281–290 of 320 posts
Earlier quoted context omitted.
The point isn't that this stuff happens. It's that a person who is trying to sell consulting services with ranty "this industry is a sham" and "it's a disgrace that it was even possible" blog posts has a website with just 5 major navigation links...and one of them is 404.
2 brain cells, have you tried reading below the fold of https://hermit-tech.com/business-owners Soy un loser
Earlier quoted context omitted.
The point isn't that this stuff happens. It's that a person who is trying to sell consulting services with ranty "this industry is a sham" and "it's a disgrace that it was even possible" blog posts has a website with just 5 major navigation links...and one of them is 404.
2 brain cells, have you tried reading below the fold of https://hermit-tech.com/business-owners Soy un loser
https://ludic.mataroa.blog/blog/i-accidentally-saved-half-a-...
Never a good sign when a "consulting" company has time to play petulant child.
> All of the AI projects we have observed as a team are failing. Every single one – we have seen 0% success in a year and a half, not only amongst projects we have been asked to participate in, but even within projects that we have observed in passing while doing totally unrelated work. That's got to be hyperbole, which blows out their credibility. They chose to say 'AI' rather than, for example, LLM, or Transformer…
He does employ a lot of hyperbole. Some of his previous blog posts have titles like "I Will Fucking Dropkick You If You Use That Spreadsheet" ( https://ludic.mataroa.blog/blog/i-will-fucking-dropkick-you-... ) and "I Will Fucking Piledrive You If You Mention AI Again" ( https://ludic.mataroa.blog/blog/i-will-fucking-piledrive-you... ). He's not a big fan of polite, corporate speech, I suspect. But I like his style an…
"This is unreasonable.
"Do I seem like a reasonable person?"
Earlier quoted context omitted.
[flagged]
One of the most wild parts of the "Is AI useful" arguments is how different people are getting so astoundingly different results from it. One guy will claim that he can one-shot "Port this unmaintained app from 2017 to modern Android," go do the dishes, and come back to a working application. And the next guy will say, "I can't get it to do anything groundbreaking and have to micro-babysit it every step of the way to…
For the last several years (since GPT 4o) I have written several apps in use by people, making money, entirely with AI/LLMs (me neither writing nor reviewing the code in any meaningful fashion - other than high level architecture, schemas, etc.) and - yes, in a few hours it can do things that would take a normal human weeks (if ever!). But left unconstrained, it will just pile more and more garbage on the pile.
Fable MAX is the thing that gets me much closer to "just send emails" but even then it doesn't look in my specs directory for the spec, it just goes off and does a Jurassic Park-style "It's a Ruby-on-Rails system! I know this!" and disregards all the other ways we send email and writes its own thing. And often I'll go "Where's the button to do X" and it will say "You're right! Nobody asked for it, so this page is an orphan!"
I happen to use Superpower's (https://github.com/obra/superpowers) "brainstorm -> spec -> plan" workflow in e.g. Fable MAX (for anything non-trivial) then I have Fable send to GPT 5.6 Sol XHIGH for execution, with Fable (either the original, or a separate one, depending on the criticality of the task and the blast radius) being the critical reviewer.
Even then, though, I need to continually guide it against the norms and conventions of the codebase/app, because it makes a ton of assumptions.
It doesn't surprise me that if people don't take a fairly rigorous approach to AI-software development then they'll end up with a mess. Even if you buy into "just re-write it" (I happen to think that's where we're ending up) - we aren't there yet and without e.g. a strong test suite, re-writing it is just as likely to create more bugs than it is to fix the existing ones.
Earlier quoted context omitted.
> We're 3 to 4 years into the LLM revolution and the rate of progress is still impressive. The “Attention Is All You Need” paper came out in 2017 and OpenAI released GPT-1 in 2018. ChatGPT was released in late 2022 but that was not the beginning of LLMs. Transformers and generative AI go back even further.
Can you pinpoint the revolution by pinpointing moments of invention and release? Revolution takes time because it’s more about uptake, downstream effects, and feedback.
Earlier quoted context omitted.
It's clear that while LLM progress is continuing, it's at something like a linear rate, or slower. The singularity requires exponential improvement. That's not happening. Maybe we will develop something that sets that off, but there's no indication of that right now.
Yet. If the exponential improvement had already started, the singularity would already have happened or happen very, very soon. The logic has always been that the AI would have to have significant tools and agency to do self-improvement for the singularity to occur. This is exactly the thing that a bunch of the AI labs are working on hard right now.
Earlier quoted context omitted.
I think the biggest realization to me of this whole thing is that most people don't want to turn off their brains. I think we, very naively, thought that some hypothetical life of zero-thought pure-leisure was not only achievable, but desirable. And it's just... not. People want to be challenged, they want to read human material, they want to listen to human music. Sure those like crappy Spotify fake artists might ma…
People say they want to get challenged. > most people don't want to turn off their brains Biologically, life is an effort-minimizing machine. Our brains have a whole system of habit-forming to minimize the enormous amount of energy it takes to think. Whatever people say, give them a way to think less, and they will necessarily prefer it unless they literally are a Buddhist monk, seeking to be aware over every action…
Optimizing the menial is the end-goal, optimizing fun and humanity and expression is not desirable. It's just not, and we're seeing that over and over again.
This part toward the end of the article resonated with me: > If you’re being asked to review huge volumes of terrible AI code, just assume that the organisation is going to burn you out and fire you. You will not convince the person drowning you in 2000 line PRs to stop. Start looking for a new job as if you have already been fired. I have seen this happen many times now I suspect we will see this phenomenon more and…
My F100 corporation has answered this problem by removing code review entirely. Thankfully it's not Boeing or anything important. Yes I am looking desperately for a new job.
This part toward the end of the article resonated with me: > If you’re being asked to review huge volumes of terrible AI code, just assume that the organisation is going to burn you out and fire you. You will not convince the person drowning you in 2000 line PRs to stop. Start looking for a new job as if you have already been fired. I have seen this happen many times now I suspect we will see this phenomenon more and…
My F100 corporation has answered this problem by removing code review entirely. Thankfully it's not Boeing or anything important. Yes I am looking desperately for a new job.
Earlier quoted context omitted.
Do yo have links handy for AI-assisted engineering going positively? The case I have on my mind of it going negatively is this recent Ford case [1] It's not that I believe it couldn't go positively, of course. [1] Ford rehires human engineers after AI fails to match quality checks https://www.bbc.com/news/articles/cgrkd41n2v9o
That Ford story was really misleading. It wasn't about modern LLMs, and the way it was reported implied that Ford had fired and then hired people but if you read closer that wasn't necessarily the case at all - it sounded more like they were re-hiring people who had retired because they needed expertise that had left the company. You need to get through the Bloomberg paywall: https://www.bloomberg.com/news/articles/2…
Oh come on, Simon. Are your glasses so rose coloured they are opaque? They fired, and then re-hired because the AI couldn't do the job. They had to re-hire the quality folks. So, no, it wasn't LLMs, it was quality control -- which is a much more well established domain for automated systems. LLMs are a complete shitshow compared to industrial process automation.
Side question -- do you worry about being so pro-LLM when the promises of LLMs are so clearly falling short?