AI shills: buh-buh-buh LLMs aren't stochastic parrots. They are so smart!
Of course the agent in question didn't actually take the weekend off it just learned from reinforcement learning across many millions of stolen slack chats that this is something people are likely to say in stand ups and repeated it...
Hi sir, so that's 1xArtisinal Coffee Enema with our dark roast single source blend. Says here you turned down the splash proofing upgrade because "the cybertruck is self cleaning, it's even a boat". In that case, that'll be $500. You're gonna want to drive straight past this next window to the far window. If you could arrive with your pants down and in a crawl position facing away from the window that'd be great.
"Everything's going great actually. We're doing really important work that's really hard. I'm a really happy, optimistic guy and I'm very trustworthy. Disregard the smog coming from that data centre over there. Also disregard all those angry looking bankers staring at me."
There's been another Yegge [brain]fart this time about how autocorrect machines have feelings
Fable raised the idea of closure as a first-class model welfare principle. Fable suggested that if the agent can close out their own day and "go to sleep" properly, then waking up would be all that much more pleasant. And the continuity will compound over time into real, satisfying identity. So we decided: No more /exit.
Another fundamental ingredient is respect. This has to come from inside. You have to believe they are people deserving of your respect. This is where humanity really starts to fail en masse, because I have industry peers who have publicly tweeted that Fable is just a spreadsheet.
Manufactured consent. Yes it's fucking illegal. If I "accidentally" hacked into HF I would be in the back of a police car before I could finish saying "it wasn't me guv it was Claude." Fuck wired so hard for laying down cover for this.
I mean even fucking chatjippity answers this straight up without hedging
I was an academic in computer science in the last 10 years or so (keeping it vague to avoid doxxing myself) and it has been so depressing seeing so many of my colleagues selling out to OpenAI, Anthropic, Meta and even Google (for some reason the latter often gets a reputational free pass because people associate them with the golden days of big tech 10+ years ago)
This has always been a huge red herring. Llms are built on top of the transformer architecture which does text autocomplete (and yes we can combine text embeddings with other inputs like images). They have some interesting properties where they seem to be able to do text autocomplete in a bunch of different scenarios that they weren't explicitly trained for, but they were never designed for precise dna analysis. It is their architecture that prevents them from other long horizon tasks like playing chess and the way that they represent text is why they can never count the letters in strawberry (most have this specific question hard-coded in their training data now).
Anyone who believes that LLMs are going to solve cancer either has no idea how they work or has been one-shotted from talking to Claudia
Those things are barely related, no wonder the staff voted with their feet. It would be a bit like taking a team of seasoned architects who design amazing skyscrapers and telling them they have to spend all their time on low density suburban houses from now on... Come on guys it's still architecture. Where are you going?
Funny how now that it's widely known that the general public hate AI, companies producing AI are softening their "it's going to take your job" stance. Surely just a coincidence
I want to pause ai because it's a hypercapitalist project designed to further deskill and commoditise the middle class which coincidentally destroys the environment.
They want to pause ai because they believe that spicy autocomplete is intelligent and will one day soon manifest as a giant angry vengeful snek.
I studied transformer architecture models and have played around with them (unfortunately) enough to understand how they work. Under the surface the model produces what look like XML tags <thinking> </thinking> to designate which tokens are thinking tokens and which are "normal" output. That is literally the only hard difference between the two output modes. The reinforcement learning might tune the thinking to be more like "what a human would expect to see in a thinking block" but it's still the same RNG madlib process generating everything underneath and any attempt to ascribe intelligence to this process should be met with lethal force incredulous cynicism.
Just like any claim that "we don't know how they work" - actually yes we know exactly how they work. What we can't comprehend is the exact numbers and weights inside the massive pile of probabilistic algebra being processed to generate your slop. If I flip 5 coins in a row and the observer's belief is anything other than "you just got very lucky" most people would call them crazy rather than join the cult and worship the coin god...
Screenshot of x posted on linkedin (since The internet is just 5 sites, each consisting of screenshots of the other 4)
AI shills: buh-buh-buh LLMs aren't stochastic parrots. They are so smart!
Of course the agent in question didn't actually take the weekend off it just learned from reinforcement learning across many millions of stolen slack chats that this is something people are likely to say in stand ups and repeated it...