People think they can use Fine-Tune for Knowledge Injection. People are Wrong
The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities (Version 1.0)
There's Something Fundamentally Wrong With LLMs
LLMs aren't trained on the "vast majority of speech," experts warn, a major blind spot that could have sweeping consequences.
The LLM Critics Are Right. I Use LLMs Anyway.
I almost agree with all of the LLM critics, yet I still use LLMs a lot. I know this sounds like I am delusional, but I don't think I am alone with it.
The LLM Critics Are Right. I Use LLMs Anyway.
I almost agree with all of the LLM critics, yet I still use LLMs a lot. I know this sounds like I am delusional, but I don't think I am alone with it.
It’s remarkably easy to inject new medical misinformation into LLMs
Changing just 0.001% of inputs to misinformation makes the AI less accurate.
LLMs believe false statements even after explicit warnings that they're false
Fine-tuning tests show "bias... toward confidently representing the claims as true."
Dan Shipper 📧 on Twitter / X
this is true and is a big reason why you don’t need to be a highly technical researcher to use LLMs in surprising and novel ways https://t.co/TuxNzXzToU— Dan Shipper 📧 (@danshipper) July 27, 2025
distil labs — Replace LLMs with Custom Small Language Models
Train and deploy custom small language models that are faster, cheaper, and just as accurate as LLMs.
Doriandarko/MLX-GRPO
A pure MLX-based training pipeline for fine-tuning LLMs using GRPO on Apple Silicon.
Why do LLMs make stuff up? New research peers under the hood.
Claude's faulty "known entity" neurons sometimes override its "don't answer" circuitry.
ethicalabs-ai/BlossomTuneLLM-MLX
Federated Fine-Tuning of LLMs on Apple Silicon with Flower.ai and MLX-LM
Why Are LLMs Smart?
A popular way to explain how current LLMs work is to say that “all” they do is predict the next most likely word in a sentence.
Solving a Million-Step LLM Task with Zero Errors
LLMs have achieved remarkable breakthroughs in reasoning, insights, and tool use, but chaining these abilities into extended processes at the scale of those routinely executed by humans,...
The scientific case for being nice to your chatbot
New research confirms that LLMs often perform better when you encourage them. But why?
