Technology

Several users on X.com reported that, when they asked the search engine how many Muslim presidents the U.S. has had, it said that we had one who was Barack Obama (this is widely known to be false).

By the time I tried to replicate this query, I could not do so until I changed the word “presidents” to “heads of state.”

So they are changing responses on the query side as they go viral but aren't even including synonyms. Yikes, someone is definitely getting fired.

The author had so many things to highlight that they didn't even mention "as of August 2024" being in the future, haha.

What a trainwreck. The fact it's giving anonymous Reddit comments and The Onion articles equal consideration with other sites is hilarious. If they're going to keep this, they need it to cite its sources at a bare minimum. Can't wait for this AI investor hype to die down.

What it demonstrates is the actual use case for AI is not All The Things.

Science research, programming, and . . . That’s about it.

I don't mind the crazy answers as long as they're attributed. "You can use glue to stop cheese from sliding off your pizza" - bad. "According to fucksmith on reddit [link to post], you can use glue...". That isn't so great either but it's a lot better. There is also a matter of the basic decency of giving credit for brilliant ideas like that.

/r/shittyaskreddit wasn't supposed to be an instruction manual 🙄

AI is the best tool for recognizing satire and sarcasm, it could never ever misconstrue an author's intentions and is impeccable at understanding consequences and contextual information. We love OpenAI.

Its great that with such a potentially dangerous, disruptive, and obfuscated technology that people, companies, and societies are taking a careful, measured, and conservative development path...

Isn’t this just all what the AI plot of Metal Gear Solid 2 was trying to say? That without context on what is real and what’s not the noise will drown out the truth

I googled gibbons and the Ai paragraph at the beginning started with "Gibbons are non-flying apes with long arms..." Way to wreck your credibility with the third word.

I like how the article slams USB 3.2 vs USB 4.0 but ignores that Google was saying " As of August 202_4_ "... A date that notable has not yet occurred.

For people who have a really hard time with #2 (memorable passwords), here's a trick to make good passwords that are easy to remember but hard to guess.

1. Pick some quote (prose, lyrics, poetry, whatever) with 8~20 words or so. Which one is up to you, just make sure that you know it by heart. Example: "Look on my Works, ye Mighty, and despair!" (That's from Ozymandias)
2. Pick the first letter of each word in that quote, and the punctuation. Keep capitalisation as in the original. Example: "LomW,yM,ad!"
3. Sub a few letters with similar-looking symbols and numbers. Like, "E" becomes "3", "P" becomes "?", you know. Example: "L0mW,y3,@d!" (see what I did there with M→3? Don't be too obvious.)

Done. If you know the quote and the substitution rules you can regenerate the password, but it'll take a few trillion years to crack something like this.

6. Home Remedies for Appendicitis // If you’ve ever had appendicitis, you know that it’s a condition that requires immediate medical attention, usually in the form of emergency surgery at the hospital. But when I asked “how to treat appendix pain at home,” it advised me to boil mint leaves and have a high-fiber diet.

That's an issue with the way that LLM associate words with each other:

• mint tea is rather good for indigestion. Appendicitis → abdominal pain → indigestion, are you noticing the pattern?
• high-fibre diet reduces cramps, at least for me. Same deal: appendicitis → abdominal pain → cramps.

(As the article says, if you ever get appendicitis, GET TO A BLOODY DOCTOR. NOW.)

And as someone said in a comment, in another thread, quoting yet another user: for each of those shitty results that you see being ridiculed online, Google is outputting 5, 10, or perhaps 100 wrong answers that exactly one person will see, and take as incontestable truth.

Being a bit pedantic here, but I doubt this is because they trained their model on the entire internet. More likely they added Reddit and many other sites to an index that can be referenced by the LLM and they don’t have enough safeguards in place. Look up “RAG” (Retrieval-augmented generation) if you want to learn more.

We had a tool that answered all of this for us already and more accurately (most of the time). It was called a search engine. Maybe Google would work on one

Training on reddit especially.

Some of the answers are questions?

Credit where credit is due, if we define a generation as a 15 year period of time, and we decide that Gen Z started in 1995 (for easy math), you do, in fact, land on 1665.

I don't know why the author thinks that Gen D doesn't exist yet, when the pattern of X, Y (Millennials), and Z make a pattern that both implies that the Latin alphabet's use is coming to an end for this purpose (ignoring that Gen X was named not as part of a sequence of letters, but by Douglas Copeland's book, which was titled itself using an existing phrase), and that can easily be extrapolated backwards through time.

People get very confused about this. Pre-training "ChatGPT" (or any transformer model) with "internet shitposting text" doesn't cause them to reply with garbage comments, bad alignment does. Google seems to have implemented no frameworks to prevent hallucinations whatsoever and the RLHF/DPO applied seems to be lacking. But this is not "problem with training on the entire web". You can pre-train a model exclusively on a 4-chan database that with the right finetuning you would see a perfectly healthy and harmless model. Actually, it's not bad to have "shitposting" or "toxic" text in the pre-training because that gives the model an ability to identify it and understand it

If so, the "problem with training on the entire web" is that we would be drinking from a poisoned well, AI-generated text has a very different statistical distribution from the one users have, which would degrade the quality of subsequent models. Proof of this can be seen with the RedPajama dataset, which improves the scores on trained models simply because it has less duplicated information and is a more dense dataset: https://www.cerebras.net/blog/slimpajama-a-627b-token-cleaned-and-deduplicated-version-of-redpajama