Townley

It’s heartening that there are people who find the problem you described “fun”

Writing a FastAPI websocket that reads from a redis pubsub is a documentation-less flailfest

It sounds like their vision for space-based data centers presupposes nearly-free energy costs, delivered via a colossal solar farm made possible by falling launch costs.

Temporarily putting aside (extremely fair) feasibility questions around those two pre-requisites, data centers are a not-bad choice for things to do with unlimited space energy.

Aluminum smelting or growing food are the two I’d think of otherwise, and neither of those can have inputs/outputs beamed to a global network of high-bandwidth satellites.

A competitive geoguesser clearly got there through memorizing copious internet searching. So comparing knowledge retained in the trained model to knowledge retained in the brain feels surprisingly fair.

Conversely, the model sharing, “I found the photo by crawling Instagram and used an email MCP to ask the user where they took it. It’s in Austria” is unimpressive

So independent from where it helps actually improve performance, the cheating/not cheating question makes for an interesting question of what we consider to be the cohesive essence of the model.

For example, RAG against a comprehensive local filesystem would also feel like cheating to me. Like a human geoguessing in a library filled with encyclopedias. But the fact that vanilla O3 is impressive suggests I somehow have an opaque (and totally poorly informed) opinion of the model boundary, where it’s a legitimate victory if the model was birthed with that knowledge baked in, but that’s it.

> These companions can take a variety of forms — in the 2004 study, which looked at 100 6- and 7-year olds, 57 percent of imaginary friends were human, 41 percent were animals, and one was “a human capable of transforming herself into any animal the child wanted.”

Real world data is a messy thing

In C# you can do

string foo = "bar";

string nameOfFoo = nameof(foo); // “foo”

Kinda nice for iterating through lists of variables and saving them to a key/value map

At work I’ve recently moved from a Node/TS monolith to “Python+TS react in a sea of .NET microservices I debug and contribute to”

It’s been the second time in my career I’ve been surprised by not hating C# (the first was goofing off with Unity in 2018). The language itself has a lot of niceties; for example a method to turn the variable foo into the string “foo”. The Neovim LSP set itself up just by installing the dotnet executable. And the syntax for creating complex workflows were pretty ergonomic once an experienced .NET dev walked me through what I was even looking at. I still prefer FastAPI + well-typed Python as the backend framework of my dreams… but I’d work in .NET again.

Blazor hasn’t sold me yet, but seems like a fine choice. It fits in the same class of tools to me as Django Templates, HTMX, or JS handlebar rendering. There’s a class and size of apps for which that’s perfect, and there’s some value in a fullstack language keeping your stack monolingual. But IMO the framework should stand on its own against frontend frameworks like React, Vue, or Svelte… with the simplicity of monolingualism added as a cherry on top. Otherwise you’re optimizing towards the number of languages your devs need to learn over which frontend framework would be the best fit for your app. And between the DX and expansiveness of the JS ecosystem, it’s been hard to imagine going back once you’ve spent a few years eating the shamefully-complicated-constantly-shifting-and-reforming elephant that is learning TS React and friends