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

Posted on Saturday, May 15th 2021

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.

The community also has a key voice in our product development process. Rather than have a huge group of people that are half good users of our technology, we have a much smaller group of people that we spend a lot of production time with. We also spend quite a bit of training time on getting them to be efficient in our technology and learning how we can make the technology work for them. 

Sramana Mitra: Just to get a sense of the scale, how many are we talking about? How many people are currently in this group that is working with you?

Spence Green: It’s in the order of thousands in the active translator community. There is also a larger group of people that have been qualified to work with us. 

Sramana Mitra: Obviously as you scale, this number is going to need to grow, because there is a manual scaling element to your business.

Spence Green: That is correct. In most services businesses, whether it’s law firms, consulting firms, or barber shops, the revenue scales linearly with the number of people. The premise of this business is that we can use software to maximize the productivity of each individual person and that we would break the link between revenue and people in terms of the linear relationship as we scale. That is one of the objectives of the business. 

Sramana Mitra: You are probably not familiar with my writing based on what we discussed in the beginning, but you can go back and read my work. For ten years, I talked about SaaS-enabled BPO where there is a big technology component and then there are people who do pieces of business processes. It’s not linear people-driven growth; it is extensively technology-driven growth. That is what you are talking about. It is a SaaS-enabled BPO business model for you. 

Spence Green: That is exactly right.

Sramana Mitra: Talk about your government business. What kind of use cases do these government agencies plug you into?

Spence Green: There is a problem in government that goes back to the formation of governments and international diplomacy. Governments typically operate in one language and they interact with the world in other languages. Governments tend to be short of language capabilities for the parts of the world that they need to engage either for diplomatic reasons, intelligence reasons, or even if they have a multilingual population to engage with their constituents.

There are two reasons for the shortage. One, if you are a great people, you have to have people who speak 150 languages to engage all over the world. That is hard to build. Secondly, for many governments and especially in defense and intelligence applications, there is a security requirement. You have to have people. You have to have people who not only are capable of these languages, but you also need them to do classified government work.

There are never enough people and the amount of data created that governments need to process is increasing at an exponential rate. This was the origin of machine translation research which is what we worked on after World II. 

This segment is part 3 in the series : Thought Leaders in Artificial Intelligence: Spence Green, CEO of Lilt
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