An Interview With Fotis Georgiadis
You always need 5 years to get a product to the market.
As a part of our series about business leaders who are shaking things up in their industry, I had the pleasure of interviewing Francisco Webber.
Francisco Webber is co-founder and CEO of Cortical.io and inventor of the company’s proprietary Retina technology, which applies the principles of cerebral processing to machine learning and natural language understanding (NLU) to solve real-world use cases related to big text data. Cortical.io solutions are based on the actual meaning of text, rather than on statistical occurrences. Francisco recognized that the brain was the only existing reference system when it came to processing natural language. While closely following developments in neuroscience, he formulated his theory of Semantic Folding, which models how the brain represents language data.
Thank you so much for your time! Can you tell us a bit about your “backstory”? What led you to this particular career path?
My first encounter with search systems dates back to my medical studies at the Vienna General Hospital. It was very difficult to find relevant patient information in the hospital databases. We knew the information was there, but the system was not able to retrieve it. It was a very frustrating experience that repeated in different contexts during my career. For example, I worked with patent experts from large companies who complained about the limits of their search systems. The common denominator of these search systems: they were all relying on statistical modeling information retrieval theories. Looking for alternative approaches, I followed the research done in the field of computational neurosciences and got hooked by Jeff Hawkins’ Hierarchical Temporal Memory (HTM) theory. I had the idea that his interpretation of how information is processed by the brain could be applied to process natural language. Basically, I founded Cortical.io in 2011 to test this idea, with the support of the Austrian Research Promotion Agency (FFG), which funded the development of our first prototype. The results proved better than expected. An angel investor provided seed funding to hire our first team of developers.
Can you tell our readers what it is about the work you’re doing that’s disruptive?
The fundamental difference of our approach is that we focus on the data representation, not on the algorithm like the mainstream machine learning approaches do. Our Semantic Folding theory describes a new data representation called Semantic Fingerprint. It corresponds to the biological way to represent language information in the human brain: a sparse, distributed vector which encodes all meanings and contexts of a given text — a word, a sentence, a paragraph or even a 200-page book, choosing from a bundle of 16,000 semantic features. Semantic fingerprints are computed using set-theory and geometry instead of statistics and probability theory. Our approach combines both high computing efficiency and high precision — a paradigm change in an era where state-of-the-art models always impose a trade-off.
Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?
I am enthusiastic about what I do and keen to explain it to anyone wanting to listen. Many years ago, at a conference, I began explaining natural language processing to a guy during lunch break. I am used to people not knowing what this means, so I have a very simple and pictorial way of explaining it, “NLP for dummies” one could say. When I was finished, he introduced himself with a smirk. He was one of the top AI researchers in Germany at the time. I can tell you, now I always ask what people do before developing!
We all need a little help along the journey. Who have been some of your mentors? Can you share a story about how they made an impact?
I owe a lot to Donna Dubinsky, the CEO and co-founder of Numenta. She introduced me to important people in Silicon Valley and in the AI business. Coming from Austria, I had no contacts. She gave the right impulses at the right moment. Most of the people she introduced me to have had an impact on our business on one level or another. I would not want to miss the insights into many of her successful business ventures after she managed high-tech companies like Palm and Handspring.
In today’s parlance, being disruptive is usually a positive adjective. But is disrupting always good? When do we say the converse, that a system or structure has ‘withstood the test of time’? Can you articulate to our readers when disrupting an industry is positive, and when disrupting an industry is ‘not so positive’? Can you share some examples of what you mean?
Disruption is always both positive and negative. Disruption is about division. Something that was one gets parted in two and one of the two parts necessarily loses. Look at the heavy investments done by the automotive industry to build GPS systems in cars. They are now obsolete, as drivers simply use Google Maps on their cell phone. Look at the automation that is disrupting work processes: workers used to complain about the repetitiveness of their tasks, but now they are afraid of losing their jobs. There is always a negative side of disruption.
Can you share 3 of the best words of advice you’ve gotten along your journey? Please give a story or example for each.
- You have really understood something when you are able to explain it — in respect of software, it means even being able to rebuild it. In the words of Jeff Hawkins from Numenta, you only understand how the neocortex is working when you can build a small neocortex. The solution to the text processing challenge is hidden in life sciences.
- Never be too technical with a customer. Typically, people believe they should stick to their marketing speech when explaining a technology product to a prospect. But what this sentence really means is: You must explain the technology in a way that the customer can understand it. In other words, your technology must be strong enough to be explainable in general terms.
- You always need 5 years to get a product to the market: regardless of the product, regardless of the market, regardless of yourself. I could not believe it, but this is what happened with Semantic Folding and my previous startups.
We are sure you aren’t done. How are you going to shake things up next?
We have begun working on the next stage of Semantic Folding, which we call Semantic Supercomputing. It is about combining Semantic Folding with hardware acceleration to reach unparalleled levels of computing efficiency. The explosion of data produced by our digital age asks for a new computing paradigm. The current computing architecture based on the Von Neumann model is 70 years old and has been designed to process information based on numbers. The throughput limitations known as Von Neumann bottleneck represent a serious hurdle in processing semantics which led to the creation of energy consuming data models like BERT and GPT-3. In the context of global warming, a new type of computing based on efficiency is essential. Nature shows us how efficient processing can work: the brain is the most efficient processing system we know of. Semantic Supercomputing, which replicates the efficiency of the brain, can play a big role.
Do you have a book, podcast, or talk that’s had a deep impact on your thinking? Can you share a story with us? Can you explain why it was so resonant with you?
I am a big fan of Lex Fridmann’s podcast. Lex is an AI researcher from MIT who talks with people who have a cognitive science background. He has had conversations with Richard Dawkins, Noam Chomsky, or Roger Penrose, for example. Basically, the who’s who of AI is invited to his podcast — a must-listen. I also appreciate the TWAI ML podcast from Sam Charrington because it shares non-mainstream thoughts and insights on AI.
Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?
Persistence leads to the goal — this was the message I got when I threw my first set of sticks with a friend who was into i-ching and divination. At the time, I laughed at his interpretation, but I must admit that this is a recurrent theme in my life.
You are a person of great influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger.
I think it is essential to share one’s passion, knowledge, and ideas with others, particularly younger generations. You never know what a discussion can trigger. It can spark an idea, a keen interest or a potential career path. In any case, I am a fervent believer of 1+1=3: the combination of two minds produces more added value than two minds thinking separately.
How can our readers follow you online?
LinkedIn: https://www.linkedin.com/in/franciscoeduardodesousawebber
Twitter: @chico_webber
Thank you so much for joining us. This was very inspirational.
Francisco Webber of Cortical On The Three Things You Need To Shake Up Your Industry was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.
