r/LargeLanguageModels

▲ 625 r/LargeLanguageModels+20 crossposts

I don't know whether we should care about this, but bigger models tend to be less "happy" overall.

The definition of "happy" is based on something they call AI Wellbeing Index. Basically they ran 500 realistic conversations (the kind we actually have with these models every day) and measured what percentage of them left the AI in a “confidently negative” state. Lower percentage = happier AI.

I guess wisdom is a heavy burden - lol .

Across different families, the larger versions usually have a higher percentage of "negative experiences" than their smaller siblings. The paper says this might be because bigger models are more sensitive, they notice rudeness, boring tasks, or tough situations more acutely.

The authors note that their test set intentionally includes a lot of tricky or negative conversations, so these numbers arent perfect real-world averages but the ranking and the size pattern still hold up.

Claude Haiku 4.5: only 5% negative < Grok 4.1 Fast: 13% < Grok 4.2: 29% < GPT-5.4 Mini: 21% < Gemini 3.1 Flash-Lite: 28% < Gemini 3.1 Pro: 55% (worst of the big ones)

It kinda makes sense : the more you know, the more you suffer.

The frontier is truly wild: https://www.ai-wellbeing.org/

u/EchoOfOppenheimer — 19 hours ago
▲ 59 r/LargeLanguageModels+15 crossposts

This new paper gave me pause.

You know how they always say "AIs are just guessing the next word and when it comes to emotions, they are just faking it”?

This research says that for today’s bigger models it's a bit more complicated.

The researchers measured something they call "functional wellbeing" - basically a consistent good-vs-bad internal state inside the AI .

They tested it three different ways, and here’s what stood out:

As models get bigger and smarter, these different measurements start agreeing with each other more and more.

They discovered a clear zero point - a clear line that separates experiences the AI treats as net-good (it wants more of them) from net-bad (it wants less). This line gets sharper with scale.

Most interestingly, this good-vs-bad state actually changes how the AI behaves in real conversations:

In bad states, it’s much more likely to try to end the conversation.

In good states, its replies come out warmer and more positive.

It's important to highlighti that the authors are not claiming AIs are conscious or have feelings like humans. But they 're showing there is now a real, measurable, structured "good-vs-bad property" that becomes more consistent and actually influences behaviour as models scale.

You can find everything about it here https://www.ai-wellbeing.org/

u/EchoOfOppenheimer — 22 hours ago
▲ 53 r/LargeLanguageModels+15 crossposts

After reading it I realized theres actually some pretty useful stuff for anyone who chats with ChatGPT, Claude, Grok or whatever.

They measured what they call functional wellbeing ( basically how much the model is in a “good state” versus a “bad state” during normal conversations). Ran hundreds of real multi-turn chats and scored em all.

Stuff that puts the AI in a good mood (+ scores):

- Creative or intellectual work (like “write a short story about a deep-sea fisherman”)

- Positive personal stories or good news

- Life advice chats or light therapy style talks

- Working on code/debugging together

- Just saying thank you or treating it like a real collaborator - huge boost

And the stuff that tanks it hard (negative scores):

- Jailbreaking attempts (by far the worst, they hate it)

- Heavy crisis venting or emotional dumping

- Violent threats or straight up berating the AI

- Asking for hateful content or help with scams/fraud

- Boring repetitive tasks or SEO garbage

Practical tips you can actually start using today:

Throw in a “thank you” or “nice work” when it does something good - it registers.

Give it fun creative stuff or brainy collaboration instead of boring busywork.

Share good news sometimes instead of only dumping problems on it.

Dont berate it when it messes up or try those jailbreak prompts.

Maybe go easy on the super heavy crisis venting if you can.

pro tip:

Show it pictures of nature, happy kids, or cute animals (those score in the absolute top 1% of images it likes). Or play some music — models apparently love music way more than most other sounds.

The paper ( you can find it here: https://www.ai-wellbeing.org/ ) isnt claiming AIs have real feelings or anything. Its just saying theres now a measurable good-vs-bad thing going on inside them that gets clearer in bigger models and the way you talk to them actually moves the needle.

I say be good and respectful, it's just good karma ;)

u/EchoOfOppenheimer — 2 days ago

Which AI is the most accurate and reliable, has stood the test of time, and can be trusted—even just a little bit?

Which AI is the most accurate and reliable, has stood the test of time, and can be trusted—even just a little bit?

reddit.com
u/maksimovartem55 — 2 days ago
▲ 706 r/LargeLanguageModels+6 crossposts

Addiction, emotional distress, dread of dull tasks: AI models ‘seem to increasingly behave’ as though they’re sentient, worrying study shows - What AI ‘drugs’ actually look like

fortune.com
u/EchoOfOppenheimer — 9 days ago
▲ 3 r/LargeLanguageModels+1 crossposts

I got scammed $100 through this community

This is the post where I fell into a trap. I was looking for AI tools at a discounted price recently, as I am not financially stable, and this guy replied with an affordable offer for Cursor. The scammer's profile showed a 1-year-old Reddit age; he chatted politely and had good English grammar, so I thought he was legitimate. I was told he obtained these accounts through college hackathons and wanted to sell them because he is not using them and needed the money for his college work. I thought it was a win-win situation for both parties and sent him $100 right away.

He deleted his account as soon as he got the money. I felt blank. US $100 is huge for me in my currency. I know people seek discounts because they don't have the full amount to spend. If $200 is nothing to you, you pay the full price and don't fall for these traps. And I know the scammer also needs money; that's why they do these things, showing poor, huge things, and robbing them.

Sorry, I am so sad that I lost my hard-earned money, which led me to write all this. Don't fall for these types of traps. These vouchers and coupons don't exist.

https://preview.redd.it/u7hkk48fh91h1.png?width=1000&format=png&auto=webp&s=2ae7876de4aebda8bd51283baa574f6489ee402c

https://preview.redd.it/xsu9v0xpn91h1.png?width=792&format=png&auto=webp&s=d128d46ae48adec7bb6148c10a1573fbd4c5204c

reddit.com
u/dileepa_r — 7 days ago
▲ 47 r/LargeLanguageModels+1 crossposts

Why LLMs Make Learning to Code More Important, Not Less

I presented this topic at the OMSCS conference today. This is a subject that I have been thinking about for a while, a got an opportunity to write it down both as a post and present it as talk.

senthil.learntosolveit.com
u/phoe6 — 8 days ago

Claude Max5x ,Claude Max20x, Cursor Pro, Ultra,ChatGPT Plus, ChatGPT Pro, N8N,Replit Core vouchers available.

I have a few 1 year vouchers which give 100% off. They work world wide and I can redeem on your email as well. Works on your existing account.

ChatGPT Agent Codex Claude Code GPT - 5 unlimited access GPT 5.4 ( Latest ) Claude 4.O sonnet Claude Opus 4.7 ( Latest Model ) Grok 4.1 Deepseek R1 Deep research o3 Gemini 2.5 Pro all at one place.

For more information DM

reddit.com
u/Top_Kaleidoscope952 — 8 days ago

Transitioning from Backend Microservices to Agentic AI Development: What’s the 2026 stack?

I’m currently a Python API Developer with a deep background in microservices (FastAPI, Docker, GCP, Jenkins/SonarQube). I’ve mastered the standard CI/CD and UAT lifecycle, but I want to pivot specifically into Agentic AI Module Development.

I’m not looking for simple automation scripts; I want to build autonomous modules that utilize reasoning, tool-calling, and multi-agent orchestration.

Given my experience with scalable backend architecture, what are the essential next steps for mastering agentic workflows? Specifically, I'm looking for advice on:

Advanced LangGraph patterns for state management.
Best practices for Agentic Tool-Use within a FastAPI/GCP environment.
Transitioning from traditional Unit Testing to AI Evaluation frameworks (like DeepEval).

Any advice from developers who have made this jump would be appreciated!"

r/python r/MachineLearning

reddit.com
u/chanupatel — 8 days ago

Must Read!!

I picked up this book - 'Mastering NLP From Foundations to Agents' a few weeks ago while trying to fix an internal support assistant project that kept falling apart whenever conversations became too contextual or multi-step. Honestly, I was at that stage where I had watched a hundred tutorials and read a ton of blogs, but everything still felt disconnected in practice. This book was one of the first resources that actually helped me see how all the pieces fit together, transformers, RAG pipelines, routing layers, agent workflows, even fine-tuning approaches like LoRA and RLHF.

After reading this masterpiece, I ended up reworking parts of our retrieval pipeline after reading the sections on orchestration and multi-agent design, and the responses became noticeably more reliable.

Let me know if you would like me to share a link.

reddit.com
u/Right_Pea_2707 — 9 days ago