There’s a part where they quote someone saying “I am not particularly confident [in my p(doom)]” and I’m still remembering getting talked down to about how Actually all subjective uncertainty can be represented as probabilities because Bayesianism and you wouldn’t happen to be one of those stupid frequentists right?
That’s weird, The Register’s versions of the quotes are different (not just pared down).
decision theory is when there’s a box with money but if you take the box it doesn’t have money
Hochman correctly deduces that R9PRESENTATIONALism originated in the 18th century, but fails to realize that the roots of this movement actually lie with the Bavarian Illuminati, a secret society which was supposedly suppressed by edict in 1784 but has in fact maintained a shadowy existence influencing politics up to the present day.
I don’t really understand what point Zitron is making about each query requiring a “completely fresh static prompt”, nor about the relative ordering of the user and static prompts. Why would these things matter?
their story is so incoherent, i can’t even tell if there was a database to begin with
solve this sokoban or you’re fired
the announcement post is obviously LLM-generated as well
The field of artificial intelligence has come full circle.
And sure enough, just within the last day the user “Hand of Lixue” has rewritten large portions of the article to read more favorably to the rationalists.
Yeah for some reason they never covered that in the stats lectures
I thought part of the schtick is that according to the rationalist theory of mind, a simulated version of you suffering is exactly the same as the real you suffering. This relies on their various other philosophical claims about the nature of consciousness, but if you believe this then empathy doesn’t have to be a concern.
If the growth is superexponential, we make it so that each successive doubling takes 10% less time.
(From AI 2027, as quoted by titotal.)
This is an incredibly silly sentence and is certainly enough to determine the output of the entire model on its own. It necessarily implies that the predicted value becomes infinite in a finite amount of time, disregarding almost all other features of how it is calculated.
To elaborate, suppose we take as our “base model” any function f which has the property that lim_{t → ∞} f(t) = ∞. Now I define the concept of “super-f” function by saying that each subsequent block of “virtual time” as seen by f, takes 10% less “real time” than the last. This will give us a function like g(t) = f(-log(1 - t)), obtained by inverting the exponential rate of convergence of a geometric series. Then g has a vertical asymptote to infinity regardless of what the function f is, simply because we have compressed an infinite amount of “virtual time” into a finite amount of “real time”.
You’re totally misunderstanding the context of that statement. The problem of classifying an image as a certain animal is related to the problem of generating a synthetic picture of a certain animal. But classifying an image of as a certain animal is totally unrelated to generating a natural-language description of “information about how to distinguish different species”. In any case, we know empirically that these LLM-generated descriptions are highly unreliable.
From the appendix:
TOTAL, COMPLETE, AND ABSOLUTE QUANTUM TOTAL ULTIMATE BEYOND INFINITY QUANTUM SUPREME LEGAL AND FINANCIAL NUCLEAR ACCOUNTABILITY
This week the WikiMedia Foundation tried to gather support for adding LLM summaries to the top of every Wikipedia article. The proposal was overwhelmingly rejected by the community, but the WMF hasn’t gotten the message, saying that the project has been “paused”. It sounds like they plan to push it through regardless.
The actual pathfinding algorithm (which is surely just A* search or similar) works just fine; the problem is the LLM which uses it.
mary chung’s mentioned! i miss mary chung’s