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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

#81

Post by throwa356262 »

simianwords wrote: post #22

To everyone praising Open weight models, could you answer a simple question? If Anthropic doesn't make money because of distillation attacks, how would they convince investors to invest in them, such that it makes financial sense for Anthropic to train even bigger models? Assuming it is preferable for everyone that we get better models in the future. Distillation attacks remove the financial incentive.

While I am sure some do distillation (even r/LocalLLaMA is full of randos bragging about it), I wish the companies named by Anthropics would respond to these accusations.

I think at least deepseek can easily take Anthropics to court and win a defamation case. The number of requests allegedly done from deepseek IP range is so small it is barely enough to run a few benchmarks.

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

#83

Post by gavin_gee »

stillpointlab wrote: post #73
LarsDu88 wrote: post #48

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…

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…

seems to me that we are at the asymtote for most usage. sure run the prompts that need the frontier on generic silicon but burning the fable 5 model into silicon could be perfectly viable

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

#84

Post by sowbug »

onlyrealcuzzo wrote: post #49
overgard wrote: post #14

I keep thinking about the Figma thing. If you're unaware, here's the google summary: ---- The Board Departure: Mike Krieger, Anthropic’s CPO and a co-founder of Instagram, sat on Figma’s board of directors. He resigned on April 14, just days before news of Claude Design broke. This sparked speculation over conflict of interest and the use of proprietary product strategy information. Betrayal of Partnership: The launc…

> 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 LLM.

I'm not your lawyer, but to the extent you have copyright in works you create, the fact that you used a tool doesn't diminish the copyright.

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

#85

Post by mountainriver »

LarsDu88 wrote: post #48

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…

Sol is running on Cerebras right?

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

#86

Post by gopalv »

LarsDu88 wrote: post #48

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…

> 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 are pushing them to go bigger and with a resource no limit approach, who have a lot of dollars to push you that way.

Follow them and they lead you to a pile of money, but then you risk something like Apple Silicon happening.

Something which got better because of efficiency & continuous improvement, not neutered due to it.

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

#87

Post by treis »

drob518 wrote: post #2

> More importantly, as sustainable long-term businesses, model-only providers are particularly at risk. Knowledge Atlas, Moonshot Labs, and Anthropic face defensibility challenges versus OpenAI, Alibaba, SpaceX, Meta, and Google. Hm. How is OpenAI not a “model-only” provider just like Anthropic? Seems like they are vulnerable in the same way.

ChatGPT is synonymous with non technical/work related LLMs. They're amassing a ton of user history. That history improves the product for the user because it has more context into the person. They can feed it back into model improvements and for advertising.

You can see a future where a user types in "plan a vacation for me" and ChatGPT coordinates everything from there. Those sorts of users aren't going to switch because model X is 10% cheaper or better.

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

#88

Post by rockinghigh »

port3000 wrote: post #50

It's amazing how quickly Fable went from 'Game-changing model that needs to be banned' to 'Yeah it's alright, but OpenAI is also just as good and there are a couple of good open weight alternatives that are equivalent for almost everything' The hype cycles are shortening, perhaps we really are reaching some kind of plateau this time (famous last words)

Open-weight models were lagging 4 months behind OpenAI/Anthropic at the beginning of the year. They are now just 4-6 weeks behind.

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

#89

Post by hnfong »

misiti3780 wrote: post #56
LarsDu88 wrote: post #48

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…

is anyone doing this ?

It sounds vaguely similar to what Cerebras.ai is doing

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

#90

Post by alex43578 »

stillpointlab wrote: post #73
LarsDu88 wrote: post #48

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…

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 tasks.

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