Where ZK and ML intersect with Yi Sun and Daniel Kang

1

Introduction

00:00 • 2min

2

Axiom and ZK

01:32 • 3min

3

ZK DSL - Your First Foray Into the ZK Space?

04:02 • 2min

4

Machine Learning and ZK - What's Your Foray?

05:46 • 3min

5

How Does Collaboration in Machine Learning Work?

09:13 • 2min

6

How Did ZK Proofs Come to Be?

10:45 • 2min

7

ZKML

12:19 • 2min

8

Is the Cloud Provider Trustless?

13:55 • 2min

9

The Gold Standard Model Is Not a Cheaper Approximation

15:39 • 2min

10

Detecting Deep Fakes in Machine Learning

17:24 • 3min

11

Using a Tested Sensor on a Camera?

20:08 • 2min

12

Tested Cameras Are the Most Common Form of a Test Camera

22:00 • 2min

13

ZKML - The Fighting Deep Fix

23:35 • 2min

14

How to Authenticate Your Biometric Identifier

25:29 • 2min

15

The Future of Biometric Authentication

27:00 • 2min

16

Is There a Connection Point?

29:16 • 2min

17

ZKP

31:34 • 2min

18

Dating Apps

33:29 • 2min

19

CKML Combination

35:07 • 2min

20

Is There a Limitation on the Sets of Transformations?

36:45 • 2min

21

The Performance Hit From Hashing in DK?

38:30 • 2min

22

Adapted Nonlinearity in Machine Learning Models?

40:11 • 2min

23

Is There a Wiggle Room in Machine Learning?

41:45 • 2min

24

The Challenges of Quantization in Machine Learning on Edge Devices

43:23 • 2min

25

Using ZKML to Prove Nonlinearity Models

44:56 • 3min

26

Do You Think We'll Get to a World Where Machine Learning Applications Drive the Library Composition Behavior

47:34 • 2min

27

Is ZK Moving in a Specific Future?

49:22 • 2min

28

The Future of ZK or ZKML?

51:11 • 2min

29

What's Next for Machine Learning?

53:25 • 2min

30

ZKML - What's Next?

55:08 • 2min