On the slow death of scaling
1–10 of 34 posts
Re: On the slow death of scaling
#2> Academia has been marginalized from meaningfully participating in AI progress and industry labs have stopped publishing
Exactly like semiconductor wafer processing.
Re: On the slow death of scaling
#3> Academia has been marginalized from meaningfully participating in AI progress and industry labs have stopped publishing Exactly like semiconductor wafer processing.
If anyone believes they're close to a generalization end-game wrt to AI capabilities, it makes no sense to do anything that could impact their advantage, by enabling others to compete. Collaboration makes sense on timeframes that don't imply zero-sum games.
Board games like the Settlers of Catan are good examples of the behavior— concretely the start of the game when everyone trades vs the end of the game when if you suspect someone wins it makes little sense to trade unless, you think it will help you win first.
Re: On the slow death of scaling
#4It's a mistake to publish papers without a code repo, with the majority of new ML paper's being noise at best.
Re: On the slow death of scaling
#5> Academia has been marginalized from meaningfully participating in AI progress and industry labs have stopped publishing Exactly like semiconductor wafer processing.
If anyone believes they're close to a generalization end-game wrt to AI capabilities, it makes no sense to do anything that could impact their advantage, by enabling others to compete. Collaboration makes sense on timeframes that don't imply zero-sum games. Board games like the Settlers of Catan are good examples of the behavior— concretely the start of the game when everyone trades vs the end of the game when if you…
> Collaboration makes sense on timeframes that don't imply zero-sum games.
People are fooling themselves if they think AGI will be zero sum. Even if only one group somehow miraculously develops it, there will immediately be fast followers. And, the more likely scenario is more than one group would independently pull it off - if it's even possible.
Re: On the slow death of scaling
#6Earlier quoted context omitted.
If anyone believes they're close to a generalization end-game wrt to AI capabilities, it makes no sense to do anything that could impact their advantage, by enabling others to compete. Collaboration makes sense on timeframes that don't imply zero-sum games. Board games like the Settlers of Catan are good examples of the behavior— concretely the start of the game when everyone trades vs the end of the game when if you…
> Collaboration makes sense on timeframes that don't imply zero-sum games. People are fooling themselves if they think AGI will be zero sum. Even if only one group somehow miraculously develops it, there will immediately be fast followers. And, the more likely scenario is more than one group would independently pull it off - if it's even possible.
Maybe, but at least Open AI, XAI and any Bostrom believer thinks this is the case.
Ilya Sutskever (Sep 20, 2017)
> The goal of OpenAI is to make the future good and to avoid an AGI dictatorship. You are concerned that Demis could create an AGI dictatorship. So do we. So it is a bad idea to create a structure where you could become a dictator if you chose to, especially given that we can create some other structure that avoids this possibility.
Nick Bostrom - Decisive Strategic Advantage https://www.lesswrong.com/posts/vkjWGJrFWBnzHtxrw/superintel...
Re: On the slow death of scaling
#7[deleted]
Re: On the slow death of scaling
#8It's a mistake to publish papers without a code repo, with the majority of new ML paper's being noise at best.
This is an opinion piece, similar to her infamous hardware lottery paper. We shouldn't expect a repo on an opinion piece.
Re: On the slow death of scaling
#9Hooker’s argument lands for me because it ties the technical scaling story to institutional incentives: as progress depends more on massive training runs, it becomes capital-intensive, less reproducible and more secretive; so you get a compute divide and less publication.
I’m trying to turn that into something testable with a simple constraint: “one hobbyist GPU, one day.” If meaningful progress is still possible under tight constraints, it supports the idea that we should invest more in efficiency/architecture/data work, not just bigger runs.
My favorite line >> Somewhat humorously, the acceptance that there are emergent properties which appear out of nowhere is another way of saying our scaling laws don’t actually equip us to know what is coming.
Regarding this paragraph >> 3.3 New algorithmic techniques compensate for compute. Progress over the last few years has been as much due to algorithmic improvements as it has been due to compute. This includes extending pre-training with instruction finetuning to teach models instruction following ..., model distillation using synthetic data from larger more performant "teachers" to train highly capable, smaller "students" ..., chain-of-thought reasoning ..., increased context-length ..., retrieval augmented generation ... and preference training to align models with human feedback ...
I would consider algorithmic improvements to be the following 1. architecture like ROPE, MLA 2. efficiency using custom kernels
The errors in the paper 1. Transformers for language modeling (Vaswani et al., 2023). => this shd be 2017
Disclosure: my proposed experiments: https://ohgodmodels.xyz/
Re: On the slow death of scaling
#10Earlier quoted context omitted.
> Collaboration makes sense on timeframes that don't imply zero-sum games. People are fooling themselves if they think AGI will be zero sum. Even if only one group somehow miraculously develops it, there will immediately be fast followers. And, the more likely scenario is more than one group would independently pull it off - if it's even possible.
Maybe, but at least Open AI, XAI and any Bostrom believer thinks this is the case. Ilya Sutskever (Sep 20, 2017) > The goal of OpenAI is to make the future good and to avoid an AGI dictatorship. You are concerned that Demis could create an AGI dictatorship. So do we. So it is a bad idea to create a structure where you could become a dictator if you chose to, especially given that we can create some other structure th…
Bostrom / Ilya are agreeing with the GPs argument AFAICT: it's not that AGI can create a dictatorship-of-the-first-AGI-owner, it's that only having one serious funded lab going at it creates a knowledge gap of N years that could give said lab escape velocity*
* imagine if Google alone had LLMs. For an innocuous example, the only provider in my LLM client that regularly fails unit tests verifying they actually cache tokens and utilize them on a subsequent request is Gemini. I used to work at Google and it'd be horrible for that too-big-for-its-own-good institution regressing to the corporate mean to own LLMs all by itself