401–410 of 1001 posts
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I wonder how Russian and North Korean citizens would feel about a capitalist, representative democracy?
I think they'd have thing or two to say about living under the rule of wealthy elites. We'd do well to listen to them.
I don’t think Russians or North Koreans could say the same with a straight face.
"Orion’s problems signaled to some at OpenAI that the more-is-more strategy, which had driven much of its earlier success, was running out of steam." So LLMs finally hit the wall. For a long time, more data, bigger models, and more compute to drive them worked. But that's apparently not enough any more. Now someone has to have a new idea. There's plenty of money available if someone has one. The current level of LLM…
Seriously? All they do is produce a “confidence metric”
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It seems to me that given how AI is likely to continuously increase capitalism's efficiency, your argument actually supports the claim you're trying to dispute.
I think this is borne out even moreso in recent years, as environmental degradation continues, and we watch as capitalist systems are unable to do anything but continue to efficiently funnel money into the pockets of shareholders.
The word "efficient" can only plausibly be applied to overly simplified models in fantastical economic theories which don't reflect reality.
The kind of AI offered by companies like OpenAI may very well be an effective tool at grabbing more stuff though, sure. Or, rather, at convincing everyone they simply must move to this new area, that they control, effectively grabbing that newly created space.
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I think the wildest thing is actually Meta’s latest paper where they show a method for LLMs reasoning not in English, but in latent space https://arxiv.org/pdf/2412.06769 I’ve done research myself adjacent to this (mapping parts of a latent space onto a manifold), but this is a bit eerie, even to me.
kinda how we do it. language is just an io interface(but also neural obv) on top of our reasoning engine.
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Says who? And more importantly, is this the boulder? All I (and many others here) see is that people engage others to sponsor pushing some boulder, screaming promises which aren’t even that consistent with intermediate results that come out. This particular boulder may be on a wrong mountain, and likely is. It all feels like doubling down on astrology because good telescopes aren’t there yet. I’m pretty sure that whe…
The buzzkill when you fire up the latest most powerful model only for it to tell you that peanut is not typically found in peanut butter and jelly sandwiches.
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AGI is the Sisyphean task of our age. We’ll push this boulder up the mountain because we have to, even if it kills us.
Do we know LLMs are the path to AGI? If they're not, we'll just end up with some neat but eye wateringly expensive LLMs.
What we can reasonably assume from statements made by insiders: They want a 10x improvement from scaling and a 10x improvement from data and algorithmic changes The sources of public data are essentially tapped Algorithmic changes will be an unknown to us until they release, but from published research this remains a steady source of improvement Scaling seems to stall if data is limited So with all of that taken toge…
Great improvements and all, but they are still no closer (as of 4o regular) to having a system that can be responsible for work. In math problems, it forgets which variable represents what, in coding questions it invents library fns. I was watching a YouTube interview with a "trading floor insider". They said they were really being paid for holding risk. The bank has a position in a market, and it's their ass on the…
I think that's a really interesting insight that has application to using 'AI' in jobs across the board.
> And the results of the project, dubbed Arrakis, indicated that creating GPT-5 wouldn’t go as smoothly as hoped. Quite the hubris to name the project after the desert planet of Dune, where multiple royal houses met their ruin.
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Do we know LLMs are the path to AGI? If they're not, we'll just end up with some neat but eye wateringly expensive LLMs.
AGI will arrive like self driving cars. it’s not that you will wake up one day and we have it. cars gained auto-braking, parallel parking, cruise control assist. and over a long time you get to something like waymo, which still is location dependent. i think AGI will take decades but sooner will be some special cases that are effectively the same
We can be reasonably confident that the components we’re adding to cars today are progress toward full self driving. But AGI is a conceptual leap beyond an LLM.
1. Even if LLM architecture doesn't work out, it's wise to remember that it's the quality of training data which is a deciding factor. A pivot is easily doable since this is a constant and disconnected from the technology itself.
2. This is clearly a moonshot project but it still feels wasteful especially with context of previous iterations of models and their shortcomings-it feels like the tremendous amount of money available is being used simply because it's available.