We gotta raise the bar, so they keep struggling to make it “better”
My attempt
0000000000000000 0000011111000000 0000111111111000 0000111111100000 0001111111111000 0001111111111100 0001111111111000 0000011111110000 0000111111000000 0001111111100000 0001111111100000 0001111111100000 0001111111100000 0000111111000000 0000011110000000 0000011110000000
Btw, I refuse to give my money to AI bros, so I don’t have the “latest and greatest”
Tested on ChatGPT o4-mini-high
It sent me this
0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 0 0 1 1 1 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0
I asked it to remove the spaces
0001111100000000 0011111111000000 0011111110000000 0111111111100000 0111111111110000 0011111111100000 0001111111000000 0011111100000000 0111111111100000 1111111111110000 1111111111110000 1111111111110000 1111111111110000 0011100111000000 0111000011100000 1111000011110000
I guess I just murdered a bunch of trees and killed a random dude with the water it used, but it looks good
I just murdered a bunch of trees and killed a random dude with the water it used, but it looks good
Tech bros: “Worth it!”
It’s a pretty big problem, but as long as governments don’t do shit then we’re pretty much fucked.
Either we take the train and contribute to the problem, or we don’t but get left behind, and end up being the harmed one.
but as long as governments don’t do shit then we’re pretty much fucked
Story of the last few decades (or centuries since I don’t know history too well)
Yup
Biggest threat to humanity
I know there’s no logic, but it’s funny to imagine it’s because it’s pronounced Mrs. Sippy
Next step how many r in Lollapalooza
Incredible
Worked well for me
What is that font bro…
Its called sweetpea and my sweatpea picked it out for me. How dare I stick with something my girl picked out for me.
But the fact that you actually care what font someone else uses is sad
Chill bro it’s a joke 💀. It’s like when someone uses comic sans as a font.
Ohh.
You’re shrodingers douchebag
Got it
It’s funny how people always quickly point out that an LLM wasn’t made for this, and then continue to shill it for use cases it wasn’t made for either (The “intelligence” part of AI, for starters)
LLM wasn’t made for this
There’s a thought experiment that challenges the concept of cognition, called The Chinese Room. What it essentially postulates is a conversation between two people, one of whom is speaking Chinese and getting responses in Chinese. And the first speaker wonders “Does my conversation partner really understand what I’m saying or am I just getting elaborate stock answers from a big library of pre-defined replies?”
The LLM is literally a Chinese Room. And one way we can know this is through these interactions. The machine isn’t analyzing the fundamental meaning of what I’m saying, it is simply mapping the words I’ve input onto a big catalog of responses and giving me a standard output. In this case, the problem the machine is running into is a legacy meme about people miscounting the number of "r"s in the word Strawberry. So “2” is the stock response it knows via the meme reference, even though a much simpler and dumber machine that was designed to handle this basic input question could have come up with the answer faster and more accurately.
When you hear people complain about how the LLM “wasn’t made for this”, what they’re really complaining about is their own shitty methodology. They build a glorified card catalog. A device that can only take inputs, feed them through a massive library of responses, and sift out the highest probability answer without actually knowing what the inputs or outputs signify cognitively.
Even if you want to argue that having a natural language search engine is useful (damn, wish we had a tool that did exactly this back in August of 1996, amirite?), the implementation of the current iteration of these tools is dogshit because the developers did a dogshit job of sanitizing and rationalizing their library of data. Also, incidentally, why Deepseek was running laps around OpenAI and Gemini as of last year.
Imagine asking a librarian “What was happening in Los Angeles in the Summer of 1989?” and that person fetching you back a stack of history textbooks, a stack of Sci-Fi screenplays, a stack of regional newspapers, and a stack of Iron-Man comic books all given equal weight? Imagine hearing the plot of the Terminator and Escape from LA intercut with local elections and the Loma Prieta earthquake.
That’s modern LLMs in a nutshell.
You’ve missed something about the Chinese Room. The solution to the Chinese Room riddle is that it is not the person in the room but rather the room itself that is communicating with you. The fact that there’s a person there is irrelevant, and they could be replaced with a speaker or computer terminal.
Put differently, it’s not an indictment of LLMs that they are merely Chinese Rooms, but rather one should be impressed that the Chinese Room is so capable despite being a completely deterministic machine.
If one day we discover that the human brain works on much simpler principles than we once thought, would that make humans any less valuable? It should be deeply troubling to us that LLMs can do so much while the mathematics behind them are so simple. Arguments that because LLMs are just scaled-up autocomplete they surely can’t be very good at anything are not comforting to me at all.
one should be impressed that the Chinese Room is so capable despite being a completely deterministic machine.
I’d be more impressed if the room could tell me how many "r"s are in Strawberry inside five minutes.
If one day we discover that the human brain works on much simpler principles
Human biology, famous for being simple and straightforward.
Because LLMs operate at the token level, I think it would be a more fair comparison with humans to ask why humans can’t produce the IPA spelling words they can say, /nɔr kæn ðeɪ ˈizəli rid θɪŋz ˈrɪtən ˈpjʊrli ɪn aɪ pi ˈeɪ/ despite the fact that it should be simple to – they understand the sounds after all. I’d be impressed if somebody could do this too! But that most people can’t shouldn’t really move you to think humans must be fundamentally stupid because of this one curious artifact. Maybe they are fundamentall stupid for other reasons, but this one thing is quite unrelated.
why humans can’t produce the IPA spelling words they can say, /nɔr kæn ðeɪ ˈizəli rid θɪŋz ˈrɪtən ˈpjʊrli ɪn aɪ pi ˈeɪ/ despite the fact that it should be simple to – they understand the sounds after all
That’s just access to the right keyboard interface. Humans can and do produce those spellings with additional effort or advanced tool sets.
humans must be fundamentally stupid because of this one curious artifact.
Humans turns oatmeal into essays via a curios lump of muscle is an impressive enough trick on its face.
LLMs have 95% of the work of human intelligence handled for them and still stumble on the last bits.
I mean, among people who are proficient with IPA, they still struggle to read whole sentences written entirely in IPA. Similarly, people who speak and read chinese struggle to read entire sentences written in pinyin. I’m not saying people can’t do it, just that it’s much less natural for us (even though it doesn’t really seem like it ought to be.)
I agree that LLMs are not as bright as they look, but my point here is that this particular thing – their strange inconsistency understanding what letters correspond to the tokens they produce – specifically shouldn’t be taken as evidence for or against LLMs being capable in any other context.
Similarly, people who speak and read chinese struggle to read entire sentences written in pinyin.
Because pinyin was implemented by the Russians to teach Chinese to people who use Cyrillic characters. Would make as much sense to call out people who can’t use Katakana.
There are different types of Artificial intelligences. Counter-Strike 1.6 bots, by definition, were AI. They even used deep learning to figure out new maps.