Все публикации

ThunderKittens goes live: AMA and library walkthrough

AI Systems in Government: Challenges & Opportunities - Jared Dunnmon | Stanford MLSys#100

Automating Enterprises With Foundation Models - Avanika Narayan & Michael Wornow | Stanford MLSys#99

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

Scaling Up “Vibe Checks” for LLMs - Shreya Shankar | Stanford MLSys #97

EVO: DNA Foundation Models - Eric Nguyen | Stanford MLSys #96

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

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

Online A/B Testing of Real-Time Event Detection Systems - David Tagliamonti | Stanford MLSys #93

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

Large Language Models for Program Optimization - Osbert Bastani | Stanford MLSys #91

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

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

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

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

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

Foundation Models on Consumer Devices - Tianqi Chen | Stanford MLSys #85

Serving 100s of LLMs on 1 GPU with LoRAX - Travis Addair | Stanford MLSys #84

Training LLMs at Scale - Deepak Narayanan | Stanford MLSys #83

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

A Taxonomy of ML for Systems Problems - Martin Maas | Stanford MLSys #81

ML for ML Compilers - Mangpo Phothilimthana | Stanford MLSys #80

AI Safety, RLHF, and Self-Supervision - Jared Kaplan | Stanford MLSys #79

Common Sense as Dark Matter - Yejin Choi | Stanford MLSys #78