No.

It does more than that, it magnifies, feeds and perpetuates them. It’s not just simple exposition.

OP sounds like he’s making a data compression pitch, but I think you have the better idea. I think surrounding the picture with a lot of contextual data about when/why/how this picture was taken will absolutely help recall and connecting to related concepts.

Essentially, you don’t ask them to use their internal knowledge. In fact, you explicitly ask them not to. The technique is generally referred to as Retrieval Augmented Generation. You take the context/user input and you retrieve relevant information from the net/your DB/vector DB/whatever, and you give it to an LLM with how to transform this information (summarize, answer a question, etc).

So you try as much as you can to “ground” the LLM with knowledge that you trust, and to only use this information to perform the task.

So you get a system that can do a really good job at transforming the data you have into the right shape for the task(s) you need to perform, without requiring your LLM to act as a source of information, only a great data massager.

I’ve been using LLMs pretty extensively in a professional capacity and with the proper grounding work it becomes very useful and reliable.

LLMs on their own is not the world changing tech, LLMs+grounding (what is now being called a Cognitive Architecture), that’s the world changing tech. So while LLMs can be vulnerable to bullshitting, there is a lot of work around them that can qualitatively change their performance.

“It has already started to be a problem with the current LLMs that have exhausted most easily reached sources of content on the internet and are now feeding off LLM-generated content, which has resulted in a sharp drop in quality.”

Do you have any sources to back that claim? LLMs are rising in quality, not dropping, afaik.

And hopefully this will allow them to follow the 80/20 rule where the AI can do 80% of the grunt work and the human can concentrate on the 20% creative part.

For one thing: when you do it, you’re the only one that can express that experience and knowledge. When the AI does it, everyone an express that experience and knowledge. It’s kind of like the difference between artisanal and industrial. There’s a big difference of scale that has a great impact on the livelihood of the creators.

I don’t think that Sarah Silverman and the others are saying that the tech shouldn’t exist. They’re saying that the input to train them needs to be negotiated as a society. And the businesses also care about the input to train them because it affects the performance of the LLMs. If we do allow licensing, watermarking, data cleanup, synthetic data, etc. in a way that is transparent, I think it’s good for the industry and it’s good for the people.

That’s always been the case, though, imo. People had to make time for art. They had to go to galleries, see plays and listen to music. To me it’s about the fair promotion of art, and the ability for the art enjoyer to find art that they themselves enjoy rather than what some business model requires of them, and the ability for art creators to find a niche and to be able to work on their art as much as they would want to.

Here are a couple of ideas:

• Nextcloud to host your files and replace GDocs/Office
• Home Assistant to control your smart home
• Plex + Radarr/Sonarr to replace streaming sites
• RSS Feed Reader to read news and blogs (sorry can’t remember the name from my phone)
• Single user ActivityPub instances
• Host your own blog site

I’m sure there’s more

Wow, none of the things you mentioned makes me want to use it.

Thanks for the explanation though!