Introduction to MLOps at the Edge | Alejandro Cantos | Conf42 Machine Learning 2023

Chapters
0:00 intro
0:22 preface
0:33 the cloud is broken
1:02 ¿why is it broken?...
1:14 ...dependence on the internet
1:43 ...high latency
2:15 ...service availability
2:37 ...loss of control
3:19 ...cost management
4:14 ...vendor lock-in
5:04 ...security and privacy
5:43 ...compliance
6:25 ¿which is the solution? #edge is the new cloud
7:04 ¿what is edge computing?
8:54 edge computing drivers...
9:03 ...low latency
9:56 ...lower bandwidth consumption
10:48 ...increased privacy and security
11:22 ...greater availability and autonomy
12:13 different types of edge
15:07 impact radar for 2023
15:37 index
16:14 acciona: intelligent virtual measurement of water components
19:55 edp: energy flexibility in self-consumption systems
23:55 edge computing ♥ ai - the architecture of alexa
28:36 maybe the cloud is not broken... maybe it just needs some friends
28:56 edge ♥ cloud ♥ ai - a powerful combination
29:12 ¿how do we manage this complexity?
29:43 mlops - machine learning operations
30:04 edge ♥ cloud ♥ ai - mlops cycle
30:52 mlops challenges
32:07 architecture and frameworks...
32:17 ...edge computing platforms...
34:43 ...native providers
35:23 barbara
35:33 technological stack
40:16 demo
45:32 applications
46:20 thank you