- That didn’t happen.
- And if it did, I’m really sorry.
- And if it was that bad, I truly apologise.
- And if it is a big deal, I understand and I’m sorry again.
- And if it’s my fault, I’ll try to do better.
- And if I meant it… I didn’t — but I’m still sorry.
And if it did, you formatted the prompt wrong.
And if you didn't, you poisoned the context.
And if you didn't, you exceeded the token limit.
And if you didn't, you're missing the right MCP server.
And if you're not, you're using too many MCP servers.
And if you're not, your temperature was wrong.
And if it wasn't, you should have used RAG.
And if you did, your embeddings weren't tuned.
And if they were, you used the wrong system prompt.
And if you didn't, you deserved it.
When nothing happened, Moore told the group the ghost would not come as they were making too much noise. He asked them to leave the room ...
when a clergyman used a candle to look under the bed, the ghost "refused" to answer, Frazer claiming "she [the ghost] loving not light".
Go to ChatGPT.com and summon a ghost. It's real. It's not a particularly smart ghost, but gets a lot of useful work done. Try it with simpler tasks, to reduce the chances of holding it wrong.
That list of "things LLM apologists say" upthread? That's applicable when you try to make the ghost do work that's closer to the limits of its current capabilities.
The capabilities of LLMs have been qualitatively the same since the first ChatGPT. This is _precisely_ a hype post claiming that a future where LLMs have superhuman capabilities is inevitable.
I can also see this live, as I'm on a free plan and currently using ChatGPT heavily, and I can watch the answers degrade as I burn through the free allowance of high-tier models and end up on the cheap models.
Now, don't get me wrong, I won't rank even the good models higher than a recent graduate, but that's in comparison to ChatGPT-3.5's responses feeling more like those of a first or second year university student.
And likewise with the economics of them, I think we're in a period where you have to multiply training costs to get incremental performance gains, so there's an investment bubble and it will burst. I don't think the current approach will get in-general-superhuman skills, because it will cost too much to get there. Specific superhuman skills AI in general already demonstrate, but the more general models are mostly only superhuman by being "fresh grad" at a very broad range of things, if any LLM is superhuman at even one skill then I've missed the news.
Go to hell and never come back.