Comment by jtonz
4 hours ago
As someone that started using Co-work, I feel like I am going insane with the frequency that I have to keep telling it to stay on task.
If you ask it to do something laborious like review a bunch of websites for specific content it will constantly give up, providing you information on how you can continue the process yourself to save time. Its maddening.
That’s pretty funny when compared with the rhetoric like “AI doesn’t get tired like humans.” No, it doesn’t, but it roleplays like it does. I guess there is too much reference to human concerns like fatigue and saving effort in the training.
This is what happens when a bunch of billionaires convince people autocomplete is AI.
Don't get me wrong, it's very good autocomplete and if you run it in a loop with good tooling around it, you can get interesting, even useful results. But by its nature it is still autocomplete and it always just predicts text. Specifically, text which is usually about humans and/or by humans.
You are not wrong, but after having started working with LLMs, I have this feeling that many humans are simply autocomplete engines too. So LLMs might be actually close to AGI, if you define "general" as "more than 50% of the population".
Yep. The veil of coherence extends convincingly far by means of absurd statistical power, but the artifacts of next token prediction become far more obvious when you're running models that can work on commodity hardware
In my experience all of the models do that. It's one of the most infuriating things about using them, especially when I spend hours putting together a massive spec/implementation plan and then have to sit there babysitting it going "are you sure phase 1 is done?" and "continue to phase 2"
I tend to work on things where there is a massive amount of code to write but once the architecture is laid down, it's just mechanical work, so this behavior is particularly frustrating.
It really is like having an intern, then