Peter Elger is the founder and CEO of four Theorem; his focus is on delivering business value to his clients through the application of cutting edge serverless cloud architectures and machine learning technology. His experience covers everything from architecting large-scale distributed software systems, to leading the internationally-based teams that built them.
In this episode, Peter tells us how his first real passion was in physics. After graduating with a BSc in Physics and a master’s degree in Computer Science, he worked for several years at the Joint European Torus (JET), the world's largest operational magnetically confined plasma physics / nuclear fusion experiment. They were doing big data, but at the time they did not refer to it as such; they dealt with around four to five terabytes of scientific data. Peter then transitioned to Indigo Stone as a Senior Technical Architect. Indigo Stone was a software disaster recovery firm which exited in 2007 to EMC.
Peter explains how it is essential to keep your technical skills up-to-date and why some of his favorite days are when he gets to code despite being the CEO of his company. If you can actually be the bridge between the business and the technology, you are an invaluable asset to any company. The freedom to innovate is what led Peter to his entrepreneurial ventures; previously, he had no real experience being his own boss. Peter says it is dangerous to think you can do everything; you have might a broad skill set, but you need to recognize that you have gaps. This is why Peter has always started businesses with co-founders. Currently, his co-founder is a world-class technologist and someone who understands the human dimension. All of his current co-founders and people Peter has worked with previously.
Later, Peter explains why he wrote about applying AI to existing platforms in his book, AI as a Service. He also recently wrote a chapter on how to apply machine learning to existing systems and the patterns that arise within two systems. Then, Peter describes why you do not need knowledge of AI to use AI as a service. In the past, everyone wanted their own security department; however, people already have the same technology that is vastly better than your own. This applies to how you can utilize AI within your existing business systems. Peter wants people to be interested in machine learning, but only a basic understanding is essential to use it within a business context. Finally, Peter discusses his approach to finding the most capable team members, being open and upfront with all staff members, and removing the ego to allow his team to perform their best work.
Enjoy the show!
We speak about:
[01:45] How Peter started in the data space
[06:50] Transition to disaster recovery
[08:55] Interactive radio and marketing applications
[13:40] Maintaining a grip with technical skills
[16:20] The entrepreneurial bug came organically to Peter
[18:40] Transition to entrepreneurship
[21:45] What to look for in a co-founder
[26:00] Building analytics with machine learning
[29:00] A tale of two technologies
[33:00] Applying AI to existing platforms
[35:10] Knowledge of AI is not necessary to use AI as a service
[37:50] Capable team members are difficult to find
[40:10] Sharing management meetings with all staff members
[44:05] Experiences with handling politics in organizations
[48:50] Removing ego + allowing the team to do their best work
[50:30] Scheduling work to maximize the impact
Peter’s LinkedIn: https://www.linkedin.com/in/peterelger/?originalSubdomain=ie
Peter’s Twitter: https://twitter.com/pelger
Peter’s Book: AI as a Service
“Computers don’t lie, and they do what you tell them.”
“In order to sell to someone, you need to understand what their problems are.”
“Business is all based on delivering value and building relationships.”
“Good software engineers have been doing things before they had a name.”
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Peter Elger is based in Ireland.
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