FromTheFirstIn

5 ms·

1.
by FromTheFirstIn 21d ago
So where’s the return? Outside of annualized numbers I haven’t even heard people pretend that OAI or Anthropic are profitable. If this is all about ROI there’s sure been a lot of I for as yet unrealized R.
2.
by FromTheFirstIn 1mo ago
No one is scared of saying something anonymously online, and wondering if that’s what’s going on is immature and silly. People earnestly disagree with you, but they don’t owe you an argument
3.
by FromTheFirstIn 1mo ago
Man there really isn’t a criticism that won’t lead to a booster saying you’re holding it wrong
4.
by FromTheFirstIn 2mo ago
> I believe a perfect solution exists. With one big caveat: you need a very clear set of requirements. Every constraint on the table. Tighten those enough and something interesting happens, you end up with only one possible solution. Thi
5.
by FromTheFirstIn 2mo ago
If it makes you feel better, most people don’t think they’re real intelligences
6.
by FromTheFirstIn 2mo ago
The only way to mitigate the damage an LLM can do because of prompt injection is to limit what that LLM can do in the first place. That’s what they mean by limiting its usefulness. If an LLM has access to an api and I want it to abuse that
7.
by FromTheFirstIn 3mo ago
I don’t think asking if someone lives in SF is ad hominem, but go off
8.
by FromTheFirstIn 3mo ago
I think they have the same app, but they don’t use it like this. It seems like you’re confident this happens a lot- do you live in San Francisco?
9.
by FromTheFirstIn 3mo ago
You’re the poster- do you live in the bay?
10.
by FromTheFirstIn 3mo ago
This is strictly a San Francisco tech problem. This isn’t happening to most people
11.
by FromTheFirstIn 3mo ago
It’s a bit like saying copy and paste must be intelligent because its output is indistinguishable from intelligent output. Reproduction of intelligence has never been equivalent to intelligence- that’s why we look down on copying, plagiaris
12.
by FromTheFirstIn 3mo ago
Would you say those humans understand what they’re talking about?
13.
by FromTheFirstIn 3mo ago
Yes, I think we simply disagree. I think you know what LLMs are based on our other thread and if you think something important happens when you get a large enough context vector I don’t think there’s much I can say to change your mind. It s
14.
by FromTheFirstIn 3mo ago
Way better- thank you!
15.
by FromTheFirstIn 3mo ago
We’re in all the same threads lately!
16.
by FromTheFirstIn 3mo ago
I think if your definition of consciousness can fit these things then you’re more open minded than I care to be. Consciousness isn’t really guessing the next thing to say- it’s hard to say what it is, obviously, but blindly feeling forwards
17.
by FromTheFirstIn 3mo ago
The styling on the website makes me feel like my phone is a cylinder
18.
by FromTheFirstIn 3mo ago
While being slow to pass judgment or disregard an approach is a valuable trait in a senior Eng, I think 3 years is plenty of time to wait for proof of concept to pan out. It’s not panning out, it doesn’t seem on the verge of panning out, an
19.
by FromTheFirstIn 3mo ago
To acquire new knowledge and build your understanding. They don’t understand so they can’t learn
20.
by FromTheFirstIn 3mo ago
You’re right, I’m very suspicious of HN when it comes to AI apologetics, but I shoulda trusted the parent commenter more.
21.
by FromTheFirstIn 3mo ago
Yeah, it not a linear cap (x% entropy doesn’t mean x% wrong) but it does seem like a hard cap. To be honest, the more I’ve understood scaling laws the more I think that the elephant in the LLM room is the entropy of the language. It explain
22.
by FromTheFirstIn 3mo ago
This is a great read! I never realized the scale of the effort to find that BSD vulnerability- helps put things in perspective
23.
by FromTheFirstIn 3mo ago
Isn’t the limit exactly what you’re describing? There’s always uncertainty, and your asymptote can approach its limit but it does have a limit. That’s the limit to the intelligence. And this is just for cross entropy loss- even if you could
24.
by FromTheFirstIn 3mo ago
Agents are always combining the same underlying weights to their inputs, relying on the same maps of semi-semantic space and the relationships between those that it was leaning towards at training time. The fact that it’s successful in maki
25.
by FromTheFirstIn 3mo ago
The first sentence is “understand or learn any intellectual task that a human can.” Whatever you think of the benefits of LLMs, they don’t understand and they can only learn during the training period and with very minor adjustments in post
26.
by FromTheFirstIn 3mo ago
My understanding is that the true entropy floor of a language is intractable- regardless of context length there will be “unpredictable” tokens where cross entropy loss is bound to happen. Even with infinite parameters and data you’ll still
27.
by FromTheFirstIn 3mo ago
And sitting right next to the data and compute factors in every cross entropy loss equation is the entropy of the language, which is just a fixed constant. There’s such a hard cap on cross entropy loss training and I never hear it come up!
28.
by FromTheFirstIn 3mo ago
You’d have to really stretch the definition of AGI to make the current models fit
29.
by FromTheFirstIn 3mo ago
Cheating is always logical for the cheater unless they’re discovered and held to account. I’m not sure what your comment is pointing out besides that it’s possible, but worth saying: just because you can cheat and would benefit from cheatin
30.
by FromTheFirstIn 3mo ago
Buddy it’s not even going to replace 1%

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