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Nvidia is the central bank of AI

economist.com

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Re: Nvidia is the central bank of AI

#251

Post by JumpCrisscross »

kennywinker wrote: post #190
jurgenburgen wrote: post #174

Earlier quoted context omitted.

It was replaced by other mechanisms. It’s not literally zero any kind of reserves.

I’m not worried about the lack of reserve, i’m worried about the money shell game where private companies can drive inflation or deflation whichever serves their profit margins best. The 2008 global financial crisis was a result of this, so not a made up worry.

> The 2008 global financial crisis was a result of this, so not a made up worry

The GFC would not have been prevented by a reserve requirement. The problem didn't originate in the banking system, and transmission to the banking and payment systems wasn't reliant on leverage per se.

Re: Nvidia is the central bank of AI

#252

Post by ericd »

kennywinker wrote: post #203
vunderba wrote: post #199

Earlier quoted context omitted.

> People are realizing that what they need isn't more general intelligence, it's more specialization. A small but well tuned coding model... It’s not quite as simple as that. Several studies have shown the opposite: models trained on more diverse knowledge tend to cross-pollinate across domains. So a more generalized model can actually perform better than a specialized one. That’s why you’re not seeing tons of tiny m…

This is definitely the position of the big ai companies. But it doesn't match my experience. Qwen3.8 27b is clearly smarter at coding than MANY bigger models. gpt-oss-120b for example, is almost 4x the size, and performs way worse at coding tasks. It's clear to me that you can build small models that work well at specific tasks. Python vs Rust is probably too fine grained a way to build a model. Coding in general see…

Gpt-oss—120b is like 1000 years old in AI years, whereas Qwen 3.8 27b is pretty young. What you’re seeing is that parameters aren’t apples to apples, and at a given parameter level, the new models are much, much better than the ones from a year or two ago. Like, to a comical degree.

Re: Nvidia is the central bank of AI

#253

Post by kennywinker »

ac29 wrote: post #247
kennywinker wrote: post #203

Earlier quoted context omitted.

This is definitely the position of the big ai companies. But it doesn't match my experience. Qwen3.8 27b is clearly smarter at coding than MANY bigger models. gpt-oss-120b for example, is almost 4x the size, and performs way worse at coding tasks. It's clear to me that you can build small models that work well at specific tasks. Python vs Rust is probably too fine grained a way to build a model. Coding in general see…

gpt-oss-120b only has 5B active parameters, so its not surprising Qwen3.8 27B outperforms it (Qwen3.8 is also ~13 months newer, which is forever in LLMs)

Fair enough. I’ve barley touched oss-120b, so i didn’t know it was so few active params. For a direct comparison, qwen3.6-35b-a3b is still better at coding than oss-120b.

And Qwen3.8-27b is still better at coding than opus 4.1.

Yes, if you list off models 27b is better than it’s all older models. But that’s my point - newer models are better than older models at the same AND much smaller size. That’s because model size matters less than they say. Training data and model architecture matter more.

Re: Nvidia is the central bank of AI

#254

Post by anon373839 »

ac29 wrote: post #247
kennywinker wrote: post #203

Earlier quoted context omitted.

This is definitely the position of the big ai companies. But it doesn't match my experience. Qwen3.8 27b is clearly smarter at coding than MANY bigger models. gpt-oss-120b for example, is almost 4x the size, and performs way worse at coding tasks. It's clear to me that you can build small models that work well at specific tasks. Python vs Rust is probably too fine grained a way to build a model. Coding in general see…

gpt-oss-120b only has 5B active parameters, so its not surprising Qwen3.8 27B outperforms it (Qwen3.8 is also ~13 months newer, which is forever in LLMs)

No, it’s not the active parameters. Qwen 3.8 Flash has 6B active and it smokes both models.

Re: Nvidia is the central bank of AI

#255

Post by gbear605 »

fc417fc802 wrote: post #231
kennywinker wrote: post #156

Earlier quoted context omitted.

OpenAI dropped sora because it was costing them ridiculous amounts of money and earning them very little. They determined that the market can't support the cost of generating video. Without a material change in the market (more buyers, vastly cheaper generation), it's unlikely a different company could make that work. More buyers isn't likely to happen, so that leaves vastly cheaper generation - something that would…

> the market can't support the cost of generating video. I'd suggest that's only the case given the current quality of output. Media is incredibly expensive to produce. A model capable of sufficiently high quality could charge prices that are absurd by today's standards.

It’s a very small set of buyers that are in that price range. Total annual domestic box office revenue is like $10 billion, maybe $50 billion for global TV and film. And that’s revenue, not profit, and a lot of costs are going to marketing, not to filming and casting. That’s a lot of money, but it’s not the scale that OpenAI and Anthropic are at.

Video generation would only make sense at that scale if it was targeting individual consumers, but then it’d need to cost something that consumers are willing to pay - which practically is probably a few hundred per year at most among US consumers, and much less globally, so again it doesn’t solve for the size of the AI companies.

I don’t see a way that video generation becomes a big industry without making generation much much cheaper.

Re: Nvidia is the central bank of AI

#256

Post by kennywinker »

JumpCrisscross wrote: post #251
kennywinker wrote: post #190

Earlier quoted context omitted.

I’m not worried about the lack of reserve, i’m worried about the money shell game where private companies can drive inflation or deflation whichever serves their profit margins best. The 2008 global financial crisis was a result of this, so not a made up worry.

> The 2008 global financial crisis was a result of this, so not a made up worry The GFC would not have been prevented by a reserve requirement. The problem didn't originate in the banking system, and transmission to the banking and payment systems wasn't reliant on leverage per se .

> The GFC would not have been prevented by a reserve requirement.

Who said anything about that?

> The problem didn't originate in the banking system

I guess i consider mortgage lending part of the banking system, but no matter - my point is it was created by financial institutions lending in ways that created money, helped their bottom line in the short term, and were unaccountable. That’s why i’m worried about how much of the US economy is created by private companies creating money out of thin air by loaning in loops.

Re: Nvidia is the central bank of AI

#257

Post by lostlogin »

JumpCrisscross wrote: post #141
theoreticalmal wrote: post #100

Earlier quoted context omitted.

I learned about this concept in college macroeconomics. I asked this exact question and the TA said “yeah I guess repaying debt is like destroying money” as if they had never thought of that before. The idea of lending money increasing the money supply is definitionally true.

> the TA said “yeah I guess repaying debt is like destroying money” as if they had never thought of that before They shouldn't have been a TA. Modern money is destroyed in three ways: through taxation, defaults and the extinguishing of debts.

Taxation destroys money?

Re: Nvidia is the central bank of AI

#258

Post by MichaelZuo »

ericd wrote: post #252
kennywinker wrote: post #203

Earlier quoted context omitted.

This is definitely the position of the big ai companies. But it doesn't match my experience. Qwen3.8 27b is clearly smarter at coding than MANY bigger models. gpt-oss-120b for example, is almost 4x the size, and performs way worse at coding tasks. It's clear to me that you can build small models that work well at specific tasks. Python vs Rust is probably too fine grained a way to build a model. Coding in general see…

Gpt-oss—120b is like 1000 years old in AI years, whereas Qwen 3.8 27b is pretty young. What you’re seeing is that parameters aren’t apples to apples, and at a given parameter level, the new models are much, much better than the ones from a year or two ago. Like, to a comical degree.

Wasnt this known by everyone who cared to pay attention?

It practically became a joke about how a huge amount of the training data for GPT-4 was bottom of the barrel reddit vomit and obvious bot spam. Leading to many bizarre edge cases.

Re: Nvidia is the central bank of AI

#259

Post by detourdog »

pvab3 wrote: post #232
kennywinker wrote: post #137

Earlier quoted context omitted.

Compute has already lost value for me. Six months ago I thought you needed a 1T+ model to be useful coding. Now I am able to get by just fine with a 27b model. I see two factors converging to cause a collapse of this house of cards: 1. People are realizing that what they need isn't more general intelligence, it's more specialization. A small but well tuned coding model, a small but well tuned customer service model,…

I've been thinking about that and that's why Nvidia's prices are surprising to me. Investors should know that better than me so there must be something I don't know

It’s really hard to know when the large tech companies have so many shares owned by a single figure. They can use margin loans and options to create the appearance of demand.
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