Thought Leaders in Artificial Intelligence: Francisco Webber, CEO of Cortical.io (Part 7)

Sramana Mitra: I have two questions. One is about who you see in deals. When you are trying to do these large deals with large customers, who else is showing up in those deals? What other alternatives are these customers considering?

Francisco Webber: You mean in competitive terms?

Sramana Mitra: Yes.

Thought Leaders in Artificial Intelligence: Francisco Webber, CEO of Cortical.io (Part 6)

Sramana Mitra: So, it’s a combination of angel financing and a lot of bootstrapping using services. Now, you are at a point where you also have production-grade product systems. 

Francisco Webber: The big pivot was in 2019 when we decided that our current frameworks were stable and mature enough to boil them down into specific products. We were also lucky to get an investment round with a company called Xilinx. It turns out that using SPGA hardware allows us to speed up our algorithms. We were lucky enough to convince Xilinx that it makes sense to develop designs on FPGAs which speed up our main filter, for example.

Thought Leaders in Artificial Intelligence: Francisco Webber, CEO of Cortical.io (Part 5)

Sramana Mitra: Everything that I have listened to so far is pointing to the fact that this company needs to be scaled as a Platform-as-a-Service company more than a pure solution company. 

Francisco Webber: Interestingly, investors prefer you to be focused, especially in the early round. 

Sramana Mitra: Absolutely.

Francisco Webber: It’s a bit of a problematic situation. 

Thought Leaders in Artificial Intelligence: Francisco Webber, CEO of Cortical.io (Part 4)

Sramana Mitra: Let me ask you a few different questions that come to mind as I am listening to you. First, you said that a large New York bank came to you, what does that mean? How did they know about you? How did that happen? A large New York bank doesn’t just come to a random company. 

Francisco Webber: That is a good question. They had a team that was supposed to be their spearhead in AI technologies. They had a bunch of experts who were scanning the market. At that time, we were a tiny company far away in Austria. The only way for us to reach out was for me to buy a plane ticket one after the other to do meet-ups and small-scale conference presentations.

Thought Leaders in Artificial Intelligence: Francisco Webber, CEO of Cortical.io (Part 3)

Francisco Webber: In the end, it translates to a situation where we could ask a person to manually annotate something like 50 documents, and the system would pick up the characteristics like the typical content, position, and context where a paragraph containing this would appear. We could demonstrate that with 50-100 examples, the system could be trained to perform even better than a human would, especially if the human has to annotate thousands of documents.

This is a problematic situation. That was one out of the ten use cases that we confronted there. They decided to license the technology at that time even in its crude form. After that, there came a bunch of other large players who allowed us to work on specific use cases in the domain of finance, chemistry, and car manufacturing. That was something that we saw quickly. There was no obvious domain in business terms where what we had would apply. It was rather a kind of use case that became the vertical.

Thought Leaders in Artificial Intelligence: Francisco Webber, CEO of Cortical.io (Part 2)

Sramana Mitra: Let me interrupt you for a second and try to understand the technology better. I completely understand the statistical approach versus more of the semantic modeling approach. How do you start? Let’s say you get a dataset. How does this begin?

Francisco Webber: One big problem that we have in statistical representation is that we lack something like semantic grounding. There are no fundamental ground truths to which we can tie the features and properties of what we want to represent. In our approach, we model what the brain does by the continuous saving of all the experiences.

How to Build an Artificial Intelligence Startup

One of the single hottest trends in technology startups is Artificial Intelligence (AI). Machine Learning, Natural Language Processing, and various other nuances are being constantly applied to problems up and down the alleyways of all industries from Manufacturing, to Retail, to Education, to Drug Discovery.

All the methodology building blocks you have been learning through the 1Mby1M entrepreneurship fundamentals courses apply. You can, for instance, bootstrap an AI startup with Services, then you can raise money (or not). You can build a Unicorn (or not). To apply current discount coupons, click on the courses found HERE.

>>>

Thought Leaders in Artificial Intelligence: Francisco Webber, CEO of Cortical.io (Part 1)

This is a terrific conversation on cutting-edge Natural language processing (NLP) with an entrepreneur in Vienna. Read on!

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

Francisco Webber: I am the CEO and one of the founders of Cortical.io. It is a startup originating from Vienna, Austria. We are working in the domain of natural language understanding. We have developed our own technology for rendering text information.