Thought Leaders in Artificial Intelligence: Spence Green, CEO of Lilt (Part 1)

This is a terrific conversation about a SaaS-enabled BPO company, Lilt, in the domain of language translation.

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

Spence Green: I am the CEO of Lilt. We have two parts of our business. The private sector of our business focuses on creating global customer experiences so that all products and services are available in all languages. We work with enterprises that want to make the user experience in other languages better. Usually, it is as good and personalized as it is in English.

Thought Leaders in Artificial Intelligence: Edge Impulse CEO Zach Shelby (Part 3)

Sramana Mitra: You have 12,000 developers currently building ML applications, what is the constitution of these developers? Are these 12,000 developers sitting inside larger companies or entrepreneurs building new apps for new ISVs?

Zach Shelby: We have the whole spectrum. That is something that we have strived for. When you bring in new technology in the space, machine learning is advanced for a lot of these industrial companies and developers, we have to be available at the education level. We do have people who are just beginning and learning about this. They are typically professionals, but they might not be applying machine learning in their work. They might be C or C++ programmers but not yet using machine learning.

Thought Leaders in Artificial Intelligence: Edge Impulse CEO Zach Shelby (Part 2)

Sramana Mitra: Let’s double-click on how you managed to get 12,000 developers working and building on your platform.

Zach Shelby: What I found to work best with developers is radical transparency, focusing on what they care about, and how they work with their product. In our case, we provide machine learning tools in the cloud and lots of software around that. We are providing an open TRR platform so we don’t treat a developer as a customer, we treat them as a part of our team.

Thought Leaders in Artificial Intelligence: Edge Impulse CEO Zach Shelby (Part 1)

Zach is building a Machine Learning platform company upon which 12,000 developers are building apps.

This is a terrific conversation that spans how to build developer networks for a PaaS company, and numerous related issues.

Sramana Mitra: Let’s start by introducing our audience to yourself as well as Edge Impulse.

Thought Leaders in Artificial Intelligence: Divyabh Mishra, CEO of CrowdANALYTIX (Part 5)

Sramana Mitra: Where are you now?

Divyabh Mishra: Right now, we are close to $6 million. This year could have been a lot more, but everyone has had a hit this year – at least in the first half of the year. Nobody was sure where things were going. Things are picking up though. It has been a trend in the right direction.

Thought Leaders in Artificial Intelligence: Divyabh Mishra, CEO of CrowdANALYTIX (Part 4)

Sramana Mitra: You said that you partially sold the company at a $100 million valuation. What is the structure of the company?

Divyabh Mishra: That’s about 43% of the company. That is another interesting piece of the company. Macnica is a public Japanese company. They are distributors of semiconductor parts and are trying to diversify.

Thought Leaders in Artificial Intelligence: Charlie Delingpole, CEO of ComplyAdvantage (Part 6)

Sramana Mitra: You are based in London, right? 

Charlie Delingpole: I’ve been in the same room where I started it all. I’ve been in my garage for the past 14 years, but yes, I am in London. We have clients in 80 countries. We have a team in New York, Transylvania, and Singapore. 

Sramana Mitra: Are you saying that you work from home?

Thought Leaders in Artificial Intelligence: Divyabh Mishra, CEO of CrowdANALYTIX (Part 3)

Sramana Mitra: What is your business model regarding these data scientists who are building these algorithms for you?

Divyabh Mishra: Let’s say the community did not exist and I had subcontracted the work to someone else. They get paid for the work they do. The data scientists are getting paid for building the models. Once we pay them, that model becomes ours. We then deploy and maintain those algorithms and we charge the client for access to those models.