Notes on AI Hardware - Benjamin Spector | Stanford MLSys #88

Text2SQL: The Dream versus Reality - Laurel Orr | Stanford MLSys #89

Hardware-aware Algorithms for Sequence Modeling - Tri Dao | Stanford MLSys #87

AI Hardware w/ Jim Keller

LLM inference optimization: Architecture, KV cache and Flash attention

The Next 100x - Gavin Uberti | Stanford MLSys #92

AI’s Hardware Problem

Andrew Ng: Opportunities in AI - 2023

How Fine-tuning Open Source LLMs Solves GenAI Productionization - Piero Molino | Stanford MLSys #94

AI Hardware, Explained.

Monarch Mixer: Making Foundation Models More Efficient - Dan Fu | Stanford MLSys #86

Stanford Seminar - Nvidia’s H100 GPU

Think Fast, Talk Smart: Communication Techniques

Language Understanding and LLMs with Christopher Manning - 686

Towards Conversational Diagnostic AI - Khaled Saab | Stanford MLSys #95

Teaching LLMs to Use Tools at Scale - Shishir Patil | Stanford MLSys #98

Trends in Deep Learning Hardware: Bill Dally (NVIDIA)

Multimodal Reasoning: PaLM-E & Gemini - Aakanksha Chowdhery | Stanford MLSys #90

host ALL your AI locally

Democratizing Foundation Models via k-bit Quantization - Tim Dettmers | Stanford MLSys #82