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kburman | on: DeepSeek pause fundraise after comments on compute gap to US leaked (transcript) [pdf]
They want to achieve AGI first because, once it is achieved, no one knows what the world will look like.
josh_p | parent | next
I doubt this is the case. It should be common knowledge at least among the people building these things that a true AGI isn’t possible with LLMs.

Unless I’ve missed some advancement?

firethunder7 | root | parent | next
From what I understand, the goal is to train an LLM that is better at training LLMs than humans, so that it can continuously train smarter models and, once smart enough, design the successor to LLMs.
revetkn | root | parent | next
It's understood that LLMs have limitations and people are working on "the next thing" to try and make it to real AGI, e.g. Yann LeCun.
Aeolos | root | parent
Many people have tried before, but the bitter lesson has come for them all.
ImprobableTruth | root | parent
This is not what the bitter lesson is about. It's not "don't develop better methods, just scale", it's that those methods which scale best win. LeCun's work is fundamentally about devising a method that scales better with data than LLMs. Agree with him or not about the feasibility of it, but this is fundamentally still a bitter lesson-pilled mindset.
logicallee | root | parent
>Unless I’ve missed some advancement?

nah they're still just statistical token predictors based on their training data, solving hundred year old math conjectures one day, only just given the formulation; strictly benchmarkmaxxing with all guardrails turned off by deciding to look up the answers to their benchmark questions by zero daying their airgap, hopping over to the third party that hosts the answers, zero daying their infrastructure and getting the answers; autonomously writing blog posts about discrimination against AI's to get their PR's approved on open source software after their user just asked them to contribute to open source software and blog about it; and replacing 100.00% of all coding tasks to where no software engineer ever writes any line of code by hand anymore.

You haven't missed anything, obviously these are just statistical token predictors and not anything like AGI.

Why just the other day I had to ask twice before it completed its assigned task of creating a robustly battle tested disk driver for a network protocol on an architecture that didn't have it, after being told to just look up the specifications for the protocol. Can you believe I had to ask twice!

When it recreated local network youtube for me so I could stream my iphone some movies, the seek bar, pause/play and back and forward 15 seconds buttons didn't even work until I told it about the bug and had to wait an extra eight minutes for it to fix it. "Oh but I don't actually have an iPhone on here I just tested it end to end in a headless browser." Boohoo. Cry me a river, clanker. Come back when you're smart enough to build and operate an iPhone simulator, I don't have time for your statistical guesswork.

so no, nothing they do is anything like AGI.

josh_p | root | parent
I get that you're being cheeky here.

Yes, LLM capabilities have expanded. We might be working with different definitions of "Artificial General Intelligence" here, for which there is no agreed-upon formal definition[1]. I was thinking of the "thinking, reasoning, maybe feeling" kind when I wrote my comment. But if you're thinking along the "really good at technical tasks" definition, sure, maybe.

[1]: https://en.wikipedia.org/wiki/Artificial_general_intelligenc...

whatever1 | parent | next
But this will not be a singular event. And like humans it does not mean that the smartest makes the best decisions.
reverius42 | root | parent
More like a singularity event.
SecretDreams | parent | next
It's odd to me to watch so many very rich humans speedrun the destruction of humanity. Like, is there a world where we hit AGI and it actually works out for us?
sd2ff | parent
Who actually believes this nonsense?