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Large Language Models in Production Round-table Conversation

Mar 23, 2023
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Episode notes
1
Introduction
00:00 • 2min
2
Introduction to Large Language Models
01:41 • 2min
3
What Is a Large Language Model?
03:24 • 2min
4
The History of Transfer Learning
04:56 • 3min
5
The Importance of Large Language Models
08:17 • 2min
6
How HANA Can Help You Make Better Decisions
10:00 • 2min
7
How to Integrate Large Language Models Into Your Product
11:56 • 3min
8
The Open Source Movement
14:31 • 2min
9
The Benefits of Off-the-Shelf Models
16:50 • 3min
10
How to Use OpenAI in Production
19:25 • 4min
11
The Engineering Gap in ML
23:30 • 2min
12
The Trade-Offs of Learning ML to Do ML
25:25 • 2min
13
Building Machine Learning Powered Applications
27:25 • 2min
14
The Future of LLM in Production
29:52 • 2min
15
The Cost, Quantity and Latency Triangle in Software Development
31:49 • 2min
16
The Importance of Re-Architecting Production
33:54 • 2min
17
The Importance of Engineering Skills in MLP
35:57 • 3min
18
The Moore's Law Approach to Large Models
38:44 • 2min
19
The Divergence of Real-Time Use Cases
41:06 • 2min
20
The Cost of Latency in a Condensed Version Event
43:30 • 3min
21
How to Optimize for Cost in Meta Scale
46:37 • 2min
22
How to Avert Cost in ML Projects
48:29 • 2min
23
The Importance of Trust in Language Models
50:05 • 2min
24
How to Make Probabilistic Workflows Feel More Deterministic
52:27 • 2min
25
The Benefits of a Constant Look Up for Databases
54:42 • 3min