At home, she has forbidden her 10-year-old daughter from using chatbots. “She has to learn critical thinking skills first or she won’t be able to tell if the output is any good,” the rater said.
And this is why the vast majority of people, particularly in the USA, should not be using AI. Critical thinking has been a weakness in the USA for a very long time and is essentially a now four-letter word politically. The conservatives in the USA have been undermining the education system in red states because people with critical thinking skills are harder to trick into supporting their policies. In 2012, the Texas Republican Party platform publicly came out as opposed to the teaching of critical thinking skills.
We oppose the teaching of Higher Order Thinking Skills (HOTS) (values clarification), critical thinking skills and similar programs that are simply a relabeling of Outcome-Based Education (OBE) (mastery learning) which focus on behavior modification and have the purpose of challenging the student’s fixed beliefs and undermining parental authority.
This has been going on at some level for more than 4 decades. The majority of people in those states have never been taught the skills and knowledge to safely use these tools safely. In fact, their education has, by design, left them easily manipulated by those in power, and now, by LLMs too.
In other news:
Meet the Drug Dealers That Won’t Let Their Friends Do Their Drugs
Meet the Pimps That Won’t Let Their Kids Become Prostitutes
Meet the People Dismantling Public Education While Their Families All Attend Private Schools
@LordMayor
Meet the software engineer living off-grid in the woods.It’s an old trope, but it rhymes with reality.
@chobeat
I work with AI and use it personally, but I have my own servers running local models which solves tons of privacy concerns. The inaccuracy is another problem but not a big one for me as I know it and will simply fact check. Also, I don’t really use it for knowledge anyway. Just to filter news to my interest, help with summaries and translation etc.
People use AI as some all-knowing oracle but an LLM is not meant for that at all.
This is the correct way to use it. In a field you are already very knowledgeable in, so you can do your own fact-checking. This is absolutely paramount. But most people are content to just copy-paste and don’t even ask the llm for sources.
There are definitely things AI is good for. Archival search is obviously the biggest, because that’s what we’ve been using it for decades. It can also be helpful for subterranean and medical imaging, and art restoration. But the companies selling it want to sell a Magic 8 Ball with ads
Could you elaborate a little on your setup? Sounds interesting
I have one server with a cheap MI50 instinct. Those come for really cheap on eBay. And it’s got really good memory bandwidth with HBM2. They worked ok with ollama until recently when they dropped support for some weird reason but a lot of other software still works fine. Also older models work fine on old ollama.
The other one runs an RTX 3060 12GB. I use this for models that only work on nvidia like whisper speech recognition.
I tend to use the same models for everything so I don’t have the delay of loading the model. Mainly uncensored ones so it doesn’t choke when someone says something slightly sexual. I’m in some very open communities so standard models are pretty useless with all their prudeness.
For frontend i use OpenWebUI and i also run stuff directly against the models like scripts.
How do you know it’s doing any of this correctly, especially filtering and translations?
I mainly use it for Spanish which I have a basic proficiency in. It just accompanies me on my learning journey. It may be wrong sometime but not often. Like the other reply said, LLMs are good at languages, it’s what they were originally designed for until people found out they could do more (but not quite as well).
And as for filtering, I just use it as a news feed sanitizer with a whole bunch of rules. It will miss things sometimes but it’s also my ruleset that’s not perfect. I often come across the unfiltered sources anyway and even if it misses something, it’s only news. Nothing really important to me.
It’s funny, I had half been avoiding it for languages. I had lots of foreign friends and they often lived together in houses and those houses would almost have this creole. They came to learn English and were reinforcing their own mistakes but it was mutually intelligible so the mistakes were reinforced and not caught. I suspect LLMs would be amazing at doing that to people and their main use case along these lines seems like it would be to practice at a slightly higher level than you so I suspect some of those errors would be hard to catch / really easy to take as correct instead of validating
Anyone learning a new language massively benefits from being able to speak with native speakers.
That being said, LLMs are better at languages and translation tasks than any pretty much anything else. If you need vocabulary help or have difficulty with grammar they’re incredibly helpful (vs Googling and hoping someone had the same issue and posted about it on Reddit).
I mean, if you can afford a native speaker tutor that is the superior choice. But, for the average person, an LLM is a massive improvement over trying to learn via YouTube or apps.
And the problem with Reddit–especially with certain language communities–is you’ll get a hallucination rate higher than current LLMs because learners can either overestimate their knowledge or sound off just because they want to show off.
I don’t recommend LLM use for beginners at languages but once they get a semester or two (or the equivalent) under their belt, the instant access to an answer that’s right most of the time is invaluable. Just first get to the point where you can start to recognize “maybe that’s not quite right…” first, and check sources. And definitely check in with natives as much as possible.
I don’t think that’s a problem. I live in Spain and speak Spanish daily with real people, many of them my friends. They’ll correct me if needed, they often do. Though most are my own mistakes.
Don’t forget people give wrong answers too. But people aren’t available 24/7 to help me.
Not OP, but…
It’s not always perfect, but it’s good for getting a tldr to see if maybe something is worth reading further. As for translations, it’s something AI is rather decent at. And if I go from understanding 0% to 95%, really only missing some cultural context about why a certain phrase might mean something different from face value, that’s a win.
You can do a lot with AI where the cost of it not being exactly right is essentially zero. Plus, it’s not like humans have a great track record for accuracy, come to think of it. It comes down to being skeptical about it like you would any other source.
Strongly disagree with the TLDR thing
At least, the iPhone notifications summaries were bad enough I eventually turned them off (but periodically check them) and while I was working at Google you couldn’t really turn of the genAI summaries of internal things (that evangelists kept adding to things) and I rarely found them useful. Well… they’re useful if the conversation is really bland but then the conversation should usually be in some thread elsewhere, if there was something important I don’t think the genAI systems were very good at highlighting it
Completely agree, those summaries are incredibly bad. I was recently looking for some information in Gemini meeting notes and just couldn’t find it, even though I was sure it had been talked about. Then I read the transcript itself and realised that the artificial unintelligence had simply left out all the most important bits.
You can disagree, but I find it helpful to decide whether I’m going to read a lengthy article or not. Also if AI picks up on a bunch of biased phrasing or any of a dozen other signs of poor journalism, I can go into reading something (if I even bother to at that point) with an eye toward the problems in an article. Sometimes that helps when an article is trying to lead you down a certain path of thinking.
I find I’m better at picking out the facts from the bias if I’m forewarned.
iPhone notification summaries were made with GPT3.5 I believe (maybe even the -turbo version).
It doesn’t use reasoning and so when using very short outputs it can produce wild variations since there are not a lot of previous tokens in order to direct the LLM into the appropriate direction in kv-space and so you’re more at the whims of temperature setting (randomly selecting the next token from a SOFTMAX’d list which was output from the LLM).
You can take those same messages and plug them into a good model and get much higher quality results. But good models are expensive and Apple is, for some reason, going for the budget option.
This has a strong whiff of the former Facebook engineers that forbade their families from using the platforms they built.
We’re living in a Black Mirror episode.
we’re living in multiple concurrent Black Mirror episodes… a multifaceted dystopia
AI companies want to sell their product. They tell us all the good stuff. Consumers take the bait. Normal capitalism today.
