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Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

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Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#121
post #84

Earlier quoted context omitted.

> I would suggest to people using LLMs: you should be cautious about giving these companies data or relying on them. If you're building an AI startup, there's a very good chance they could decide to directly compete with you if your idea has traction. You're also at their mercy for API pricing etc. LLM generated code is not copyrightable, so even if they do "steal" it - I don't think there's legal grounds to do anyth…

This is a popular misreading of the state of the law. Someone tried, as a bit of a stunt, to register a work for copyright with generative AI as the sole creator/author. That registration was rejected. This is quite different from a person using generative AI as a tool to create a work. People have copyright in photos and videos they create, even if they used a camera. Same with images and code, even if they used an…

This isn't quite true: https://www.congress.gov/crs-product/LSB10922

The clearest part from the page:

> Before the proliferation of generative AI, U.S. courts did not extend copyright protection to various nonhuman authors, holding that a monkey who took photos of himself lacked standing to sue under the Copyright Act; that human authorship was required to copyright a book purportedly inspired by celestial beings; and that a living garden could not be copyrighted. The U.S. Copyright Office has also long maintained that copyrighted works must be "created by a human being" and therefore refused to register works that are "produced by a machine or mere mechanical process that operates randomly or automatically without any creative input or intervention from a human author."

I think the long story short is if you're incorporting LLM generated content into your own work, then your own work is copyrighted but if it's purely AI created and you never put any of your own work into it, it's not (so: think the slop cannons people are pointing at social media for example -- probably not copyrighted (although I don't know why you'd want to put your name on it anyway)). Granted, I don't know how you'd ever prove that something was purely LLM generated so it's kind of a technicality for coding, but for image and music I think it applies pretty clearly.

As an aside, I think socially maintaining that copyrights are for humans only is extremely important. It might be the most important legal matter around this. I see nothing good of allowing AI labs that have strip-mined the internet to claim a copyright on the things they regurgitate, and I don't think spammers deserve copyright protection either. The human-only requirement is a very good one.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#122

Earlier quoted context omitted.

The tokens per second performance numbers coming from Cerebrus/Talas are several orders of magnitude higher than models running on GPUs, which is such a huge step change that it will enable many more uses of LLMs that are impractical otherwise. I.e. think about gamers and burning in an LLM chip on a game console like a future Play Station - it doesn't matter if its a frontier LLM if it allows them to talk to in game…

> Cerebrus/Talas They are fast, but they're still programmable accelerators, not a model burned into the gates.

Cerebras is a programmable accelerator, but Taalas does burn the model into the gates.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#123
post #122

Earlier quoted context omitted.

> Cerebrus/Talas They are fast, but they're still programmable accelerators, not a model burned into the gates.

Cerebras is a programmable accelerator, but Taalas does burn the model into the gates.

Ah, right. I misremembered. Does Taalas have a meaningful advantage here then?

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#124

The open weight, open architecture releases of the past several days has me more convinced that ultimately, the winner will be whoever burns their models to ASICs fastest. The LLMs themselves are capable of doing some aspects of chip design as evinced by the K3 press release. Furthermore, the frontier models are "good enough" for a wide swathe of tasks and will soon hit that threshold for a good amount of software en…

How does an ASIC manage to have 60x the memory bandwidth needed to achieve that speedup?

You don't need memory because the output of the previous layer flows directly into the input gates of the next. So no I/O to/from HBM or similar

You still need some memory for the context, in flight answers, ... but not for the model weights and for the output of the intermediate layers. I found taalas demo here: https://chatjimmy.ai/

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#125
post #86

Earlier quoted context omitted.

> Does anyone think we need a Mythos level model to plan a road trip, or give someone tips on making a cake recipe? This is starting to look at a lot like Intel vs Arm from the last era. The Fable & Mythos are starting to look like a giant Xeon, while the smaller lighter models are starting to look like a lot of tiny ARM chips which sip on power instead. The risk is the same as what Intel had. There is a group who ar…

Except aren’t these Chinese models having to go big too? While they might not be Mythos/Fable sized, a trillion plus parameters is hardly a local server or even desktop to mainframe style jump

I've had 2b models give a plausible Paris vacation itinerary. A tools-capable 12b and especially 30b model from 2026 is certainly capable of producing passable results. I was demonstrating the qwen 3.6 27b model I stood up last week to my wife and it gave her a passable Moroccan Chicken recipe. With tool calling (search) they're quite good.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#126

Earlier quoted context omitted.

I'm not convinced, mostly because things like crypto, which I believe went into ASICs, were based on very slowly moving and mostly understood algorithms. LLMs and model architectures seems significantly more volatile. I wouldn't want to be working out the finer details of my chip rollout only to find a new paper/approach that give multiples of performance. So I guess it depends on how much the latest-greatest model m…

I think the gamble comes down to how many tokens need to be served on your best model, versus how many can be served in the cheapest/fastest way. Imagine if Anthropic could give effectively unlimited access to Sonnet, for $20. Wouldn’t that be an appealing option for many users? I know I’d make a lot of use of it for agentic tasks, office work, summarization, etc; when right now I’d save quota for more important task…

I mean, if I imagine Anthropic giving away unlimited Sonnet 4.5 away at $20, I would still be paying the $200 for fable.

It is a bit like saying "why would you hire someone with a doctorate when you could get unlimited high school grads". How appealing that sounds depends on your needs.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#127

The open weight, open architecture releases of the past several days has me more convinced that ultimately, the winner will be whoever burns their models to ASICs fastest. The LLMs themselves are capable of doing some aspects of chip design as evinced by the K3 press release. Furthermore, the frontier models are "good enough" for a wide swathe of tasks and will soon hit that threshold for a good amount of software en…

Open weights are a red herring if you can’t run the model independently. Good luck fitting these models on your Mac mini.

In fact the superior models are irreducibly nothing but superior web services run from China.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#128

Earlier quoted context omitted.

Regarding the latter, are you able to obtain good results from an LLM? With graphics programming work, I find LLMs only help in cases where the task would take me 5 mins or so.

Absolutely.

Interesting. Do you happen to have a public example?

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#129

The open weight, open architecture releases of the past several days has me more convinced that ultimately, the winner will be whoever burns their models to ASICs fastest. The LLMs themselves are capable of doing some aspects of chip design as evinced by the K3 press release. Furthermore, the frontier models are "good enough" for a wide swathe of tasks and will soon hit that threshold for a good amount of software en…

What precisely is an ASIC supposed to do that a more programmable accelerator can't? Memory latency is memory latency: doesn't matter whether it's embedded in a cache-line wait state or some flipflop state machine. ROM isn't going to be faster than RAM either. Likewise, for compute, is the ASIC somehow going to beat a systolic array? You can't have one circuit per weight: the die area and electrical fan-out would be…

No, if you burn your model into the silicon you don't need memory as the output of a layer flows through circuitry directly into the next one. No I/O to memory of any kind. You still need a bit of memory for in flight answers, but that's it.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#130

The open weight, open architecture releases of the past several days has me more convinced that ultimately, the winner will be whoever burns their models to ASICs fastest. The LLMs themselves are capable of doing some aspects of chip design as evinced by the K3 press release. Furthermore, the frontier models are "good enough" for a wide swathe of tasks and will soon hit that threshold for a good amount of software en…

While running the model at 9000 tokens/s is the more flashy demo, I imagine running 1000 concurrent requests at 150 tokens/s each is the much more achievable goal

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