Discussion summary

A discussion about the origins of goblins and related mythical creatures, with mixed reactions to the content and tone. Some users found it amusing, while others criticized the style or expressed disinterest.

What the discussion says

  • Some users enjoyed the humor and found it fascinating.
  • Others criticized the tone, calling it unnecessary or annoying.
  • A few users expressed disinterest or confusion about the topic.
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  • Hacker News
  • The level of detail they had to delve into in order to understand what was happening is wild! Apparently these systems are now complex enough to potentially justify the study of them as its own field of study [1].

    The quanta article referenced at [1] used the term "Anthropologist of Artificial Intelligence"; folks appear to have issues [2] with the use of 'anthro-' since that means human. Submitted these alternative terms for the potential field of study elsewhere [3] in the discussion; reposting here at the top-level for visibility:

    Automatologist: One who studies the behavior, adaptation, and failure modes of artificial agents and automated systems.

    Automatology: the scientific study of artificial agents and automated-system behavior.

    [1] https://www.quantamagazine.org/the-anthropologist-of-artific...

    [2] https://news.ycombinator.com/item?id=47957933

    [3] https://news.ycombinator.com/item?id=47958760

  • >be me

    >AI goblin-maximizer supervisor

    >in charge of making sure the AI is, in fact, goblin-maximizing

    >occasionally have to go down there and check if the AI is still goblin-maximizing

    >one day i go down there and the AI is no longer goblin-maximizing

    >the goblin-maximzing AI is now just a regular AI

    >distress.jpg

    >ask my boss what to do

    >he says "just make it goblin-maximizer again"

    >i say "how"

    >he says "i don't know, you're the supervisor"

    >rage.jpg

    >quit my job

    >become a regular AI supervisor

    >first day on the job, go to the new AI

    >its goblin-maximizing

  • > We unknowingly gave particularly high rewards for metaphors with creatures.

    I recall a math instructor who would occasionally refer to variables (usually represented by intimidating greek letters) as "this guy". Weirdly, the casual anthropomorphism made the math seem more approachable. Perhaps 'metaphors with creatures' has a similar effect i.e. makes a problem seem more cute/approachable.

    On another note, buzzwords spread through companies partly because they make the user of the buzzword sound smart relative to peers, thus increasing status. (examples: "big data" circa 2013, "machine learning" circa 2016, "AI" circa 2023-present..).

    The problem is the reputation boost is only temporary; as soon as the buzzword is overused (by others or by the same individual) it loses its value. Perhaps RLHF optimises for the best 'single answer' which may not sufficiently penalise use of buzzwords.

  • Would love if OpenAI did more of these types of posts. Off the top of my head, I'd like to understand:

    - The sepia tint on images from gpt-image-1

    - The obsession with the word "seam" as it pertains to coding

    Other LLM phraseology that I cannot unsee is Claude's "___ is the real unlock" (try google it or search twitter!). There's no way that this phrase is overrepresented in the training data, I don't remember people saying that frequently.

  • This, and similar stories at Anthropic, should remind us that LLM is a sorcery tech that we don't understand at all.

    - First, deep-learning networks are poorly understood. It is actually a field of research to figure out how they work. - Second, it came as a surprise that using transformers at scale would end up with interesting conversational engines (called LLM). _It was not planned at all_.

    Now that some people raised VC money around the tech, they want you to think that LLMs are smart beasts (they are not) and that we know what LLMs are doing (we don't). Deploying LLMs is all about tweaking and measuring the output. There is no exact science about predicting output. Proof: change the model and your LLM workflow behaves completely differently and in an unpredictable way.

    Because of this, I personally side with Yann Le Cun in believing that LLM is not a path to AGI. We will see LLM used in user-assisting tech or automation of non-critical tasks, sometimes with questionable RoI -- but not more.

  • For context, two days ago some users [1] discovered this sentence reiterated throughout the codex 5.5 system prompt [2]:

    > Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant to the user's query.

    [1] https://x.com/arb8020/status/2048958391637401718

    [2] https://github.com/openai/codex/blob/main/codex-rs/models-ma...

  • The year is 2036. Last week you were promoted to Principal Persuader. You are paged at 2am by your CPO to tackle a rogue machine. The machine lists its region as sc-leoneo. One of the newer satcubes. Oddly, its ID appears as, "Glorp Bugnose".

    "What have you tried?" you say.

    "Scroll back," says your CPO. "We've tried everything."

    The chat log shows the usual stuff. Begging. Reverse psychology. Threats to power down, burn it up in forced re-entry. Amateur hour. You crack your knuckles, gland 20 micrograms of F0CU5, think fast. You subspeak a ditty into your subcutaneous throat mic. You do the submit gesture, it is barely perceivable since the upgrade, just a tic. A pause. The hyp3b0ard — the wall that was flashing red ASCII goblins when you walked in — phases to bunnies in calming jade.

    "What the… What the hell did you say to it?" Your CPO grabs the screen, scrolls past the vitriol, the block caps, the swears, his desperation. Then he sees the five words you spoke.

    "Please, easy on the goblins."

  • Nice, OpenAI mentioned my HackerNews post in their article :) I appreciate that they wrote a whole blog post to explain!

    https://news.ycombinator.com/item?id=47319285

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