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

Поделиться
HTML-код
  • Опубликовано: 20 окт 2024

Комментарии • 6

  • @robertwachen2082
    @robertwachen2082 Год назад +3

    I’d like to see more of this Ben guy

  • @alimottaghi
    @alimottaghi Год назад +1

    Thanks!

  • @intoeleven
    @intoeleven Год назад

    After fusion and memory optimization, I think Google ml system next step is the network optimization…

  • @420_gunna
    @420_gunna 9 месяцев назад

    martin is a based skyrim nord 👍😍

  • @420_gunna
    @420_gunna 9 месяцев назад

    Ben has W white boy rizz

Следующие
Автовоспроизведение
Democratizing Foundation Models via k-bit Quantization - Tim Dettmers | Stanford MLSys #8258:25Democratizing Foundation Models via k-bit Quantization - Tim Dettmers | Stanford MLSys #82
Democratizing Foundation Models via k-bit Quantization - Tim Dettmers | Stanford MLSys #82Stanford MLSys Seminars
Просмотров 4 тыс.
Monarch Mixer: Making Foundation Models More Efficient - Dan Fu | Stanford MLSys #8656:32Monarch Mixer: Making Foundation Models More Efficient - Dan Fu | Stanford MLSys #86
Monarch Mixer: Making Foundation Models More Efficient - Dan Fu | Stanford MLSys #86Stanford MLSys Seminars
Просмотров 4 тыс.
Text2SQL: The Dream versus Reality - Laurel Orr | Stanford MLSys #8957:05Text2SQL: The Dream versus Reality - Laurel Orr | Stanford MLSys #89
Text2SQL: The Dream versus Reality - Laurel Orr | Stanford MLSys #89Stanford MLSys Seminars
Просмотров 5 тыс.
Foundation Models on Consumer Devices - Tianqi Chen | Stanford MLSys #8547:35Foundation Models on Consumer Devices - Tianqi Chen | Stanford MLSys #85
Foundation Models on Consumer Devices - Tianqi Chen | Stanford MLSys #85Stanford MLSys Seminars
Просмотров 3,8 тыс.
Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training19:15Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training
Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel TrainingQuantumBlack
Просмотров 3,1 тыс.
Notes on AI Hardware - Benjamin Spector | Stanford MLSys #881:16:48Notes on AI Hardware - Benjamin Spector | Stanford MLSys #88
Notes on AI Hardware - Benjamin Spector | Stanford MLSys #88Stanford MLSys Seminars
Просмотров 4,8 тыс.
AI, Machine Learning, Deep Learning and Generative AI Explained10:01AI, Machine Learning, Deep Learning and Generative AI Explained
AI, Machine Learning, Deep Learning and Generative AI ExplainedIBM Technology
Просмотров 378 тыс.
Teaching LLMs to Use Tools at Scale - Shishir Patil | Stanford MLSys #981:06:34Teaching LLMs to Use Tools at Scale - Shishir Patil | Stanford MLSys #98
Teaching LLMs to Use Tools at Scale - Shishir Patil | Stanford MLSys #98Stanford MLSys Seminars
Просмотров 5 тыс.
Hardware-aware Algorithms for Sequence Modeling - Tri Dao | Stanford MLSys #871:19:06Hardware-aware Algorithms for Sequence Modeling - Tri Dao | Stanford MLSys #87
Hardware-aware Algorithms for Sequence Modeling - Tri Dao | Stanford MLSys #87Stanford MLSys Seminars
Просмотров 6 тыс.
USENIX ATC '21/OSDI '21 Joint Keynote Address-It's Time for Operating Systems to Rediscover Hardware1:06:20USENIX ATC '21/OSDI '21 Joint Keynote Address-It's Time for Operating Systems to Rediscover Hardware
USENIX ATC '21/OSDI '21 Joint Keynote Address-It's Time for Operating Systems to Rediscover HardwareUSENIX
Просмотров 40 тыс.
Geoffrey Hinton | On working with Ilya, choosing problems, and the power of intuition45:46Geoffrey Hinton | On working with Ilya, choosing problems, and the power of intuition
Geoffrey Hinton | On working with Ilya, choosing problems, and the power of intuitionSana
Просмотров 262 тыс.
The Next 100x - Gavin Uberti | Stanford MLSys #9259:21The Next 100x - Gavin Uberti | Stanford MLSys #92
The Next 100x - Gavin Uberti | Stanford MLSys #92Stanford MLSys Seminars
Просмотров 6 тыс.