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The Moat or the Commons

warman.life

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Re: The Moat or the Commons

#21

Post by cmwelsh »

renewiltord wrote: post #7
ramoz wrote: post #2

> DeepSeek, Qwen, Kimi, GLM — running on the LangChain, vLLM, llama.cpp, and Ollama stack "running on the LangChain" ?? EDIT: look, I think the general discussion is important, so I don't want to denounce the article. I, for one, am excited for better control, ownership, and accessibility of models. The ride labs take us on can be quite frustrating. Maybe there's even signal that the model progression is stalling (ie…

[flagged]

Can you contribute to our community when writing this stuff? Put it in a blog post, think about it, etc. You’ve been around long enough to know this is trash shit.

Re: The Moat or the Commons

#22

Post by esseph »

echelon wrote: post #15
danny_codes wrote: post #9

Earlier quoted context omitted.

This seems like a wildly unlikely risk. Innovations in this space are just mathematical ideas, easy to write down in a paper and replicate. It’s much more likely that performance will plateau and open weights will catch up asymptotically

> It’s much more likely that performance will plateau and open weights will catch up asymptotically I really don't think so. This almost never structurally happens. I think it'll be more like Linux on the Desktop. Or Ubuntu on the smartphone. Or Firefox. We'll have open weights, but 99% of everything will go through hyperscalers.

> I really don't think so. This almost never structurally happens. > I think it'll be more like Linux on the Desktop.

I think it will be Linux on the server, or the one that runs your watch, your phone, the radio or infotainment system in your car, maybe your thermostat, a bunch of medical devices and military devices, running in space shuttles and space stations and... You get the point. It's on everything.

Re: The Moat or the Commons

#23

Post by QuesnayJr »

ramoz wrote: post #2

> DeepSeek, Qwen, Kimi, GLM — running on the LangChain, vLLM, llama.cpp, and Ollama stack "running on the LangChain" ?? EDIT: look, I think the general discussion is important, so I don't want to denounce the article. I, for one, am excited for better control, ownership, and accessibility of models. The ride labs take us on can be quite frustrating. Maybe there's even signal that the model progression is stalling (ie…

"the" is connected to "stack", not "LangChain". "LangChain" is a adjective that modifies stack.

Cutting it off at "the LangChain" is like if I took the first sentence of your edit and said "look, I think the general" ?? You think the general?

Re: The Moat or the Commons

#24

Post by ramoz »

QuesnayJr wrote: post #23
ramoz wrote: post #2

> DeepSeek, Qwen, Kimi, GLM — running on the LangChain, vLLM, llama.cpp, and Ollama stack "running on the LangChain" ?? EDIT: look, I think the general discussion is important, so I don't want to denounce the article. I, for one, am excited for better control, ownership, and accessibility of models. The ride labs take us on can be quite frustrating. Maybe there's even signal that the model progression is stalling (ie…

"the" is connected to "stack", not "LangChain". "LangChain" is a adjective that modifies stack. Cutting it off at "the LangChain" is like if I took the first sentence of your edit and said "look, I think the general" ?? You think the general?

I wasn't complaining about grammar. I didn't even notice that.

Re: The Moat or the Commons

#26

Post by ninjagoo »

> American AI was financed on a particular bet. The bet was that frontier models would be the next great monopoly business

> The collision between those two facts — that American capital paid for a moat, and that the technology no longer provides one — is the most important force in the AI industry today.

> The open-weight ecosystem did not arrive in stages. It arrived in a wave. In late 2024, a Chinese lab named DeepSeek released a model

Looking at the assertions above, anyone passingly familiar with AI over the past few years will tell you that open weights and open research were the norm until OpenAI GPT-3 came along, and even then they were forced to release GPT-OSS by the market. So what technology moat? There has never been one in AI. Training 100B+ or trillion+ parameter models in expensive runs was potentially a moat, until the chinese startups showed in short order that it could be done for $6 million a run. Even the CUDA monopoly seems to be ending.

Also, no evidence referenced to back up any of the assertions. How do they know that the bet was that the frontier models would be the next great monopoly business? Especially when there were many from the outset: GPT, Anthropic, Llama, Deepmind, etc. etc.

I'd argue that the wholesale replacement of labor was and is the driver behind the capex, not monopoly dreams.

The starting premises appear to be, well, faulty. Whither the rest of the article?

Re: The Moat or the Commons

#27

Post by [deleted] »

pkilgore wrote: post #12

I can't tell if this was written by AI or by an author that has absorbed all of its worse tendencies, but past the bullet list at the front this was terrible writing. It's like the author was trying to meet a page requirement.

[deleted]

Re: The Moat or the Commons

#28

Post by ninjagoo »

hnav wrote: post #11
2001zhaozhao wrote: post #6

I think it's good to note that there are scenarios where the trend of open models keeping up will not continue forever. AI development speed is increasingly influenced by the quality of the model you are able to use internally. The frontier labs could easily pull ahead again if they increasingly withhold their best models (e.g. Claude Mythos) from the public entirely. They will benefit from increased R&D speed intern…

Superior architectures will leak pretty quickly via engineers. Withholding your best models doesn't work unless you have no competition.

> Superior architectures will leak pretty quickly via engineers.

I agree with the outcome of your premise (i.e., openness), but for different reasons:

First, isn't it the case that these bleeding edge 'newfangled' LLMs are basically variations on the same core ideas from "Attention Is All You Need" from 2017? [1]. Different scale, but still the same basic architecture. Even the "MoE" innovation keeps the Transformer attention stack while replacing or augmenting the dense feed-forward/MLP part with routed expert blocks.

And, I would argue that Engineers aren't working on new architectures. That would be Researchers, working on

  State-space models/Mamba (CMU/Princeton ecosystem), 
  Diffusion Language Models (Inception Labs), 
  Long-convolution architectures/Hyena (Stanford etc.), 
  RWKV/Recurrent LLMs (open-source community), 
  Memory-augmented architectures (Google Research/DeepMind?), 
  World models/spatial intelligence (LeCun/Fei-Fei Li/DeepMind), 
  Symbolic/neurosymbolic alternatives, 
  Thousand brains (Numenta).
That research is still open, so the outcome that you propose (openness) is likely to come to pass. Researchers/Scientists gotta publish, otherwise it's not science (to quote LeCun [2])

[1] https://arxiv.org/abs/1706.03762

[2] https://x.com/ylecun/status/1795589846771147018

Re: The Moat or the Commons

#29

Post by hnav »

2001zhaozhao wrote: post #19
hnav wrote: post #11

Earlier quoted context omitted.

Superior architectures will leak pretty quickly via engineers. Withholding your best models doesn't work unless you have no competition.

> Withholding your best models doesn't work unless you have no competition. It could also work if you DO have competition but your compute capacity is overbooked anyway, so releasing the better model doesn't actually make you that much more money (except for raising prices for the same amount of compute, which would give limited gains). This is pretty much the situation Anthropic is in today.

That just means that Anthropic is fucked unless they get more capacity.
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