I don’t know how many people actually know about them. I learned only when I was invited to help at a industrial controls/robotics outfit. You know those little screw-type terminals you might find on a home theater receiver, a car audio amplifier, sprinkler control, thermostat or any other of the myriad things we use that connect directly via wire? One non-secret nobody may have ever told you: those screw terminals require a minimum gauge of solid core, ideally soft (pure copper) wire.

When my grandmother was still a child her family had electrical infrastructure run to their home for the first time. Her dad was so unsure of the new technology that he made it his job to stay up all night under the artificial light of the kitchen lamp to make sure they weren’t turning it off when nobody was looking. It’s been nearly 90 years since Great Grandpa put together his manually implemented check on grid stability, and here I am to take it a level or so deeper.

Attention-based LLMs re-train their learned patterns with attention to context distance, meaning they infer patterns, then collections between concepts as they train. As I understand it this is the thesis of the paper “Attention is All You Need” and it’s new machine learning pattern, transformers. ChatGPT is a generative (it writes things, makes content) pre-trained (they’re not training it on the fly, it has to fit context and is locked to inference) transformer (the attention thingy majig).

There’s something you should know about AI. Elon’s not telling the truth, but that’s not it that’s just a dependent fact. Whether he’s deceiving himself or not, I don’t have too much bandwidth to care. What is obvious to me is that people are not aware of the dimensions of complexity in AI. Dimensions are interesting. You can stack them until you’re dizzy and nothing inherent in the math tells you that they can’t keep overlapping, multiplying the information stored in a single point in the space.

But why? I won’t enumerate the many failures of JavaScript in their entirety. We know, of course, that Mr. Eich the original author of the language agrees that he took some bad advice about type coercion, for example. Instead, this is a personal beef. JavaScript has professionally and personally been a pain point and seems to have had a diminishing use case in my mind as long as I’ve been programming.

There are a whole bunch of things that on the face of it, Go as a programming language seems to be lacking 1. enums -> iota 2. set -> map[type]struct{}{} 3. override -> ... type Option func (c *config) 4. implements -> var _ interface = &myType{} Starting with enumGo lacks the type but gives you the ability to set constant types with simple addition or shifting with iota. This lacks a lot of the type safety, so there are packages like https://github.

You hear that giant sucking sound in the distance? That’s thousands of your money-hungry competition furiously reading and re-reading solutions to Leetcode problems so that they can walk into an interview having spent several hundred dollars to know ahead of time what the likely assessment problems will be and nail them. After this interview they will get offers, if you applied and did not do this secret handshake you will not, and many of them will go on to uneventful careers making enormous amounts of money mostly replying to their team in a messenger of whatever form because of the geometric nature of connections among teams.

On LinkedIn, Facebook, Reddit and other social media platforms I’ve found myself subscribed to both Go specific and web or general programming forums of all types. About once a quarter I’ll stumble onto a post or repository that presents me an API token, database connection string or some other credential. This is frankly unacceptable given how much PII (privately identifiable information) any random database on the internet can provide on users.

Programming, whether you call it ‘dev’ work or ‘software engineering’ almost always includes some amount of work that resembles Data Entry roles. In my past I’ve experienced more and less, but it really makes me think. In this post I’d like to defend what I think are reasonable data entry tasks and draw criticisms against needless ones that represent outstanding requirements. Working for my former employer, it wasn’t exactly data entry that drove me to quit.