2001zhaozhao 19 hours ago

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 internally that cannot be matched by open labs.

Also, it seems plausible that frontier labs will eventually accumulate architecture-level improvements in their models that make them significantly more efficient than open LLMs. In that case, if the open labs cannot reverse engineer and replicate that, then their models will forever fall behind. On the other hand, any architectural innovations in the open model space can be used freely by closed frontier labs.

There's a counter-trend that favors open models however, which is that the design of model harnesses and multi-agent systems is more and more important to AI quality today relative to the intelligence of the model itself. This MIGHT mean that having a bunch of dumb, but cheap models in the right harness can actually compete very well against raw frontier intelligence in most practical tasks. (In other words, better harnesses makes models more efficient at improving their task completion by spending extra tokens.) This would give cheaper open models an advantage in any task where they're smart enough to complete at all, since a good multi-agent harness might mean they can do these tasks reliably and typically for cheaper than frontier models even if pushing a higher number of raw tokens.

▲ danny_codes 19 hours ago | parent | next [-]

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

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oofbey 19 hours ago | parent | next [-]

Mathematical ideas are very difficult to protect. But models can also be improved with brute force improvements in size. Imagine Mythos is a 32 trillion parameter model for example. That could be very difficult to replicate even though everybody knows exactly how it works.

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echelon 19 hours ago | parent | prev [-]

> 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.

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esseph 19 hours ago | parent [-]

> 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.

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echelon 17 hours ago | parent [-]

The smartphone is the most important piece of infrastructure in the modern world, yet we have basically two vendors.

Unless something dramatically changes, that's the world we're in for.

Chinese foundation model providers are releasing fewer weights as they "catch up", not more. There's little incentive for anyone to dump on the market if they can't collect the proceeds.

	▲	rapind 12 hours ago \| parent \| next [-]
		> There's little incentive for anyone to dump on the market if they can't collect the proceeds. Foreign state actors are not lacking incentives when the entire US economy is propped up by overvalued and overhyped AI. Like dumping a model that runs at Opus 4.6 brains at a fraction of the price on non-nvidia hardware.
	▲	esseph 14 hours ago \| parent \| prev [-]
		> The smartphone is the most important piece of infrastructure in the modern world, yet we have basically two vendors. > Unless something dramatically changes, that's the world we're in for. If you limit LLM use to cellphones, maybe, but that seems awful silly right now. And why would you when there's so many B2B or B2C tools and products for it to go in. No reason to consider the market to be that constrained IMO.

▲ hnav 19 hours ago | parent | prev | next [-]

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

▲ ninjagoo 18 hours ago | parent | next [-]

> 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

▲ 2001zhaozhao 19 hours ago | parent | prev [-]

> 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.

	▲	hnav 18 hours ago \| parent [-]
		That just means that Anthropic is fucked unless they get more capacity.

▲ CamperBob2 17 hours ago | parent | prev [-]

A bag of weights is not a product, but a component of a product. The models won't be that important at the end of the day. They are already good enough, or almost so.

The agentic tooling and harnesses will be what's important... and nobody has a moat with those, either. At least not until the easy money runs out and the patent suits start flying back and forth.