also will bring up some good opportunities in the optimization space. Smaller and cheaper models + optimization can bring performance up, especially in certain domain specific applications of ai.
The current AI pricing was always going to go away
91–100 of 100 posts
Re: The current AI pricing was always going to go away
#92Deepseek dropped their price permanently.Now v4 pro costs 3.48% of the output token price of opus 4.7. (now that opus 4.7 has a more costly tokenizer). Is it fair to say that Anthropic/OpenAI is marching to bankruptcy as opensource models like deepseek improves?
Note that deepseek also supports 500 concurrent requests per account for any individuals for v4 pro.
Re: The current AI pricing was always going to go away
#93Earlier quoted context omitted.
I know this is highly contested, but I'll try explaining it anyway, because I keep seeing this and it's ... wrong. Your comment is wrong both theoretically and practically. First, the theory. The idea that model weights are "binary driver blobs" is technically wrong. I don't know why this is so common on a technical site, but anyway. An LLM model consists of 3 main parts: The architecture, the inference code, and som…
The inference code is not part of a LLM and there can be multiple different implementations of it. The model, code to train the model, and code to run the modal are different things.
> The inference code is not part of a LLM
While that might be true in a majority of cases, it's not necessarily universal. Recently model providers have worked with inference libraries to support their models at launch, but say in transformers you can include code for a new architecture, and if you load it with "trust_remote_code=True" it will still work. You can modify the forward pass or whatever you want to do. In that sense, code can be part of a model.
Re: The current AI pricing was always going to go away
#94Earlier quoted context omitted.
I know it comes off as pedantic to point this out but: Those are open weight models not open source models. Closed weight models are the equivalent of SaaS. Open weight models are the equivalent of binary driver blobs or Windows software. We don't really have actual open source LLMs, which would need to publicly release their training data and technique so you could train a similar model yourself, or use their work a…
I know this is highly contested, but I'll try explaining it anyway, because I keep seeing this and it's ... wrong. Your comment is wrong both theoretically and practically. First, the theory. The idea that model weights are "binary driver blobs" is technically wrong. I don't know why this is so common on a technical site, but anyway. An LLM model consists of 3 main parts: The architecture, the inference code, and som…
| Technically, once a model is initialised, that's it. That is a model. If released, that would be, even for the most pedantic absolutists, undoubtably open source.
That is true. But it is not the same model as the LLM created by combining the released weights with the released architecture. The thing that is the "binary blob" is the weights. It is pretty much exactly akin to a Linux driver that depends on linux-firmware. It is wonderful that it exists! But it is only partly open.
| Now, what licensing does, and the only thing that licensing can do is to give you rights to inspect, modify and release that model. That's it. A license will never give you (it cannot) the right to have the internal IP, knowledge, know-how or the "why's" on how the model was edited. That's on you. You have the right to modify, but you can't get the right to know how others have modified it, from a license file. Never had, never will.
| In practice, we do have fully open (open data, open training code, open source models) models. Apertus, from Switzerland and Olmo from the US. Don't get me wrong, it's absolutely great that we have these models, they are very important for the community, and they do help inform everyone about what works, what doesn't, and so on.
You seem to contradict yourself here. That said: I appreciate the correction of my perception that there aren't truly open large language models.
Re: The current AI pricing was always going to go away
#95Earlier quoted context omitted.
> I'm convinced that most of those folks and their elaborate workflows aren't really for productivity but for bragging rights about how much they use AI. This is quite the reductive, charged statement. Can I ask what subscription plan you're using? My personal experience is unlike this at all-- I work on ever-expanding codebases so I can easily burn tokens. Not to mention, structured agentic coding with adverserial r…
I'm on OpenAI's Pro (200/mo) plan.
That's a super generous plan. Indeed, it's hard to normally saturate the limits of the OpenAI's $200 plan.
Re: The current AI pricing was always going to go away
#96Earlier quoted context omitted.
I know this is highly contested, but I'll try explaining it anyway, because I keep seeing this and it's ... wrong. Your comment is wrong both theoretically and practically. First, the theory. The idea that model weights are "binary driver blobs" is technically wrong. I don't know why this is so common on a technical site, but anyway. An LLM model consists of 3 main parts: The architecture, the inference code, and som…
| Technically, once a model is initialised, that's it. That is a model. If released, that would be, even for the most pedantic absolutists, undoubtably open source. That is true. But it is not the same model as the LLM created by combining the released weights with the released architecture. The thing that is the "binary blob" is the weights. It is pretty much exactly akin to a Linux driver that depends on linux-firm…
> It is pretty much exactly akin to a Linux driver that depends on linux-firmware.
The key distinction between the two is "is that the preferred form of modifying that linux driver"? And then "does the license allow you to inspect, modify and re-release that linux driver"? If the answer to any of those questions is "no", then it's not "exactly the same".
> You seem to contradict yourself here.
I don't think so. There are open source models (released under Apache2.0, MIT, like qwens, some mistrals, deepseek, etc.), weights-available models (released under restrictive licenses i.e. llamas, some mistrals, some from cohere, etc) and there are open data models (Apertus, Olmo, etc). The license dictates if a model is open source or weights available. The difference is what you are allowed to do with th emodel.
Re: The current AI pricing was always going to go away
#97Re: The current AI pricing was always going to go away
#98Earlier quoted context omitted.
I know it comes off as pedantic to point this out but: Those are open weight models not open source models. Closed weight models are the equivalent of SaaS. Open weight models are the equivalent of binary driver blobs or Windows software. We don't really have actual open source LLMs, which would need to publicly release their training data and technique so you could train a similar model yourself, or use their work a…
I know this is highly contested, but I'll try explaining it anyway, because I keep seeing this and it's ... wrong. Your comment is wrong both theoretically and practically. First, the theory. The idea that model weights are "binary driver blobs" is technically wrong. I don't know why this is so common on a technical site, but anyway. An LLM model consists of 3 main parts: The architecture, the inference code, and som…
I don’t see how models can be licensed at all. There is no creative element in them.
As you say, you start with a random array and start mutating it until you get something that magically does interesting things.
Sure, you can hold copyright over all the software used to train the thing. And trade secrets or patents around your data selection, training methods, and infrastructure and such.
But unlike typical software compilation, the model isn’t a rote translation of something that has a creative element. Ordinary software has creative source code as input, mechanically processed into an output.
Models start with a bunch of inputs that are not the creative property of the model maker. Those non-creative inputs are not imbued with novel creativity, no matter how advanced the intermediate machinery may be.
By analogy, you may hold a copyright on the layout and creative elements of a phone book, but you have no rights over the actual data of phone numbers. Nor will any amount of ingenious layout engines or ad placement algorithms or complex printing press methods turn those numbers into something that can be licensed.
IANAL. This is truly baffling to me and it seems like everyone is going along with it because some corporate lawyer probably said “Iunno, let’s just say we are licensing this thing before release. Worst case, a court throws out the license”.