Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Introduction
00:00 • 3min
The Future of Machine Learning
03:24 • 2min
The Benefits of Learning From Past Experiences
05:10 • 2min
How I Learned to Code
06:42 • 2min
How I Decided to Go to Graduate School
08:22 • 2min
The Evolution of Parsing
09:53 • 2min
The Importance of Dependency Parsing
12:02 • 2min
The Importance of Reading Completion
13:43 • 2min
Neural Reading Completion and Beyond
15:16 • 2min
The Future of Machine Completion
17:13 • 1min
The MC Test: A Full Package
18:40 • 1min
The Evolution of the MC Test
20:09 • 2min
The Challenge of Defining the Right Problem
22:13 • 2min
How Dr. QA Is Building a System That Can Answer Open Domain Questions
24:22 • 2min
The Stanford Attentive Reader: A Novel Approach to Reading Comprehension
25:58 • 2min
The Interaction Between Memory Networks and Neural Reading Comprehension Models
27:43 • 2min
The Importance of Reading Completion Models
29:52 • 2min
The Benefits of Pre-Chalang With Models for Question Answering
32:05 • 2min
The Benefits of Retrieval-Based Models for Question Answering
34:00 • 3min
The Benefits of Generic Datasets for Reasoning
36:35 • 2min
The Challenges of Generalization in Large Scale Neural Sequence Models
38:20 • 2min
Conversational Question or Co-Currency
39:52 • 2min
The Importance of Question Answering and Dialogue in Dialogue Systems
41:34 • 2min
The Importance of Efficiency in NLP Systems
43:21 • 3min
How to Build a Stronger Natural Language Understanding Systems
46:12 • 2min
How to Pick New Problems for Research
47:56 • 2min
How to Optimize for Career Aspects in Your PhD
50:08 • 2min
How to Slow Down and Carve More of a Major Path
52:03 • 4min