Leo Meyerovich on how and why the best companies are adopting Graph Visual Analytics, Graph AI, and Graph Neural Networks.
Leo Meyerovich is founder and CEO of Graphistry1, a startup building tools to democratize visual graph intelligence and graph machine learning. Leo and I recently wrote a well-received post (“What Is Graph Intelligence?”) making the case for why companies need to revisit graph analytics and graph intelligence. We believe that it’s just a matter of time until graphs become a standard method to analyze data for operational insights. In this episode we discuss the key insights from our post, and Leo provides updates on the rapidly changing ecosystem for graph intelligence.
If we just start on the visual side, we think of a few categories here. Some of the classic “connect the dots” scenarios. A lot of our work is forensic where there’s a security or fraud incident, or physical people interacting. Often there’s actually metadata in it. Nowadays everyone’s dealing with digital data. So for forensics it might be people are clicking around a website, and maybe they’re a bot ring trying to defraud your website. We also get into a lot of big companies where they don’t see their supply chain, they don’t know their HR hierarchy. And that’s a lot a lot of the connect the dots stuff.
The other side is more of a data science perspective where one way of thinking about an edge in a graph is a correlation. … And more broadly, If you’re looking at different correlations, and a lot of disparate data sets, you want to really get those fuzzy correlations. You’ll end up with a graph and having visual tools early in your data process … let’s you actually reason about those relationships. If you want to make machine learning interpretable, one of the things I’m seeing is while a graph is not the end all, it’s actually one of the more powerful tools for showing correlations.
In our recent post we highlighted the explosion in interest in graph neural networks (GNN) within the research community. As this begins translating to industry interest in building and using GNNs, companies will need tools for data processing. As we noted in our post, companies can use modern data platforms and tools like Spark to perform most Graph Intelligence tasks. But as Leo notes in this episode, some large-scale data processing requires graph computations that aren’t convenient to do with existing open source data processing tools. This is a gap in the suite of open source data processing tools that aspiring open source developers might want to fill.
Highlights in the video version:
- Introduction to Leo Meyerovich
What is graph intelligence? Do you detect a change in interest level?
What tools do companies use to turn data into graphs?
For graph analytics on the visual analytics side, how accessible are the tools now?
Have tools for navigating large chart graphics improved?
Current state of graphic neural networks tools and future of these tools?
You may not need a graph database to get started
For graph AI and graph machine learning, you don’t really need a graph database
Graph analytics, massive graph queries, and modern data platforms
Is there the equivalent of SQL for graphs?
What’s been the reaction to the graph intelligence stack?
Are vector databases optional on the ML side?
Examples of graph neural networks that do not use a vector database
What will the graph intelligence landscape look like in late 2022 and early 2023?
What about the usability of graph neural networks in computer vision and NLP?
Universal models, model hub, and fine tuning in NLP
When will it become routine for an analyst to present their decision maker with graph analysis?
Episode Notes will include free tools from Graphistry
Examples involving blockchain
- A video version of this conversation is available on our YouTube channel.
- What is Graph Intelligence?
- Simon Crosby: “Delivering Continuous Intelligence at Scale”
- Mike Tung: “Applications of Knowledge Graphs”
- Zhe Zhang: “How Technology Companies Are Using Ray”
- “Where Do Machine Learning Engineers Work?”
- “Get Ready For Confidential Computing”
 Ben Lorica is an advisor to Graphistry and other startups.