The science that simulates the engagement , decision and the discovery process of the human brain – Artificial Intelligence(AI) or Cognitive Sciences has unlocked a world of possibilities for the banking industry in particular. Cognitive systems quickly identify patterns similar to a way our brain identifies situations and responds to it.

Within AI , there are a number of different technologies and they lie at different points in the curve of adoption with virtual assistants and robo-advisors riding the crest of adoption. Semantic Technologies specifically have a world of discovery lying ahead. Although it is widely used as the underlying technology for most deep learning systems , there is a vast amount of work remaining in this area and experts believe it is only half tapped although it has been around for years.

This post is essentially focused on semantic fingerprinting and how semantic technologies are about extracting meaningful data from quantitative data , text , voice ,video and images . Unlike previous applications , data and relationships were pre-defined and read from relational databases but semantics open up a world of realtime relationship extraction and contextual inference models being built and leveraged at runtime.

Semantic Maps – Vocabulary Building Tools

Semantic Maps or Networks have been around for more than a decade where words are understood under the context they are used , very similar to how the human brain understands and processes words, phrases or a language. This technique is used as a teaching method for children learning a language and has been seen as a very powerful vocabulary building tool.

The same terminology takes on a far more complex computing context .Semantic Mapping can be used for dimensionality reduction of a set of multi-dimensional vectors to retain main data characteristics. The original properties are clustered to generate an extracted feature. This technology has typically been explored for text mining and information retrieval.

Semantic Fingerprinting

Semantic fingerprinting is a new method whose manner of processing text is modeled on that of the human neocortex . Semantic fingerprinting has the potential to be more powerful in document comparisons than are word list-based analyses.This technique is used to identify similarities , identify context and also arrive conclusions.

Since semantics are heavily dependent on context , the fingerprint for ‘Apple’ would have strong connections with the computer brand.  Words, Sentences and whole texts amounting to terabytes can be compared against each other.

Source : Cortical.IO

Big Data + Semantics = Endless Possibilities

Big Data Semantics is where technology is applied to reduce the stream of unstructured data to understand , predict , categorize or sort just as much as one would with any form of data once reduced to an understandable , identifiable form.

The system ingests data in any unstructured form – emails , faxes , documents , sms , social media or data from internal systems and then runs it through a semantic engine.  The semantic engine generates smart binary vectors with minimal memory footprint represented in boolean. This helps to compare aggregated or atomic representations of words .

Some ways in which it is being leveraged in banks are seen in the table below

We all know and acknowledge that larger tech giants such as IBM , Google , Apple have experimented and mastered these technologies over decades now and while IBM has focused on strong enterprise use of these technologies , Google and Apple have invested in embedding cognitive in consumer applications with specific focus on mobile tech. Also , having invested hugely across the AI technology stack , they also have a huge advantage of direct and indirectly available data corpus used for training data .This makes the competition one sided and leaves little room for startups. But what the startups are doing beautifully , is coming up with differentiated, disruptive use cases .With the rise of AI startups receiving funding across the globe , the interlocking of logically related technologies and their use cases are only to rise . We can only wait to watch for the treasures it unlocks.

Disclaimer: This post is not influenced by any of the institutions that I am/have been directly or indirectly associated with and views and opinions expressed are solely mine .

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