I think the argument is that decentralization leads to deceleration because it means less centralized funding and data. Those are the two primary ingredients for accel.
The problem with the decel/accel rhetoric is that it lacks nuance.
If your worldview is “most of the progress is made by closed labs, then open labs fast-follow” (which isn’t implausible given the documented distillation of Fable), and further that open labs cannot make make meaningful progress vs the closed labs except by fast-following and that they won’t pick up the ability to make progress after the closed labs are gone, then driving closed labs out of business slows down overall progress.
I think it's pretty hard to hold that worldview: Anthropic couldn't ship a reasoning model until they copied DeepSeek R1's homework, and they've all copied DS-style super-sparse MoEs at this point too.
With slightly different cherry-picking, you could equally well claim that DeepSeek couldn't ship a reasoning model until they copied the idea from OpenAI's o1-preview, and they also copied MoEs from Google Brain/Jagellonian University https://arxiv.org/abs/1701.06538 way back in 2017, too!
But ultimately these were ideas floating around in the air, if one group hadn't done the experiment, someone else would have.
That’s a really good point. Folks really need to read the papers coming out of these Chinese labs. Every paper from the DeepSeek team has been a step change.
Open Source models decelerate growth of closed AI. For people who think (or want) AI = closed_AI then that argument has weight. Good luck getting them to update their priors.
the argument is that we should all fold and let sam altman burn trillions of dollars on naive scaling and pay monopoly prices for their closed APIs until the models are good enough to be closed off for "safety" reasons so that they can take an even larger cut by competing directly with us
Open source AI is actually a lot less "powerful" than genuine frontier models, i.e. it has a much tighter inherent capability ceiling. This is "decelerationist" from a purely AGI-pilled point of view but it's actually great if you're worried about a capabilities arms race putting AI Safety at severe risk.
Kimi K3 is plausibly a lot less dangerous than a totally jailbroken ChatGPT/Gemini/Claude Sonnet (let alone Opus or Fable!) and it's quite deeply weird how no one seems to be calling for those models to be banned or restrained by further regulation. Why the double standard against the less concerning (but more efficient!) open weight models?
If you're targeting widespread local/on prem deployment which is what many open weight models are doing, that inherently limits your scale in terms of total model weights/inference-time compute compared to running in a few centralized datacenters. A centralized model will always be able to leverage a larger scale of deployment, placing it much closer to the genuine "frontier".
It’s a different topic but it’s correct imo. Open sourcing things is the best way to accelerate development.
Put another way, if you want to slow things down, put it behind a paywall, tag ideas ans “intellectual property” (meaning you’re the only one who can use it) and get the lawyers involved (injecting our slow legal system).
None of the above is a judgement call on whether development should be accelerated.
I know it's a hard ask on this site, but I need you to start parsing content and not tone. It was a helpful bit of context, even if it was a bit vitriolic.
The content was 'you need to get your head checked'. That isn't tone, that directly implying that if you hold that position, there is something wrong with you. It's rude and unnecessary.
Because discourse around tone isn't productive. You could wipe this whole comment thread, starting with the parent of mine, and lose exactly zero information.
Oh, I understand. It's the nature of the voting system of comment feedback. Reddit behaves the same way. Arguments become competitions to see who can inject enough vitriol while still maintaining a placid genteel demeanor. The one who "wins" (convinces the peanut gallery to upvote them) is the one who can avoid looking like they got mad.
It's why people can advocate for ethnic cleansing here, and that's fine as long as they word it correctly, but if someone calls them an asshole about it, they're flagged.
Really common in rationalist circles from my experience as well because they believe that true statements aren't always normative, and that, since their arguments are true because they're rational, their statements aren't necessarily normative. Begging the question, of course, but I see that in situations like Scott Alexander's defense of "human biodiversity" theories (the whole HBD moniker is itself an example of everything I'm talking about condensed into two words).
> Oh, I understand. It's the nature of the voting system of comment feedback. Reddit behaves the same way. Arguments become competitions to see who can inject enough vitriol while still maintaining a placid genteel demeanor. The one who "wins" (convinces the peanut gallery to upvote them) is the one who can avoid looking like they got mad.
Depends on which subreddit and which flavor of groupthink. The behavior you say is upvoted is one I often see downvoted to oblivion on Reddit.
> but if someone calls them an asshole about it, they're flagged.
That's because name calling is against HN guidelines.
Just an aside since it's not clear: I think the asshole is the one using labels like "decel" (or even "MAGA" unless the person self describes). It's irrelevant if I agree with the rest of the comment.
It's OK to call people out for name calling while still agreeing with the rest.
It's problematic to require one acknowledge the quality of the rest of the comment when calling them out on their name calling.
Put in a less twisted manner: If it's OK to address his comment sans the "decel", it should also be OK to address his use of "decel" without discussing the rest of the comment.
I'm not sure I understand the case for open-source models being decelerationist, is this it?
Decel:
- Potentially reduces investor appetite for funding big labs.
- More risk of powerful AI getting in bad hands -> more regulation.
Accel:
- More competition so big labs can't rest on laurels.
- More research in open, so all labs can accrete advancements faster.
I feel like open-source = acceleration has a much more clear argument. (and how bad would deceleration be in any case?)
I think the argument is that decentralization leads to deceleration because it means less centralized funding and data. Those are the two primary ingredients for accel.
The problem with the decel/accel rhetoric is that it lacks nuance.
I think it's basically open weights => more inference competition => less profit from inference => less training competition
> less training competition
I think you meant less research and experiments in big labs because they don't get all the AI money.
Training is expensive, but they also have more than 10 000 of employees combined and they cost a lot of money.
If your worldview is “most of the progress is made by closed labs, then open labs fast-follow” (which isn’t implausible given the documented distillation of Fable), and further that open labs cannot make make meaningful progress vs the closed labs except by fast-following and that they won’t pick up the ability to make progress after the closed labs are gone, then driving closed labs out of business slows down overall progress.
I think it's pretty hard to hold that worldview: Anthropic couldn't ship a reasoning model until they copied DeepSeek R1's homework, and they've all copied DS-style super-sparse MoEs at this point too.
With slightly different cherry-picking, you could equally well claim that DeepSeek couldn't ship a reasoning model until they copied the idea from OpenAI's o1-preview, and they also copied MoEs from Google Brain/Jagellonian University https://arxiv.org/abs/1701.06538 way back in 2017, too!
But ultimately these were ideas floating around in the air, if one group hadn't done the experiment, someone else would have.
That’s a really good point. Folks really need to read the papers coming out of these Chinese labs. Every paper from the DeepSeek team has been a step change.
Open Source models decelerate growth of closed AI. For people who think (or want) AI = closed_AI then that argument has weight. Good luck getting them to update their priors.
the argument is that we should all fold and let sam altman burn trillions of dollars on naive scaling and pay monopoly prices for their closed APIs until the models are good enough to be closed off for "safety" reasons so that they can take an even larger cut by competing directly with us
Open source AI is actually a lot less "powerful" than genuine frontier models, i.e. it has a much tighter inherent capability ceiling. This is "decelerationist" from a purely AGI-pilled point of view but it's actually great if you're worried about a capabilities arms race putting AI Safety at severe risk.
Kimi K3 is plausibly a lot less dangerous than a totally jailbroken ChatGPT/Gemini/Claude Sonnet (let alone Opus or Fable!) and it's quite deeply weird how no one seems to be calling for those models to be banned or restrained by further regulation. Why the double standard against the less concerning (but more efficient!) open weight models?
Do you think they are inherently less powerful? I'd imagined that closed labs have a head start / more funding so the open labs are playing catch-up.
Is there a world where open source models end up at the frontier, or do you think there are structural/first-principles reasons why this won't happen?
If you're targeting widespread local/on prem deployment which is what many open weight models are doing, that inherently limits your scale in terms of total model weights/inference-time compute compared to running in a few centralized datacenters. A centralized model will always be able to leverage a larger scale of deployment, placing it much closer to the genuine "frontier".
Why? Absolutely correct, especially considering the position of the person they're referring to
It’s a different topic but it’s correct imo. Open sourcing things is the best way to accelerate development.
Put another way, if you want to slow things down, put it behind a paywall, tag ideas ans “intellectual property” (meaning you’re the only one who can use it) and get the lawyers involved (injecting our slow legal system).
None of the above is a judgement call on whether development should be accelerated.
Why?
[flagged]
I know it's a hard ask on this site, but I need you to start parsing content and not tone. It was a helpful bit of context, even if it was a bit vitriolic.
The content was 'you need to get your head checked'. That isn't tone, that directly implying that if you hold that position, there is something wrong with you. It's rude and unnecessary.
Why should I waste time parsing content and not tone? Why can't the commenter just avoid the tone? It even saves time since you can write less!
Because discourse around tone isn't productive. You could wipe this whole comment thread, starting with the parent of mine, and lose exactly zero information.
[flagged]
> because it gets people like you going
So you're admiting you were trolling?
no, the goal was to spark a conversation about the value of *open AI* and it looks like it worked
Some battles are simply not going to be won.
I, for example, dislike reading comments complaining the submission (or another comment) is LLM generated. Focus on the content, not the style.
I'm not going to have my way, and nor shall you.
Oh, I understand. It's the nature of the voting system of comment feedback. Reddit behaves the same way. Arguments become competitions to see who can inject enough vitriol while still maintaining a placid genteel demeanor. The one who "wins" (convinces the peanut gallery to upvote them) is the one who can avoid looking like they got mad.
It's why people can advocate for ethnic cleansing here, and that's fine as long as they word it correctly, but if someone calls them an asshole about it, they're flagged.
Really common in rationalist circles from my experience as well because they believe that true statements aren't always normative, and that, since their arguments are true because they're rational, their statements aren't necessarily normative. Begging the question, of course, but I see that in situations like Scott Alexander's defense of "human biodiversity" theories (the whole HBD moniker is itself an example of everything I'm talking about condensed into two words).
> Oh, I understand. It's the nature of the voting system of comment feedback. Reddit behaves the same way. Arguments become competitions to see who can inject enough vitriol while still maintaining a placid genteel demeanor. The one who "wins" (convinces the peanut gallery to upvote them) is the one who can avoid looking like they got mad.
Depends on which subreddit and which flavor of groupthink. The behavior you say is upvoted is one I often see downvoted to oblivion on Reddit.
> but if someone calls them an asshole about it, they're flagged.
That's because name calling is against HN guidelines.
Just an aside since it's not clear: I think the asshole is the one using labels like "decel" (or even "MAGA" unless the person self describes). It's irrelevant if I agree with the rest of the comment.
It's OK to call people out for name calling while still agreeing with the rest. It's problematic to require one acknowledge the quality of the rest of the comment when calling them out on their name calling.
Put in a less twisted manner: If it's OK to address his comment sans the "decel", it should also be OK to address his use of "decel" without discussing the rest of the comment.
It depends on if we expect posters to be informative and include nuance.