Kinda funny how we managed to type the exact same thought at the same time.
You beat me by two mins :)
Readit NewsNo it’s not
Nobody has built a human so we don’t know how they work
We know exactly how LLM technology works
We know _how_ it works but even Anthropic routinely does research on its own models and gets surprised
> We were often surprised by what we saw in the model
https://www.anthropic.com/research/tracing-thoughts-language...
This thread is about what software developers like. It’s common knowledge that many programmers like working with computers because that’s different in specific ways from working with people. So saying that LLMs are just like people doesn’t help here.
Yeah there's a reason there is a stereotype/trope about programmers not liking people. I like a lot of people. But I would hate to work with many of them even if I like hanging out with them.
That said, I do like having an LLM that I can treat like the crappy bosses on TV treat their employees. When it gets something totally wrong I can yell at it and it'll magically figure out the right solution, but still keep a chipper personality. That doesn't work with humans.
Things don’t need to be huge deals to influence behavior or be a net gain.
I bet you’ve taken a shortcut to save less than 1h for example.
I think time is different because it's finite. I admit I'll still opt for store brand to save a few bucks even making an engineering salary. But I'll also do something "illegal" (like parking at a metered spot without paying) to save time or otherwise do what I want and just deal with whatever financial cost incurred if I know it won't break me.
A saying I've heard is that if the punishment for a crime is financial, then it is only a deterrent for those who lack the means to pay. Small business gets caught doing bad stuff, a $30k fine could mean shutting down. Meta gets caught doing bad stuff, a billion dollar fine is almost a rounding error in their operational expenses.
It’s under 5 hours of GDP for Texas. It’s a big fine, but not a huge deal for either party.
So what's the point? If neither party is really affected by a penalty (no diacernible benefit or loss to either), then is it all just performative?
Maybe I just answered my own question.
abustamam commented on I now assume that all ads on Apple news are scams kirkville.com/i-now-assum... · Posted by u/cdrnsf
Ever since Apple moved to Services Strategy in 2014 it has been like this. Services were not there so they could provide a better experience for its "customers". I use the word "customer" here which is what Apple / Steve Jobs used to call their loyal fans, and not user. But to further growth their Revenue pie because they foresee iPhone one day will stagnant.
You now have Apple Fitness+, Apple TV, News, Music, Arcade. None of these are of any quality of what Apple used to be. It is really sad.
Oh and the most iconic thing? Apple was the one who tried to kill internet ads between 2017 - 2020.
"The only people who call customers 'users' are drug dealers and software companies."
Yes, because there’s value in a common reference for comparison. It helps to shed light on different models’ relative strengths and weaknesses. And, just like with performance benchmarks, you can learn to spot and read past the ways that people game their results. The danger is really more in when people who are less versed in the subject matter take what are ultimately just a semi tamed genre of sales pitch at face value.
When such benchmarks aren’t available what you often get instead is teams creating their own benchmark datasets and then testing both their and existing models’ performance against it. Which is eve worse because they probably still the rest multiple times (there’s simply no way to hold others accountable on this front), but on top of that they often hyperparameter tune their own model for the dataset but reuse previously published hyperparameters for the other models. Which gives them an unfair advantage because those hyperparameters were tuned to a doffeeent dataset and may not have even been optimizing for the same task.
Thanks, that makes sense!
All shared machine learning benchmarks are a little bit bogus, for a really “machine learning 101” reason: your test set only yields an unbiased performance metric if you agree to only use it once. But that just isn’t a realistic way to use a shared benchmark. Using them repeatedly is kind of the whole point.
But even an imperfect yardstick is better than no yardstick at all. You’ve just got to remember to maintain a healthy level of skepticism is all.
Is an imperfect yardstick better than no yardstick? It reminds me of documentation — the only thing worse than no documentation is wrong documentation.
There is corruption everywhere. But do you deny that these organizations by-and-large provided aid and therefore saves the lives of folks who may have otherwise died from illness?
This doesn't make corruption OK. But he tore out a lifeline for some people without giving them an alternative way to get aid.
Everything you said right now holds equally true for chemical engineering and biomedical engineering so like you need get some experience
That doesn't mean complex systems never behaved unexpectedly, but the engineering goal was explicit determinism wherever possible: predictable execution, bounded failure modes, reproducible debugging. That tradition carried through operating systems, compilers, finance software, avionics, etc.
What is newer is our comfort with probabilistic or emergent systems, especially in AI/ML. LLMs are deterministic mathematically, but in practice they behave probabilistically from a user perspective, which makes them feel different from classical algorithms.
So I'd frame it less as "determinism is new" and more as "we're now building more systems where strict determinism isn't always the primary goal."
Going back to the original point, getting educated on LLMs will help you demystify some of the non-determinism but as I mentioned in a previous comment, even the people who literally built the LLMs get surprised by the behavior of their own software.