ME:: RAGs are great if you use current (i.e. not months old) data you own since plagiarizing your own data is ok :-) and have permission for but they still make mistakes! ; Marcus Hutchins:: Every Reason Why I Hate AI and You Should Too

Discovered: Aug 4, 2025 15:49 ME:: RAGs are great if you use current (i.e. not months old) data you own since plagiarizing your own data is ok :-) and have permission for but they still make mistakes! ; Marcus Hutchins:: Every Reason Why I Hate AI and You Should Too

QUOTE

Read the whole thing: Marcus Hutchins:: Every Reason Why I Hate AI and You Should Too

RAG basically allows the LLM to search the internet for fresh data relevant to the user’s query, enabling it to fetch the most up-to-date information. The LLM can then use its training data to summarize the information retrieved via RAG. Essentially, this combines LLMs and search engines into a single product.

So, why do I hate this? Well, it’s basically glorified plagiarism. While I’d argue LLMs in general are just Plagiarism-as-a-Service, RAG is a lot closer to actual plagiarism that typical LLM behavior. As I’ve already argued, LLMs don’t think or reason. Thus, all RAG is really doing is using the LLMs’ natural language abilities to summarize or re-word some news article, blog post, or research paper. This deprives the original author of revenue & website traffic, while not transforming their work in any meaningful way.

…

So yes, while I may come off as a massive LLM hater, I feel like I have my reasons. With that said, I am still actively researching and experimenting with LLM regularly, and I’m always open to being proven wrong. But currently, I’m simply not seeing it. I’m not seeing heaps of successful LLM products, businesses, or use cases. What I’m seeing is a lot of shovel selling, and a huge black hole for VC money.

Maybe some day I’ll write a post about the viability of LLMs for something I’m building. But it won’t be today, this year, or likely anytime soon. In fact, I’m currently still getting job offers for manual reverse engineering jobs. It’s extremely common for security companies that use machine learning to hire manual analysts. ML models need constant tweaking and updating, which means a huge market for experts who can be a part of that process.

I’d expect this is where LLMs will go should the tech take off. Not job replacement, but a shift towards professionals using their experience to fine tune LLMs, instead of doing the work directly. In fact, I’ve started getting the same offers to consult for LLM companies that I am for traditional ML ones.

Times change, but technology progresses slowly.