Skip to content
Kinetica in Motion
The Kinetica Blog
Blog »
Andrew Wooler

Highlights from Kinetica CEO Paul Appleby on the M4Edge Podcast

Our CEO Paul Appleby joined the M4Edge podcast this week to discuss industry transformations and how Kinetica is helping the world’s largest organizations to solve their toughest challenges with active analytics. Paul chatted with hosts Michael Leifman and Marco Annunziata on how organizations can use data in real-time to fight pandemics, navigate traffic, analyze banking, and more. Check out the full episode here and find the highlights below!

On joining Kinetica (3:49): 

Appleby: “It actually came down to one meeting. I met with [Kinetica’s] earliest investor, Ray Lane. He used to be president of Oracle, and he called me and said, listen, I want some help with this company…what Ray shared with me about Kinetica, where it came from and the problems that it’s solved, really caught my eye because I’d been looking for a long time for a company that sat at the crossroads of data, business, and AI. In Kinetica, that’s what I found.”

On digital transformations across industries (5:33): 

Appleby: “I was able to attend the World Economic Forum, I think it was six years running in Davos, and there was a consistent theme that evolved in those conversations. Everybody puts a different label on it, Industry 4.0, the 4th Industrial Revolution, Digital Transformation, et cetera…

…What it came down to is a fundamental realization that each and every one of those things was really talking about organizations, governments, and societies, taking data and leveraging it in a totally new way. Not putting it into giant swamps and driving some sort of insight out of it, but actually looking at data as a perishable asset. 

The ability to actually ingest these huge streams of events that might be occurring from wearables to medical devices, from motorcars to smart grids or smart cities, to be able to consume that data, interpret it, learn from it and respond to it dynamically. That’s what Kinetica was built for.”

On Kinetica’s origins with the U.S. intelligence community (10:16)

Appleby: “We were founded out of a research project in U.S. intelligence that was really aimed at doing what Hollywood would believe that we solved many years ago, which is consuming vast amounts of structured and unstructured data. You would imagine all of the data that the Intel agencies have access to from satellite imagery, drone footage, mobile data, social media data, et cetera. But taking those vast volumes of data, running those streaming data sets up against historic data, analyzing that data in the context of location, and running complex models to identify patterns of behavior that could predict risk of catastrophic events.”

On solving the key challenges for telcos rolling out 5G (17:43):

Appleby: “Every telco on the planet is looking at their 5G rollout. Now, for those of us that know a little bit about 5G, we know the propagation models are totally different to 4G…It’s a huge geospatial computational challenge because you have to layer all of the traffic data. You have to lay that over 5G propagation models and then layer over that a 3D model of every one of the cities that we’re going to deploy our 5G infrastructure in.

We worked with a telco recently who was trying to do this and they calculated, for the state of California with their existing tech, that it would take five years of compute runtime to build a single model. Now, we did it in 50 minutes in a POC. So we’re pretty excited about what we’re able to do there.”

On the importance of ease of implementation (27:26): 

Appleby: “In this world of dynamic change, if you’re talking about bringing essentially a toolkit into a company that requires 200 forward deployed engineers and 18 months or 24 months to do a project, you are just completely out of step with reality. So a big part of our focus as we came to market was not only to produce this incredibly disruptive and innovative technology, but to create a form factor that was easy to address for the developer class and for the creative class.

[Kinetica] presents itself as a relational database, with an architecture built around open APIs. So somebody with a good basic understanding of relational databases and development can take Kinetica as a platform and start building these modern data-driven applications.”

On real-time analysis for financial services (34:11): 

Appleby: “I was in New York [in February] and met with an executive who owns data and analytics for one of the world’s top five banks. And he said that, the interesting thing in financial services, because of the volume of data and challenges in their world with legacy technology, they live in the world of batch processing still. Things like risk, which is a key element in a highly regulated environment, is managed as a batch process. It runs overnight on a separate data science platform.

What we’re able to do with them is bring together all of the events that are occurring in the market. So all the trading events, all the historic trading data, and run their risk models in real time. 

Kinetica is being deployed as a high speed fabric in the bank. Any process or workload that they want to bring into this real time or near real time world, Kinetica is going to act as the speed layer.”

On the future of work (48:58): 

Appleby: “I’ve joined the board of a future thinking high school, which is a school that’s built around the principles of project based learning and design thinking. It’s really about educating the next generation of workers, not for the kind of post industrial revolution manufacturing era that we were in, which is the way most schools educate our kids, but for this modern, disruptive, automated future that we’re actually living in today…

…There is no doubt that automation, AI, robotics, will replace the work that was done by humans…so there’s no doubt going to be great societal dislocation. But what I would say is, if we’re in the fourth industrial revolution, if every time that machines replaced work that humans used to do and those humans lost those jobs in aggregate, we’d probably have 60 or 70% unemployment today. We don’t, and the reason is that those technologies created new forms of work.”

You've made it this far, share it on:
GPU Data Analytics eBook
New White Paper

BI Meets AI

Augmenting Analytics with Artificial Intelligence to Beat the Extreme Data Economy