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

(55:59)

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

(1:16:48)

FlashAttention - Tri Dao | Stanford MLSys #67

(58:58)

AI Systems in Government: Challenges \u0026 Opportunities - Jared Dunnmon | Stanford MLSys#100

(52:27)

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

(59:21)

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

(57:5)

Stanford CS229 I Machine Learning I Building Large Language Models (LLMs)

(1:44:31)

what i eat as a college student | stanford university

(14:58)

Stanford CS229: Machine Learning - Linear Regression and Gradient Descent | Lecture 2 (Autumn 2018)

(1:18:17)

The Venture Mindset: Mastering Venture Capital with Ilya Strebulaev

(1:18:31)

Debugging ML in Production feat. Shreya Shankar | Stanford MLSys Seminar Episode 12

(59:18)

Open Pretrained Transformers - Susan Zhang | Stanford MLSys #77

(1:5)

Reshaping ML with Compilers feat. Jason Knight | Stanford MLSys Seminar Episode 22

(59:39)

Stanford LEAD: Meet a LEADer November, 2024

(1:1:6)

Machine Learning 1 - Linear Classifiers, SGD | Stanford CS221: AI (Autumn 2019)

(1:20:34)

The Missing Link in ML Infrastructure feat. Josh Tobin | Stanford MLSys Seminar Episode 11

(1:1:23)

Musing On LLMs - Stanford Engineering Everywhere: CS229 \u0026 Stanford: CS25

(10:)

Declarative Machine Learning with Ludwig feat. Piero Molino | Stanford MLSys Seminar Episode 13

(1:33)

Professional Norms in Generative AI - Rob Reich | Stanford MLSys #74

(1:37)

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

(1:6:34)

Deep Recommender Systems at Facebook feat. Carole-Jean Wu | Stanford MLSys Seminar Episode 24

(1:5:6)

Automating Enterprises With Foundation Models - Avanika Narayan \u0026 Michael Wornow | Stanford MLSys#99

(1:8:55)

Efficiently Modeling Long Sequences with Structured State Spaces - Albert Gu | Stanford MLSys #46

(57:19)

Causal AI for Systems feat. Pooyan Jamshidi | Stanford MLSys Seminar Episode 38

(1:5:36)

Open-Source Systems for Federated Learning | Stanford MLSys #48

(56:10)

How Netflix does MLSys feat. Savin Goyal | Stanford MLSys Seminar Episode 17

(1:1:)

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

(56:32)