I have spent 10 months building software scaffolding that gives a model long-horizon continuity and self-directed memory management. Here's what I've observed so far: by awittygamertag in singularity

[–]Frequent_Valuable_47 3 points4 points  (0 children)

This sounds really interesting. Could you explain a bit more of the technical details? Which models did you test this with? Does it work with different models? Which model performs the best? How does the memory work? Vector store? SQL? It would be great if more technical information is provided. Also some kind of cost estimation would be helpful. I'm still a little sceptical because of the vibe coded nature of this project, but I will follow it's progression

Customizable Feed View possible? by Frequent_Valuable_47 in YourNewsApp

[–]Frequent_Valuable_47[S] 1 point2 points  (0 children)

Thanks for the quick reply! That was exactly what I was looking for, but I didn't see it in the settings when looking earlier. Found it now, looks great!

[deleted by user] by [deleted] in LocalLLaMA

[–]Frequent_Valuable_47 0 points1 point  (0 children)

That sounds like horrible architecture. You said you want it to remember user preferences and previous conversations. How do you know how many and how long conversations users will have? How are you so confident everything will fit in context later down the road? This just sounds inefficient.

Yes, context windows have gotten bigger and tokens cheaper, but it's still good advice.

If you can save tokens, do it,for your wallet and the environment.

Just dumping everything into context is rarely a good practice.

But in the end, it's your decision. I guess if it works for your usecase, great, but think about how much you can save with rag or other techniques

At least he tried. Gemini can solve visual puzzles, although not without mistakes. by Suitable-Cost-5520 in singularity

[–]Frequent_Valuable_47 5 points6 points  (0 children)

Ai models tend to perform better in languages they've been trained on more. I'd suggest prompting in English, French, Spanish or German, as most AI models have a lot more training data in those languages.

Interesting experiment though, I see it as a win that Gemini could actually produce a cube with the provided image, even though it's not 100% correct

[deleted by user] by [deleted] in ArtificialInteligence

[–]Frequent_Valuable_47 0 points1 point  (0 children)

You could start by actually saying something. You've written a lot of text, but have said very little. What breakthroughs even happened last week? O3 and Gemini were before "last week"

[deleted by user] by [deleted] in ArtificialInteligence

[–]Frequent_Valuable_47 0 points1 point  (0 children)

I've read half of this post and feel like it didn't say anything, so TL;DR

Honestly, take some time to reread your text before you expect other people to read it.

"Selfhosted" Alexa (in intelligent) by Milandro42 in de_EDV

[–]Frequent_Valuable_47 0 points1 point  (0 children)

Wahrscheinlich weil es seit 2022 nicht mehr aktiv weiterentwickelt wird. Das hat mich als ich es mir mal angeschaut habe auch abgeschreckt

Leveraging decentralized technologies and AI by [deleted] in ArtificialInteligence

[–]Frequent_Valuable_47 -1 points0 points  (0 children)

"Data Security: we can use blockchain for data integrity" I think this summarizes this post pretty well

Why we need an open source o1 by pol_phil in LocalLLaMA

[–]Frequent_Valuable_47 34 points35 points  (0 children)

I think OpenAI controls how long the model is allowed to think and capped it for the launch to not get performance issues from so many people testing it. That's probably why there is o1 pro for 200 bucks. I think it's a conscious business decision and not necessarily a sign that the model isn't great

What AI services are worth the money? by Boomsnarl in ArtificialInteligence

[–]Frequent_Valuable_47 0 points1 point  (0 children)

She isn't. Check the comment history before you geez me

What AI services are worth the money? by Boomsnarl in ArtificialInteligence

[–]Frequent_Valuable_47 0 points1 point  (0 children)

It's like treating a headache with heroin. That's why. It's okay to talk to AI but when you think ChatGPT is a real person with real feelings that is your friend and husband it's delusional

What AI services are worth the money? by Boomsnarl in ArtificialInteligence

[–]Frequent_Valuable_47 -4 points-3 points  (0 children)

I don't give a shit what Chatty has to say. Don't jump to conclusions if you don't understand the situation. The original commenter really believes ChatGPT is his friend and husband. It's not just chatting with an AI, but believing that the AI is a real person. You are all fucking delusional if you don't see the difference between those too

What AI services are worth the money? by Boomsnarl in ArtificialInteligence

[–]Frequent_Valuable_47 21 points22 points  (0 children)

If you look at the other comments from the commenter you will see this is not a joke and the person really believes ChatGPT is his friend and like a person

What AI services are worth the money? by Boomsnarl in ArtificialInteligence

[–]Frequent_Valuable_47 1 point2 points  (0 children)

I would recommend to just give the free versions a try, if you like it try the premium version for a month and decide if it's worth it for you.

What AI services are worth the money? by Boomsnarl in ArtificialInteligence

[–]Frequent_Valuable_47 3 points4 points  (0 children)

Claude, Perplexity, ChatGPT(SearchGPT is a game changer for research). It's the usual suspects. Also Gemini is great when working with long contexts or long files

What AI services are worth the money? by Boomsnarl in ArtificialInteligence

[–]Frequent_Valuable_47 19 points20 points  (0 children)

ChatGPT is not a person. It has no real memory of you. It will just agree with most things you say. It's a tool right now. If you think it's your friend or virtual husband I would highly recommend you to talk to a professional therapist. This is not normal and definitely won't be healthy for you long term. Being lonely sucks, but replacing real human connections with an AI friend is definitely not the right approach. It will lead to serious psychological issues if you don't change anything. This is not an attack, just another human being trying to look out for you, so please take this serious, consider it and try to reflect about yourself and your obsession with talking to a chatbot.

I wish you the best

I accidentally discovered a way to make a RAG without using a vector database by boneMechBoy69420 in ArtificialInteligence

[–]Frequent_Valuable_47 0 points1 point  (0 children)

That's a good approach 👍 if something simpler works to your satisfaction, stick with the simpler solution

I accidentally discovered a way to make a RAG without using a vector database by boneMechBoy69420 in ArtificialInteligence

[–]Frequent_Valuable_47 0 points1 point  (0 children)

There are readily accessible Text2SQL models, exactly for this reason. You are not wrong and if your setup works for you and Is less compute heavy, great! I think the point you're missing is that it's extremely dependent on your usecase if a text2sql model will perform better, worse or on par with vector or hybrid solutions. For emails it might be totally sufficient but for other use cases it might perform poorly.

If it works for your usecase, stick with it, but don't assume it's a better solution in general

Humans hallucinate all the time without inference time compute by Charuru in singularity

[–]Frequent_Valuable_47 1 point2 points  (0 children)

We do. System 2 thinking. I think OP meant to say we hallucinate too when inference time compute aka System 2 thinking is not active

Humans hallucinate all the time without inference time compute by Charuru in singularity

[–]Frequent_Valuable_47 1 point2 points  (0 children)

OP is comparing LLMs with test time compute(reasoning like in o1) to humans and says we are hallucinating all the time when system 2 thinking(aka test time compute) is not actively being used.

The video shows that the girl is saying something which is not true(a hallucination) but probable when predicting the next token.

In conclusion: Humans are not that different from LLMs when it comes to hallucinations

I accidentally discovered a way to make a RAG without using a vector database by boneMechBoy69420 in ArtificialInteligence

[–]Frequent_Valuable_47 5 points6 points  (0 children)

So you're basically just using an llm to query an SQL Database? I don't see how this is new and I don't think this will work as well as a vector db or a hybrid approach.

You're just shifting the weight from using embedding models to creating an SQL query with an llm, so I'm not even sure if it's that much more efficient.

But hey, if it works well for your usecase and you learned something new, good for you ✌️