developer since 2012 and recently switched to uv. The ability to manage dependencies, venv, and multiple Python versions makes it best-in-class now. It really is a fantastic tool.

As someone coming from the Python data science / Jupyter side: holy crap this is lightning fast. Kudos! Very impressive work.

An insightful comment! Had never drawn those parallels before -- great call.

Holy crap, that Mac OS 9 one is fantastic!!!

Examine.com does something similar for health related studies, and I've found it valuable in the past.

Note: I haven’t worked with PDF bank statements.

My current solution is pdfplumber → GPT-3 API. I played around with a few different options, and this is personally what’s worked best for my use cases.