Thought Leaders in Artificial Intelligence: Ram Swaminathan, CEO of BUDDI.AI (Part 3)

Ram Swaminathan: We go back in time with the hospital data sets; and we mine the claims data and the medical record data, the way the physicians writing the notes come from different backgrounds. We grab all of those variants in history and we customize the NLP technology for AI to understand these various documents.

Thought Leaders in Artificial Intelligence: Ram Swaminathan, CEO of BUDDI.AI (Part 2)

Sramana Mitra: There is a company that we covered extensively for a while in the payments space. This was Athenahealth. It sounds like what you are doing is like what Athenahealth does but with AI. Is that correct?

Ram Swaminathan: That is correct.

Sramana Mitra: Why don’t you expound on that? I’ll phrase the question a little bit more specifically. Athenahealth’s big innovation was having the expertise to be able to manage these codes, claims, and collections processes.

Thought Leaders in Artificial Intelligence: Ram Swaminathan, CEO of BUDDI.AI (Part 1)

You have read our coverage of AthenaHealth over the years in the healthcare IT space. BUDDI.AI is taking an AI-driven approach to healthcare coding and billing.

Sramana Mitra: Let’s start introducing our audience to yourself as well BUDDI.AI.

Ram Swaminathan: I am the co-founder and CEO of BUDDI.AI. We focus on building the next generation of artificial intelligence for healthcare.

Thought Leaders in Artificial Intelligence: Spence Green, CEO of Lilt (Part 4)

Spence Green: One of the first applications of digital computers for cryptography and bomb-making were developed with machine translation. People started working on this in the late 1940s and early 1950s. Machine translation research surged and flowed over the following decade and it took off after 9/11 when the United States government realized that it didn’t have enough Arabic language speakers.

It started investing money and research in the university system to build these machine translation systems. Out of that came Google Translate and Microsoft Translator Hub. The latter was what put my co-founder and me through grad school. There were a bunch of us in 2000 working with machine translation.

Thought Leaders in Artificial Intelligence: Spence Green, CEO of Lilt (Part 3)

Sramana Mitra: How big is your community of translators?

Spence Green: It is a reasonably large community. It’s smaller than some of our competitors, but there is a reason for that. The reason is that we believe in our community. We would rather have a smaller group of highly-specialized people that we utilize completely than to have a much broader group of people that we treat like a crowd. We are building the technology at the same time that we are building the operational process.

Thought Leaders in Artificial Intelligence: Edge Impulse CEO Zach Shelby (Part 5)

Sramana Mitra: I enjoy listening to you and hearing what you have been doing. I keep my eye out for finding platform companies. You may want to look up my writing on the Platform-as-a-Service. I think you will enjoy that. It’s an area that we are covering extensively.

Switching gears, what are some open problems that see that you would like some new startups to go pick up using your platform? From where you sit, you are developing the platform and you are looking for developers to develop applications. If you could have your wish, what are some apps that you would like to see entrepreneurs take on using your platform?

Thought Leaders in Artificial Intelligence: Spence Green, CEO of Lilt (Part 2)

Sramana Mitra: Give me some examples of things that Google Translate cannot do, but you can.

Spence Green: Google Translate can do the same thing a person can do. You can give a string input and it can give you a string output. People can do that too. What you don’t have is any certificate of correctness. You don’t know if it is right or not.

Thought Leaders in Artificial Intelligence: Edge Impulse CEO Zach Shelby (Part 4)

Sramana Mitra: If I am a developer, what are my choices in terms of picking a machine learning engine or platform? What am I choosing from? You and who else?

Zach Shelby: What kind of developer are you? That is the real question. Rationally, machine learning and AI tooling have been designed for data scientists. Almost all machine learning tools are designed for the data scientist. That is okay if your job is to solve back-end cloud problems with machine learning.