I like the website and my first prompt to create a modern table worked reasonably well, but if it's just a re-skinned ChatGPT, I probably wouldn't wanna spend extra money on it.
I think this difference should be comparable to asking something like:
This website uses UsersDb, which makes me think you have built a custom database, but if you can easily switch between sqlite and postgres, that makes it seem like there's no real work happening. Could you shed some light on this?
I feel this comparison is almost entirely valid since fine tuning can be as simple as:
- Create request/response tabular data
- Click "upload" on leading LLM provider
- Click "fine tune"
- Change your code to reference llm.com/finetuned instead of llm.com/base-model
bullshitting/lying isn’t implementation detail, it’s a mindset and I understand people who actively try to avoid it. Prompts and rag don’t make it a new powerful model that is superior to say ChatGPT
I'm not even saying there is any need for a custom model. Obviously, RAG etc. can work just as well, or even just a well-crafted prompt on a foundation model. But selling it as a custom model is misleading on purpose, and deters me from using the product.
The reason why I was asking is that as a potential customer, I kinda feel cheated reading about a langcss.fast model that doesn't actually exist. I don't think there's any need for putting this misleading (well, actually not even misleading; just plain wrong) information on the website, to make potential customers think you've trained a custom model on tailwind etc.
Honesty is a very attractive selling point, at least to me, and I'd bet it is to others too.
I have updated the UI to make it more obvious what the model is.
I am happy for people to know how the sausage is made and go direct to that provider if they don't see value in the UI. I might write an architecture post one day too.