Gradient Dissent: Conversations on AI

Chris Albon — ML Models and Infrastructure at Wikimedia

Sep 23, 2021
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1
Introduction
00:00 • 3min
2
What Are Some of the Most Contentious Wikipedia Articles and Does Your Team Ever Get Involved?
03:09 • 2min
3
The Implications of Modeling
04:44 • 2min
4
Detecting the Most Common Type of Spam Attacks on Machine Learning Systems
06:32 • 3min
5
How to Live Stream Your Open Source Work?
09:56 • 4min
6
Do You Think You've Had to Develop a Thicker Skin?
13:33 • 3min
7
How Do You Get Distracted by the Content on Wikipedia?
16:10 • 2min
8
What's Your Favorite Wikipedia Page?
18:11 • 2min
9
What Are the Important ML Applications at Wikipedia?
20:05 • 2min
10
Is There a Gold Standard for NLP?
22:33 • 3min
11
How Do You Prioritize Requests?
25:13 • 2min
12
ML at the Wikimedia Foundation
27:38 • 2min
13
Is Wikimedia Using Deep Learning?
29:58 • 3min
14
ORS Is a Homegrown Model Management System
33:26 • 5min
15
AWS Kubeflow
38:15 • 2min
16
Kubeflow
40:00 • 3min
17
How Did You Get Into Machine Learning?
42:58 • 4min
18
Do You Have a Flashcard for ML Interviews?
46:44 • 3min
19
How Do You Avoid Gotcha Questions When Interviewing Data Scientists?
49:46 • 2min
20
What's the Biggest Challenge of Machine Learning?
52:13 • 4min