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Comment by bko

8 months ago

It's a little depressing how many high valued startups are basically just wrappers around LLMs that they don't own. I'd be curious to see what percentage of YC latest batch is just this.

> 70% of Y Combinator’s Winter 2024 batch are AI startups. This is compared to -57% of YC Summer 2023 companies and ~32% from the Winter batch one year ago (YC W23).

The thinking is, the models will get better which will improve our product, but in reality, like the article states, the generalized models get better so your value add diminished as there's no need to fine tune.

On the other hand the crypto fund made a killing off of "me too" block chain technology before it got hammered again. So who knows about 2-5 year term but 10 year almost certainly won't have these billion dollar companies that are wrappers around LLMs

https://x.com/natashamalpani/status/1772609994610835505?mx=2

How is being a wrapper for LLMs you don’t own any different from being a company based on cloud infrastructure you don’t own?

LLMs are a platform.

Bill Gates definition of a platform was “A platform is when the economic value of everybody that uses it exceeds the value of the company that creates it.”

  • It's relatively easy to move to different cloud infrastructure (or host your own) later on down the line.

    If you rely on an OpenAI LLM for your business, they can basically do whatever they want to you. Oh, prices went up 10x? What are you gonna do, train your own AI?

    • Anyone who says it’s relatively easy to go to a different cloud has never led a major migration (I have). That’s kind of part of my day job - cloud consulting.

      And if you think it’s hard to move to another LLM you haven’t done a major implementation using an LLM and used LangChain (I have). It abstracts a lot of the work and people can choose which LLM they want to use.

      You don’t train your LLM. You use your LLM along with RAG.

  • A LLM wrapper adds near-zero value. If I type some text into a "convert to Donald Trump style" tool, it produces the exact same output as typing it into ChatGPT following "Convert this text to Donald Trump style:" because that's what the tool actually does. Implementing ChatGPT is 99.999% of the value creation. Prepending the prompt is 0.001%. The surprising fact is that the market assigns a non-zero value to the tool anyway.

    Startups that use cloud servers still write the software that goes on those servers, which is 90% of the value creation.

    • That’s not what I see from the companies I work with (cloud consulting).

      Almost all of them are using LLMs along with “tools” and RAG.