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Edward Scott is the CEO of ElectrifAi, one of the oldest machine learning product companies in the US serving the Fortune 500 as well as the federal and state sectors. Ed has over 25 years of experience in the technology and private equity sectors building, managing and investing in dozens of high-growth enterprises globally.

Ed started his career in the LBO group of Drexel Burnham Lambert and joined the Apollo Investment Fund in 1990. While at Apollo, Ed invested in dozens of companies across multiple industries focusing primarily on the TMT sector, chemicals, transportation and financial services sectors and was on the board of directors for numerous Apollo portfolio companies. 

Ed was also a partner at the Baker Communications Fund, originating and managing the firm’s two most successful portfolio company investments, both of which have become multi-billion dollar enterprises: Akamai Technologies (NASDAQ:AKAM) and Interxion Holding NV (NASDAQ: INXN). Akamai is the global leader in content distribution and edge computing and Interxion is the largest data center and managed services business in Europe. Ed has held senior-level positions at Napier Park Global Capital and White Oak Global Advisors. Ed graduated from Columbia University with a B.A. in history and earned an MBA from the Harvard Business School with second year honors.

Episode Links:  

Ed Scott’s LinkedIn: https://www.linkedin.com/in/edward-scott-74354923/ 

Ed Scott’s Twitter:  @Electrifai

Ed Scott’s Website: https://electrifai.net/ 

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Outline: 

Here’s the timestamps for the episode: 

(00:00) – Introduction

(02:30) – ElectrifAI is the United States oldest machine learning company that started off in the procurement area and then pivoted to create the first, fully integrated closed proprietary machine learning platform, everything from all the data ingestion and the transformation to the DQM, to the preparation for the models to the scoring, to the insights and so forth.

(02:57) – We transitioned that closed proprietary platform into a fully open platform built on the cloud, built on a common spark computational engine with the use of Kubernetes Docker containers and of course, notebooks.

(03:29) – We not only change the entire re-architecting to reengineer the entire technology stack, for our customers, to make it more modern and open and agile. We also shifted from being more of a data science consulting type of company to a fledged world-class machine learning products company. 

(04:43) – We focus on a certain number of verticals and a certain number of products. Our products focus on Procurement AI, Contracts AI, hidden risks, image AI, customer attention, customer acquisition, retention, and development, which is very important in the healthcare area with regard to patient steerage.

(06:17) – Everybody's data is disparate and it's disconnected and it's all over the place. It's on SAP system, Oracle systems, IBM systems, Cerner's systems, Epic systems, Allscripts systems. And there's no way really to get at that data until now. And that truly is one of the core competencies of ElectrifAi.

(07:10) – Without  clean data, there's no AI, that's simply the case. And we are seeing it across the world in the most sophisticated enterprise customers. And of course in the hospital and the payer space. 

(08:57) – If we're going to drive AI and ML into every single part of this business, it has to be done by leadership from the top in the digital world. If you are not embracing digitization in this world, your company's dead. 

(09:55) – When you look at comprehensive AI or a machine learning program, you really have to understand what your objectives are. What the objectives of the C-suite are. You need leadership and you need definition, clear scoping, project definition. The success of AI and ML really is contingent upon your capability and your competency in the data pipeline.

(12:58) –  If you, as the CEO or the CFO of your firm, cannot express a return on investment or return on invested capital from all the money you spent on data lakes and data marks and all the tools companies, you're going to be out of a job. 

(14:22) – Our areas of focus, our verticals are TMT, healthcare, financial services and the federal space. Principally because we have the machine learning products that dial up the revenue, dial down the cost and dial down the risk. 

(15:14) – The power of machine learning is using AI and NLP to extract key terms, words, and conditions from contracts to show risks, opportunities, how can you can reduce the number of suppliers that gain leverage with the ones that you actually annoyed, how can you can reduce the suppliers who are not focused on social issues.

(17:59) – It's a team effort at ElectrifAi. We talk about our culture, our culture of urgency, our culture of transparency, our culture of disruption, re-invention and self-examination and our culture of teamwork.

(18:51) – Data is in our blood, but it's practical data and practical ML, and that's why we go back to getting the data prepared and so forth. We are going to change the way the world works in machine learning. They believe that our suite of practical machine learning products will help that C-suite in a very differentiated way. So it's all done with that team.

(21:23) – The world is facing a massive demand and supply shock. And that's going to hurt the technology business and the small companies. And it's going to hurt companies that have tremendous fixed costs and cannot adjust those fixed costs or that risk quick enough.

(25:14) – We have an image analytics department that automates annotations and then turns all those pixels into ones and zeros, and in a sense, mimic SQL and is able to search a database to say over the last 50 years, and give all the liver tumors. That is real power for ML and it's spreading into how we do with COVID. We can get that person segregated quickly into care versus them going into the cities and spreading it more. That's a game changer. Our technology is three years out ahead of the market.

(30:49) – We haven't seen in a while the collaboration of the world together to attack an issue. We are citizens of the world and we have to solve this problem together and we have to solve it now. And it's a very exciting time.

(33:46) – Businesses will adapt and will adjust to the new world of not necessarily conducting business by congregating in the office. But, those that are very adaptable and flexible and purposeful and very customer driven.

(37:01) – Our mission is to change the way the world and our customers work in machine learning. Our culture is a culture of urgency, transparency, disruption, re-invention, self-examination. We tell our customers, we'll serve you through ML today. But tomorrow there might be a completely new technology, and we'll have to adapt. And that adaptability is at the heart of who we are. 

(43:13) – I'm going to say that the Time’s 2020 person of the year is humanity, because we're going to come together as a global family and solve this. AI for the good.