Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Introduction
00:00 • 4min
The Future of Machine Learning
03:49 • 3min
Transparency in Machine Learning
07:00 • 3min
How to Use Machine Learning Tools to Improve Transparency
09:51 • 2min
The Importance of Inherently Interpretable Machine Learning
11:30 • 3min
The Bogging Machine Learning Systems for Safety and Performance
14:24 • 2min
The Importance of Validation in Banking
16:05 • 4min
The Importance of Domain Knowledge in Decision Making
20:24 • 2min
The State of Tooling for Model Validation for Structured Data
22:42 • 3min
The Reality of AI Risk Management
25:29 • 2min
The Importance of Risk Management in Data Engineering
27:16 • 2min
The Importance of Data in Engineering Design
28:50 • 4min
The Importance of Language Models in Alignment
32:25 • 2min
The Future of Cybersecurity
34:11 • 2min
The Demise of Responsible AI in Banking
36:36 • 2min
The Relationship Between Independent Testers and Model Validators
38:21 • 3min
How to Build Better Models
41:12 • 3min
The Importance of Documentation
44:11 • 2min