Please login or sign up to post and edit reviews.
Chris Albon — ML Models and Infrastructure at Wikimedia
Podcast |
Gradient Dissent
Publisher |
Lukas Biewald
Media Type |
audio
Categories Via RSS |
Technology
Publication Date |
Sep 23, 2021
Episode Duration |
00:56:15

In this episode we're joined by Chris Albon, Director of Machine Learning at the Wikimedia Foundation.

Lukas and Chris talk about Wikimedia's approach to content moderation, what it's like to work in a place so transparent that even internal chats are public, how Wikimedia uses machine learning (spoiler: they do a lot of models to help editors), and why they're switching to Kubeflow and Docker. Chris also shares how his focus on outcomes has shaped his career and his approach to technical interviews.

Show notes: http://wandb.me/gd-chris-albon

---

Connect with Chris:

- Twitter: https://twitter.com/chrisalbon

- Website: https://chrisalbon.com/

---

Timestamps:

0:00 Intro

1:08 How Wikimedia approaches moderation

9:55 Working in the open and embracing humility

16:08 Going down Wikipedia rabbit holes

20:03 How Wikimedia uses machine learning

27:38 Wikimedia's ML infrastructure

42:56 How Chris got into machine learning

46:43 Machine Learning Flashcards and technical interviews

52:10 Low-power models and MLOps

55:58 Outro

This episode currently has no reviews.

Submit Review
This episode could use a review!

This episode could use a review! Have anything to say about it? Share your thoughts using the button below.

Submit Review