Name: MLT __init__ Session #17: LLM.int8()
Start: 2022-09-17T11:00:00+09:00
End: 2022-09-17T12:00:00+09:00

**📌 Paper Reading & Discussion**
📌 Tim Dettmers, Mike Lewis, Younes Belkada, Luke Zettlemoyer: [LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale](https://arxiv.org/abs/2208.07339)

**📌 Session**
11:00 - 11:05 am Introduction
11:05 - 11:30 am Presentation
11:30 pm - 12:00 pm Discussion

**📌 Presenter: Tim Dettmers**
Tim is a fifth-year PhD student advised by Luke Zettlemoyer at the University of Washington. He has a background in applied math and automation. His main work focuses on making transformers more efficient and understanding how they work.
Personal website: [https://timdettmers.com/](https://timdettmers.com/), Twitter: [https://twitter.com/Tim_Dettmers](https://twitter.com/Tim_Dettmers)

**MLT init** is a monthly event led by Jayson Cunanan and J. Miguel Valverde where a paper is first presented by a volunteer and then discussed among all attendees. Our goal is to give participants good initializations to study Deep Learning effectively. We also hope to promote collaboration between participants. We will try to achieve this by:

* Discuss fundamental papers whose key ideas apply to state-of-the-art models.
* Providing the audience with summaries, codes, and visualizations to help understand the critical parts of a research paper.

Find more information, the videos, and materials from previous sessions in [https://github.com/Machine-Learning-Tokyo/](https://github.com/Machine-Learning-Tokyo/__init__)**[init](https://github.com/Machine-Learning-Tokyo/__init__)**

**📌 Prerequisites**
We allocate most of the time for discussion and kindly ask participants to read the paper in advance and join the session with at least two questions or comments in mind. These can be parts of the research paper that you think is interesting or unclear. For instance: What did you like the most about this paper? What did you learn? What did you not understand?

**📌 Organizer's Bio**
**J. Miguel Valverde** is a PhD student at the University of Eastern Finland working on Rodent MRI Segmentation with Deep Learning. He has multiple research experiences across Europe and Japan. In his free time, he enjoys nature, learning languages, programming, and making food.
https://twitter.com/jmlipman

**Jayson Cunanan** is an AI Researcher/Engineer in Tokyo. He obtained a PhD in Mathematics at Nagoya University and was awarded the JSPS Postdoctoral Fellowship 2018. In his free time, he loves playing the guitar.
https://www.linkedin.com/in/jayson-cunanan-phd/
https://twitter.com/jsonmathsAi

● MLT PATRON
Become a MLT Patron and help us to keep MLT meetups like this inclusive and for free.[ https://www.patreon.com/MLTOKYO](https://www.patreon.com/MLTOKYO)

● FIND MLT RESOURCES
Github:[ https://github.com/Machine-Learning-Tokyo](https://github.com/Machine-Learning-Tokyo)
Youtube:[ https://www.youtube.com/MLTOKYO](https://www.youtube.com/MLTOKYO)
Slack:[ https://bit.ly/2Yb0uXI](https://bit.ly/2Yb0uXI)

● RECRUITING
MLT events are for community building and knowledge sharing. We politely ask that company representatives, recruiters and consultants looking to hire or sell their services do not participate in MLT activities or approach members in any form.

● CODE OF CONDUCT
MLT promotes an inclusive environment that values integrity, openness and respect.[ https://github.com/Machine-Learning-Tokyo/MLT_starterkit](https://github.com/Machine-Learning-Tokyo/MLT_starterkit)

J. Miguel Valverde

Suzana

Jayson Cunanan

Machine Learning Tokyo

Artificial_Intelligence

Technology

Neural Networks

Big Data

Artificial Intelligence Applications

Predictive Analytics

New Technology

Machine Learning

Natural Language Processing

Machine Intelligence

Data Science

Deep Learning

Artificial Intelligence

Open Source

MLT __init__ Session #17: LLM.int8()

Online event

共有

Machine Learning Tokyo

MLT init Session #17: LLM.int8()

Machine Learning Tokyo

詳細

メンバーは以下の興味/トピックにも関心があります