Lora

How to train a Million Context LLM — with Mark Huang of Gradient.ai

Latent Space

Mentioned in the context of model alchemy and for potentially transferring capabilities, though its effectiveness for complex abilities is debated.

AI Engineering for Art - with comfyanonymous

Latent Space

Low-Rank Adaptation technique for efficiently fine-tuning diffusion models by training smaller matrices.

A Comprehensive Overview of Large Language Models - Latent Space Paper Club

Latent Space

Low-Rank Adaptation, a parameter-efficient fine-tuning technique that significantly reduces computational cost.

Open Source AI is AI we can Trust — with Soumith Chintala of Meta AI

Latent Space

Low-Rank Adaptation, a method for efficiently fine-tuning large language models, born out of the necessity of open-source models.

The Truth About The AI Bubble

Y Combinator

A company representing the second wave of AI-native companies, competing with established players like Harvey, and also mentioned in relation to investor benefits from fine-tuning costs.

AI Dev 25 | Sharon Zhou & Mahdi Ghodsi: Run Deepseek Reasoning and Finetuning on AMD GPUs w/ Lamini

DeepLearningAI

How AI Coding Agents Will Change Your Job

Y Combinator

A Swedish company that went through Y Combinator, mentioned as an example of a startup successfully building tools for the legal industry, contrary to the received wisdom that lawyers don't buy software.

5 Papers That Show Where AI Research Is Heading Right Now

Y Combinator

Low-Rank Adaptation, discussed as an alternative for fine-tuning, showing impressive performance at lower sample sizes.