zeknife

5 ms·

1.
by zeknife 2mo ago
> GOG is the only vendor that actually lets you to own your games. If I own it, can I sell it?
2.
by zeknife 6mo ago
It's a bit of misdirection, since you actually have more options than just clicking the button.
3.
by zeknife 6mo ago
>The Turing test has a rigorous definition Does it? Where?
4.
by zeknife 6mo ago
ELIZA fooled plenty of people (both originally and in the study you just linked) but i still wouldn't say Eliza passed/passes the turing test in general. It just shows that occasionally or even frequently fooling people is not a s
5.
by zeknife 7mo ago
I get the impression LLM agents are a bit like tamagochi but for tech bros.
6.
by zeknife 7mo ago
This is nice but it looks so suspiciously AI-written how can I trust it? I could just ask ChatGPT for any of these things myself.
7.
by zeknife 8mo ago
Ruby has a similarly intuitive `3.times do ... end` syntax
8.
by zeknife 11mo ago
A human being informed of a mistake will usually be able to resolve it and learn something in the process, whereas an LLM is more likely to spiral into nonsense
9.
by zeknife 11mo ago
At least until they spend some time with it
10.
by zeknife 11mo ago
It also doesn't need to be good for anything to turn the world upside down, but it would be nice if it was
11.
by zeknife 11mo ago
I see about 40 paragraphs?
12.
by zeknife 1y ago
I assume you're not very interested in the subject if you think synthesizers aren't real instruments
13.
by zeknife 1y ago
I didn't mean that a human driver needs to leave their vehicle to drive safely, I mean that we understand the world because we live in it. No amount of machine learning can give autonomous vehicles a complete enough world model to deal
14.
by zeknife 1y ago
I wouldn't trust a human to drive a car if they had perfect vision but were otherwise deaf, had no proprioception and were unable to walk out of their car to observe and interact with the world.
15.
by zeknife 1y ago
How many images do you need? What are the use-cases that need a bunch of artificial yet photoreal images produced or altered without human supervision?
16.
by zeknife 1y ago
Thinking is subconscious when working on complex problems. Thinking is symbolic or spatial when working in relevant domains. And in my own experience, I often know what is going to come next in my internal monologues, without having to actu
17.
by zeknife 1y ago
By what definition of turing test? LLMs are by no means capable of passing for human in a direct comparison and under scrutiny, they don't even have enough perception to succeed in theory.
18.
by zeknife 2y ago
I haven't kept up with his tweets, but I got the impression he deliberately chose to not get involved in LLM hype in his own AI research?
19.
by zeknife 2y ago
Like with music generation models, the main thing that might make "open source" models better is most likely that they have no concern about excluding copyrighted material from the training data, so they actually get a good starti
20.
by zeknife 2y ago
You said it, those tests are designed to measure human intelligence, because we know that there is a correspondence between test results and other, more general tasks - in humans. We do not know that such a correspondence exists with langua
21.
by zeknife 2y ago
Ironically, I almost never see quick answers in the top results, mostly it's dragged out pages of paragraph after paragraph with ads inbetween.
22.
by zeknife 2y ago
I like to think I have a pretty sharp eye for LLM output, and nothing else in the article raised any alarms for me.
23.
by zeknife 2y ago
Does the abstract sound like ChatGPT output to anyone else? Their A and B require a delicate balance of C and D, 'compelling', 'embody a distinct intersection', 'wide array of possibilities'... You don't e
24.
by zeknife 2y ago
It is easy to construct an MLP that implements any basic logic function. But XOR requires at least one hidden layer.
25.
by zeknife 2y ago
Anything except tasks that require having direct control of a physical body. Until fully functional androids are developed, there is a lot a human-level AI can't do.
26.
by zeknife 2y ago
It can't explain it's thinking after producing the answer, like you say, it'll just generate a post-hoc rationalization. But if you ask it to think step by step before making a conclusion, LLM's will somewhat reliably
27.
by zeknife 2y ago
Talking about sentence structure in the conventional sense may not be meaningful here, since what could be described as reasoning in LLM's happens in a more abstract space. If we're looking to understand why a small change makes a
28.
by zeknife 2y ago
If you had a prompt that reliably made the model perform better at all tasks, that would be useful. But if you have to manually tweak your prompts for every problem, and then manually verify that the answer is correct, that's not so us
29.
by zeknife 2y ago
Unless you invent a new field of mathematics, how can you know that whatever you come up with is "new reasoning"?
30.
by zeknife 2y ago
It's not obvious at all that an LLM can perform new reasoning that hasn't been done before

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