vLLM V1: Prioritizing Correctness in LLM Reinforcement Learning
vLLM's transition from V0 to V1 emphasizes a crucial shift: achieving correctness before relying on post-hoc corrections in RL for LLMs.
NVIDIA Megatron-LM: Scaling AI Model Training
An in-depth look at NVIDIA's Megatron-LM framework, enabling the training of massive deep learning models.
Clinical AI on AMD ROCm: Training MedQA Without CUDA
A breakthrough in healthcare AI, demonstrating successful fine-tuning of MedQA on AMD ROCm, bypassing CUDA.
MedQA: Fine-Tuning Clinical AI on AMD ROCm Without CUDA
MedQA successfully fine-tunes a clinical AI model using AMD ROCm, showcasing an alternative to CUDA for AI development.
![[Clinical AI]: MedQA Fine-Tuning on AMD ROCm, Bypassing CUDA](https://res.cloudinary.com/dobyanswe/image/upload/c_limit,f_auto,q_auto,w_960/v1778228706/blog/2026/medqa-fine-tuning-clinical-ai-on-amd-rocm-without-cuda-2026.jpg)
[Clinical AI]: MedQA Fine-Tuning on AMD ROCm, Bypassing CUDA
The MedQA project successfully fine-tunes a clinical AI model using AMD ROCm, showcasing an alternative to CUDA for AI development.
Unsloth and NVIDIA: Revolutionizing LLM Training Speed
Learn how Unsloth, in conjunction with NVIDIA hardware, drastically speeds up Large Language Model training, enabling faster AI innovation.
Unlocking Large Scale AI Training with MRC
Learn about Multipath Routing Cache (MRC) and its role in enabling efficient and scalable training of massive AI models.