@MizusPuddle Do you think the same about Mr Beast? I don't know much about either of them -- just see clips here and there -- but they've both made this claim that they could do it again because it was 99% skill
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Frostbite
3.7K posts
What's really funny about this, is he's giving a "class" on this and he's historically always been wrong.
"I think they'll be rejected by the viewers." OK that's a cute thought, but they're not. In fact they're so overwhelming popular that the only way to stop them is artifical limits in the algorithm itself (which seems to get more false positives then anything)
This is the same guy who said he could make a new YouTube channel successful with his knowledge, only to completely fail so hard he had to start using his money and connections to try and salvage it, and even that didn't work.
He got where he is by pure chance and has absolutely no idea how to replicate it.
iWill ➡️ ???@iWillTheGamer
I think this is the best take on AI thumbnails
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Frostbite retweetledi
if you have ADHD, it's imperative you learn that pop psychology has lead people to pathologize every single aspect of human condition and that you should not fall for it
𝓐 ⭑@ayojoestar
If you have ADHD, it’s imperative you learn about limerence and how it can negatively affect you. Here’s what nobody explains:
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people who say programming is art baffles me
kache@yacineMTB
Maybe programming is a low intelligence task and a total god awful waste of human time
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@yacineMTB Does seeing his argument written out more sensibly change your view? Genuine, not a troll x.com/i/status/20786…
Haseeb ＞|＜@hosseeb
This argument by @deanwball is being badly misunderstood. It's OK to disagree with it, but first you have to actually understand what he's saying. He's saying: releasing the weights for a frontier-level model is effectively dumping. Dumping is when you sell a product at significantly below cost in order to corner market share. It's illegal. The reason: dumping results in short-term consumer surplus, but long-term it prevents the formation of a competitive market and discourages capex outside of the dumper. Standard Oil famously did this in order to consolidate the oil market before it was broken up. So why is he claiming releasing the weights of a frontier level model is basically dumping? Isn't he just describing open source? His argument: it's not financially sustainable to train a frontier model and release the weights. In the long run, you will not be able to internalize enough of the gains given the cost of training a frontier model, because neoclouds and other inference providers will be able to outcompete you at actually serving the model. It costs an astronomical amount of money to train frontier models, and if everyone else can serve them, you don't capture enough of the surplus to pay for the training and R&D. It's not like normal open source when you build some software and then release it and sell services on top of it. The amount of capex required for frontier-level models is an order of magnitude higher than normal software, which is why doing this at frontier level is so economically irrational. Right now the Hong Kong stock market is ebullient enough that Chinese AI companies are not getting punished for the fact that they're all deeply, deeply unprofitable. Releasing model weights is great marketing, intellectually appealing, and strikes fear into the hearts of their opponents. We can assume the status quo continues for a while because of the AI supercycle. But eventually the AI market will correct, the Hong Kong market will dump, and suddenly these Chinese labs won't be able to afford to training super expensive models without internalizing more of the gains. But what if China, seeing that this strategy is successfully kneecapping the US lead (by discouraging further capex and lowering valuations), says no--don't stop. And so the Chinese government starts buying up the shares of these companies and demanding that they continue releasing frontier-level weights, profitable or not. In that case, it becomes a genuine space race. For-profit companies cannot continue to compete on either side. US labs valuations fall, and the White House realizes that to keep their advantage in the AI race, they cannot rely on the free market to maintain their lead. They nationalize the labs and fund them off government subsidies. Now you have government-controlled and distributed models on both sides. That's what Dean is calling the "dystopian hellscape." The best analogy is drug development: if China were to sell American drugs back to us really cheaply, that would result in a large short-term consumer surplus. Cheap Viagra and Ozempic is obviously great. But in the long run, this would discourage investment in developing new drugs. That's the sense that Dean is saying it's long-term "decel." Now, I happen to disagree with Dean. I think the consumer surplus of having frontier-level open weight models is huge, even at the current capabilities. I also think China is going to defect from this strategy soon (there's been reporting along these lines, that Beijing will stop allowing large models to be open-weight; I think there are other reasons for this aside from competition). I also suspect that nationalization of labs is inevitable as they take on more geopolitical and cyber capabilities. But he's not wrong--releasing frontier-level weight models is weird. The question of how long this market will remain profit-driven is a very coherent question to ask.
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1. Open source models are le bad and also decel
2. Government should make them banned
3. You should rent tokens from our price fixed oligopoly forever and be under threat of us removing access for any reason
4. My text is all lowercase because it's the vogue thing
5. No non ono
Qwen@Alibaba_Qwen
Qwen3.8 is launching and going open-weight soon!🌐 With a massive 2.4T parameters, this model is continuously evolving. We believe it’s one of the most powerful model available today, compatible to leading frontier AI models , second only to Fable 5. You don't have to wait to test it. Just now, the Qwen3.8-Max-Preview made its debut on Alibaba’s Token Plan, Qoder, and QoderWork. Be among the very first to try it out. Can't wait to hear what you build. Stay tuned! 🚀 Token Plan international：qwencloud.com/pricing/token-… China：platform.qianwenai.com/pricing/token-…
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@DC_1712 @yummy___cookies @WriteToRebel You can't be serious. The subscription plans right now are $40,000 of inference for $200 a month. Software engineers easily clear $200 in a day. How is the math hard for you?
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@yummy___cookies @WriteToRebel To be spending it monthly on AI? Yes the fuck it is.
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You people were paying $200 a MONTH? Have you no self respect?
Symoné B. Beez@SymoneBeez
What happened to the limits on Claude? I used to be able to literally use Claude all day on the $200/mo plan. Now I'm hitting limits in 3 hours.
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Haseeb ＞|＜@hosseeb
This argument by @deanwball is being badly misunderstood. It's OK to disagree with it, but first you have to actually understand what he's saying. He's saying: releasing the weights for a frontier-level model is effectively dumping. Dumping is when you sell a product at significantly below cost in order to corner market share. It's illegal. The reason: dumping results in short-term consumer surplus, but long-term it prevents the formation of a competitive market and discourages capex outside of the dumper. Standard Oil famously did this in order to consolidate the oil market before it was broken up. So why is he claiming releasing the weights of a frontier level model is basically dumping? Isn't he just describing open source? His argument: it's not financially sustainable to train a frontier model and release the weights. In the long run, you will not be able to internalize enough of the gains given the cost of training a frontier model, because neoclouds and other inference providers will be able to outcompete you at actually serving the model. It costs an astronomical amount of money to train frontier models, and if everyone else can serve them, you don't capture enough of the surplus to pay for the training and R&D. It's not like normal open source when you build some software and then release it and sell services on top of it. The amount of capex required for frontier-level models is an order of magnitude higher than normal software, which is why doing this at frontier level is so economically irrational. Right now the Hong Kong stock market is ebullient enough that Chinese AI companies are not getting punished for the fact that they're all deeply, deeply unprofitable. Releasing model weights is great marketing, intellectually appealing, and strikes fear into the hearts of their opponents. We can assume the status quo continues for a while because of the AI supercycle. But eventually the AI market will correct, the Hong Kong market will dump, and suddenly these Chinese labs won't be able to afford to training super expensive models without internalizing more of the gains. But what if China, seeing that this strategy is successfully kneecapping the US lead (by discouraging further capex and lowering valuations), says no--don't stop. And so the Chinese government starts buying up the shares of these companies and demanding that they continue releasing frontier-level weights, profitable or not. In that case, it becomes a genuine space race. For-profit companies cannot continue to compete on either side. US labs valuations fall, and the White House realizes that to keep their advantage in the AI race, they cannot rely on the free market to maintain their lead. They nationalize the labs and fund them off government subsidies. Now you have government-controlled and distributed models on both sides. That's what Dean is calling the "dystopian hellscape." The best analogy is drug development: if China were to sell American drugs back to us really cheaply, that would result in a large short-term consumer surplus. Cheap Viagra and Ozempic is obviously great. But in the long run, this would discourage investment in developing new drugs. That's the sense that Dean is saying it's long-term "decel." Now, I happen to disagree with Dean. I think the consumer surplus of having frontier-level open weight models is huge, even at the current capabilities. I also think China is going to defect from this strategy soon (there's been reporting along these lines, that Beijing will stop allowing large models to be open-weight; I think there are other reasons for this aside from competition). I also suspect that nationalization of labs is inevitable as they take on more geopolitical and cyber capabilities. But he's not wrong--releasing frontier-level weight models is weird. The question of how long this market will remain profit-driven is a very coherent question to ask.
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@cgtwts Their ass hurts so much. The Chinese are winning this war and it’s for the benefit of all humanity. Kimi K3 is the first model I truly consider vaulting offline once the community quantizes it etc.
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Frostbite retweetledi
Physical touch = Too horny
Acts of service = I’m not your mom
Receiving gifts = Feminine
Quality time = ✅ doesn’t require effort
Word of affirmation = why you need to hear that
🧟♀️🌸💕@namedafteracity
Ask a man his love language… it’s always gonna be physical touch. Like OH BROTHER 😒
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Haseeb ＞|＜@hosseeb
This argument by @deanwball is being badly misunderstood. It's OK to disagree with it, but first you have to actually understand what he's saying. He's saying: releasing the weights for a frontier-level model is effectively dumping. Dumping is when you sell a product at significantly below cost in order to corner market share. It's illegal. The reason: dumping results in short-term consumer surplus, but long-term it prevents the formation of a competitive market and discourages capex outside of the dumper. Standard Oil famously did this in order to consolidate the oil market before it was broken up. So why is he claiming releasing the weights of a frontier level model is basically dumping? Isn't he just describing open source? His argument: it's not financially sustainable to train a frontier model and release the weights. In the long run, you will not be able to internalize enough of the gains given the cost of training a frontier model, because neoclouds and other inference providers will be able to outcompete you at actually serving the model. It costs an astronomical amount of money to train frontier models, and if everyone else can serve them, you don't capture enough of the surplus to pay for the training and R&D. It's not like normal open source when you build some software and then release it and sell services on top of it. The amount of capex required for frontier-level models is an order of magnitude higher than normal software, which is why doing this at frontier level is so economically irrational. Right now the Hong Kong stock market is ebullient enough that Chinese AI companies are not getting punished for the fact that they're all deeply, deeply unprofitable. Releasing model weights is great marketing, intellectually appealing, and strikes fear into the hearts of their opponents. We can assume the status quo continues for a while because of the AI supercycle. But eventually the AI market will correct, the Hong Kong market will dump, and suddenly these Chinese labs won't be able to afford to training super expensive models without internalizing more of the gains. But what if China, seeing that this strategy is successfully kneecapping the US lead (by discouraging further capex and lowering valuations), says no--don't stop. And so the Chinese government starts buying up the shares of these companies and demanding that they continue releasing frontier-level weights, profitable or not. In that case, it becomes a genuine space race. For-profit companies cannot continue to compete on either side. US labs valuations fall, and the White House realizes that to keep their advantage in the AI race, they cannot rely on the free market to maintain their lead. They nationalize the labs and fund them off government subsidies. Now you have government-controlled and distributed models on both sides. That's what Dean is calling the "dystopian hellscape." The best analogy is drug development: if China were to sell American drugs back to us really cheaply, that would result in a large short-term consumer surplus. Cheap Viagra and Ozempic is obviously great. But in the long run, this would discourage investment in developing new drugs. That's the sense that Dean is saying it's long-term "decel." Now, I happen to disagree with Dean. I think the consumer surplus of having frontier-level open weight models is huge, even at the current capabilities. I also think China is going to defect from this strategy soon (there's been reporting along these lines, that Beijing will stop allowing large models to be open-weight; I think there are other reasons for this aside from competition). I also suspect that nationalization of labs is inevitable as they take on more geopolitical and cyber capabilities. But he's not wrong--releasing frontier-level weight models is weird. The question of how long this market will remain profit-driven is a very coherent question to ask.
English
@martin_casado saw that this morning and was trying to make a case for it
i guess he means that all resources should go to a single effort? and any amount of competition is "decelerationist"
obviously very naive and ignores the realities of what humans are like
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Frostbite retweetledi
This argument by @deanwball is being badly misunderstood. It's OK to disagree with it, but first you have to actually understand what he's saying.
He's saying: releasing the weights for a frontier-level model is effectively dumping.
Dumping is when you sell a product at significantly below cost in order to corner market share. It's illegal. The reason: dumping results in short-term consumer surplus, but long-term it prevents the formation of a competitive market and discourages capex outside of the dumper. Standard Oil famously did this in order to consolidate the oil market before it was broken up.
So why is he claiming releasing the weights of a frontier level model is basically dumping? Isn't he just describing open source?
His argument: it's not financially sustainable to train a frontier model and release the weights. In the long run, you will not be able to internalize enough of the gains given the cost of training a frontier model, because neoclouds and other inference providers will be able to outcompete you at actually serving the model. It costs an astronomical amount of money to train frontier models, and if everyone else can serve them, you don't capture enough of the surplus to pay for the training and R&D.
It's not like normal open source when you build some software and then release it and sell services on top of it. The amount of capex required for frontier-level models is an order of magnitude higher than normal software, which is why doing this at frontier level is so economically irrational.
Right now the Hong Kong stock market is ebullient enough that Chinese AI companies are not getting punished for the fact that they're all deeply, deeply unprofitable. Releasing model weights is great marketing, intellectually appealing, and strikes fear into the hearts of their opponents. We can assume the status quo continues for a while because of the AI supercycle. But eventually the AI market will correct, the Hong Kong market will dump, and suddenly these Chinese labs won't be able to afford to training super expensive models without internalizing more of the gains.
But what if China, seeing that this strategy is successfully kneecapping the US lead (by discouraging further capex and lowering valuations), says no--don't stop. And so the Chinese government starts buying up the shares of these companies and demanding that they continue releasing frontier-level weights, profitable or not.
In that case, it becomes a genuine space race. For-profit companies cannot continue to compete on either side. US labs valuations fall, and the White House realizes that to keep their advantage in the AI race, they cannot rely on the free market to maintain their lead. They nationalize the labs and fund them off government subsidies.
Now you have government-controlled and distributed models on both sides. That's what Dean is calling the "dystopian hellscape."
The best analogy is drug development: if China were to sell American drugs back to us really cheaply, that would result in a large short-term consumer surplus. Cheap Viagra and Ozempic is obviously great. But in the long run, this would discourage investment in developing new drugs. That's the sense that Dean is saying it's long-term "decel."
Now, I happen to disagree with Dean. I think the consumer surplus of having frontier-level open weight models is huge, even at the current capabilities. I also think China is going to defect from this strategy soon (there's been reporting along these lines, that Beijing will stop allowing large models to be open-weight; I think there are other reasons for this aside from competition). I also suspect that nationalization of labs is inevitable as they take on more geopolitical and cyber capabilities.
But he's not wrong--releasing frontier-level weight models is weird.
The question of how long this market will remain profit-driven is a very coherent question to ask.
martin_casado@martin_casado
"Open-weight models are inherently decelerationist" .... this is a grossly incorrect statement with no supporting arguments or logic that is counter to the long arc of learnings of the industry over the last 50 years. What a stupid thing to say.
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@deanwball "removing incentive to push boundary will lead to less boundary pushing"
"LOL OF COURSE OPENAI WOILS THINK THAT"
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I’m afraid to tell you that it is effectively impossible to do the kind of writing I used to do on this website, not because anyone at OpenAI censors me but because of the sheer volume of hostility I get for sharing my analysis as a frontier lab employee.
I enjoyed writing quick takes on this website for one basic reason: I could get rapid feedback on my own ideation process in real time. Post the early version of the take here, see the criticism; then refine, sharpen, and repeat. Unfortunately now that feature of this site is gone, because the feedback I get is now almost exclusively colored by resentment at the fact that I work at a frontier lab or other forms of hatred for my employer. The feedback signal is essentially useless now, so writing on here is not fruitful for me anymore.
Literally everything I write now is responded to with “of course you said that because .” I am truly just writing what I think and would have written anyway, but everyone reads what I say in the shrieking tone of “this is what openai thinks!!!!” (to be clear, my posts are not what openai thinks). This is an unpleasant and more importantly unproductive pattern for me.
I anticipate that the shape of this account will change significantly as a result. I do not currently know how. It will not become a LinkedIn feed. It will change in some other way. It will no longer be a real-time accounting of my own thinking as it develops, since this is precisely the thing that seems impossible to do now. That will have to shift to private channels.
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figuring out if the OP here is the owner of the miata or the cybertruck has a certain classical riddle element to it
mellipede@fixxieee
mogged this faggot at @Wawa
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You were literally paid by Russia to spread propaganda.
Tim Pool@Timcast
HOLY SHIT Trump says intel shows China paid US journalists to write negative stories about the Trump administration
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@MysticMuse16 @noahacrossusa @WizardSyndicat1 @dontclipit the 16 in your name must be your age because there is zero chance you are a real functioning human and not a dependent drain on others lol
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@noahacrossusa @WizardSyndicat1 @dontclipit why do you think this is some gotcha? ludwig is only where he is today from sitting on his ass begging for donations from teenagers. just because that retard has millions now to garner sponsors that doesnt make what i said earlier irrelevant. get his dick out your mouth
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@noahacrossusa @dontclipit and how did he get to a stage in his career where that was possible? born rich? some random billionaire sponsored a 1 viewer streamer? lmao
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I like the Zig language, even started to build Turso with it. But the attitude towards losing Bun feels so hostile, I get the vibe like they want to remain a niche language, which is a stark contrast to C which they want to replace.
Debasish (দেবাশিস্) Ghosh 🇮🇳@debasishg
Andrew's thoughts on the Bun Rust rewrite .. andrewkelley.me/post/my-though…
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