Why I care about how the brain works

Ever since I first became involved with data and analytics in 2006, I have been fascinated by the seemingly endless possibilities data can transform businesses. I’ve spent a lot of time with data management technologies which essentially comprise data processing, data storage and visualization. In some cases, this meant applying machine learning/statistical models to predict certain outcomes such as customer churn or device failures. Other projects involved AI models to extract information from images, videos, audio files and documents. I am extremely grateful for this experience as it allowed me to learn about state-of-the art data analytics solutions and how they can be applied in real-world scenarios. Along the way I met outstanding people at innovative companies and had fun, some successes and of course failures. I was particularly impressed how Microsoft’s Azure cloud platform evolved during my time there and how the team at Microsoft Austria managed to bring transformative technology to the market.

So that’s my professional past. But what made me leave a market-leading company like Microsoft and what were the motivations driving my decision?

While I was watching my 4-year-old daughter growing up and experienced, how quickly she learned and acquired new skills, I was wondering how this amazing little girl processed all this information? What was most impressive from my point of view, was how she understands language and its context.

In my professional life, I was experiencing the inadequacy of machine learning and rule based natural language processing systems and was often frustrated about their mediocre results, in particular their incapacity of handling language ambiguity.

I wondered if there is a better, more efficient way of processing language and its context by applying the concepts of how the brain understands language to computing, rather than using traditional statistical methods and word frequency calculations.

That’s how I found Cortical.io which proposes a unique paradigm for natural language understanding (NLU) that overcomes the limitations of other artificial intelligence (AI) approaches. Semantic Folding is inspired by the latest findings on the way the brain processes information. This novel theory introduces a new data representation, the Semantic Fingerprint, which encodes meaning explicitly, including all senses and contexts. The system determines the relatedness of two items by measuring the overlap of their fingerprints. As a result, it is very fast, reliable, and easy to implement—a breakthrough technology that leverages the intelligence of the brain to enable natural language understanding of big-text data.

The biggest benefit in my view is, that there is way less training data needed to achieve accurate results. This is a big deal as many organizations simply do not have large quantities of (labeled) data available or time needed for training purposes. Since the technology works with a meaning-based approach, it can accurately classify text even if a term is not represented in the training data. Another advantage of this approach is that it’s extremely computational efficient as it does not involve complex statistical calculations. The products Cortical.io has built with the approach require no AI/Data science experts which leads to faster time to value, reduced implementation costs and more real-life productive applications

Apropos applications – where can this new paradigm be applied in real-life use cases? Cortical.io has developed two products based on the technology that have potential uses in any industry struggling to gain insight from complex, unstructured text documents. Use cases can be found virtually everywhere. For example Insurance, Banking, Transportation & Logistics as well as Telecommunications companies all deal with a flood of complex documents. (Please find explainer videos below)

I'm excited to take on this new challenge with a great team of motivated people here at Cortical.io. Stay tuned for updates!

Peter

Contract Intelligence:

Message Intelligence:

Curious? This short 5-minute video explains how Semantic folding works: