Скачать или смотреть AI Knowledge Graphs Explained: How to Cut Supply Chain Complexity by 95% | Featuring Max De Marzi

Yesterday, I hosted a RelationalAI LinkedIn Live session focused on tariffs, supply chains and AI. More specifically, we focused on one of my favorite topics, AI enabled Knowledge Graphs.

AI enabled Knowledge Graphs are fascinating (obviously) but can be abstract and difficult to understand. Especially if you aren't an engineer.

Given the advantages they present for Enterprises trying to adjust, on the fly, to expected and at times unexpected tariff changes to optimize supply chain management, their application today is more relevant and timely than ever.

I facilitated the session with Max De Marzi, a Knowledge Graph SME at RelationalAI.

I really enjoy Max's presentations because he takes abstract and highly technical concepts and explains them with more universal language while integrating pop culture into his entertaining narratives.

Yesterday’s LI Live Session was exactly that.

The 3 questions Max answered that I found most interesting:

1: How do Knowledge Graphs elevate the essence of your business logic from mountains of accidental complexity by effectively reducing your legacy codebases by 95%?

2: Based on #1, how much faster / better can you run supply chain simulations, what-if scenarios etc to anticipate what to do next in the event of more tariff changes?

3: Tell me more about “Graph Neural Networks” and their role in “shaping” your Knowledge Graph in a way that automatically adjusts to the evolution of your data sets as new data comes in?

The :30 minute session is up on YouTube and I encourage you to check it out.

Here is a link to the video: https://www.youtube.com/live/OYVLlI6f...

Below are the chapters with time stamps.

Tariffs and the Supply Chain Impact: 2:38 - 6:18
Yeti Coolers Use Case Visualizing the Supply Chain: 6:18-8:24
The (Same) Data Problem - Silos and Messy Data: 8:24-11:14
Relational Knowledge Graphs / Intelligent Supply Chains: 11:14-20:00
Predictive vs Prescriptive Analytics: 20:00-25:33
Talking to Your Graph via Natural Language Queries: 25:33-26:47
Q+A / The Shape of the Graph and its Benefits: 26:47-30:02