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Comment by blindriver | Hacker News Reader

It's not functionality. It's access to content.

The real target is replacing search with AI, as well as locking up all content creators into exclusive deals so that other LLMs don't get access to the new data.

Just like how streaming has locked video content under different vendors, LLMs will split information across multiple vendors and we will need to get subscriptions to different companies in order to search things in the future. And it's going to cost a lot of money for us peons to get access to data in the future.

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Since web 1.0 is our best analogue, I am thinking of it like this:

Late 1990s internet infrastructure buildout means that most of the captured value was at the hardware level (HP Computers, Dell, Intel, Cisco etc.).

2020s AI infrastructure buildout appears to be the same. NVIDA is capturing a lot of value, and experiencing explosive growth.

Late 1990s/early 2000s was a time of tremendous development for web software , but no one really had a business model. These LLMs are like the web browsers of that era -- they are an interface to access other peoples IP, but no one really knows what the financial model looks like.

It wasn't until the mid 2000s/early 2010s that the business models came into sharp focus for web services.

Like web browsers, the LLMs might be a vital tool for enabling the capture of value for businesses, but it might not be the actual thing that they end up monetizing.

Right. OpenAI exhausted all public training content and now they're hiring expert human authors to write proprietary training content in targeted areas. Frontier model competitors are probably doing the same. Over time we'll probably see quality differences between those models in particular domains depending on how much funding they put into generating novel training data.

To draw an analogy it's sort of like the stock market. You'll never achieve sustained above-market returns by trading based on publicly available data because everyone else has access to all the same data. In order to get an edge over other traders you have to do proprietary research (or be faster or cheat).

> locking up all content creators into exclusive deals so that other LLMs don't get access to the new data

It seems like most (all?) foundational models were trained on stolen content. I’m not sure what content exclusivity looks like for LLMs. It’s not like Joe Rogan signing on with Spotify where they have exclusive distribution rights for a particular piece of content.

There was already a $60M/year deal between Google and Reddit

Exactly. And Reddit is doubling down on monetizing content it doesn't create itself. Not only are the mods completely free and unpaid for who curate and hone the best posts for their subreddits, now the subredditors are having their comments monetized by Reddit for free. And the upvoting ensures that high quality data is already reinforcement learning via meatbots.

How do you enforce it? Even if you try doing it through copyright laws a company like DeepSeek is not going to care.

This is exactly what it's going to be. Free information is dead, we just don't know it yet. It's dead because why would someone produce free content, and then have all their page clicks hijacked by LLMs that just return the data directly? I think ad/search ecosystem is dead in less than 5 years. If it's not dead then OpenAI fucked up.

And what do they have to compete with Google on content access?

better knowledge reach, the biggest search intent goal

> locking up all content creators into exclusive deals

This is the worrying part. The real content creators are people like you or me (not reddit or stackoverflow) and we aren't getting a piece of the exclusive deals. So if this is the end game, then it means either exploiting real people who are writing things or that people stop using it and the internet uses a lot of its utility as a place for communication and shared knowledge; probably a bit of both

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