Artificial Intelligence

Artificial Intelligence encompasses a wide spectrum of converging technologies – Deep Learning, Machine Learning, Neural Networks and Natural Language Processing (NLP).

Artificial Intelligence which is sometimes called as Machine Learning can be defined as ‘the valuable part of machine learning is predictive modeling where we use historical data to train a model and use the model to make predictions’.

Tom Mitchell in his classic book on machine learning says: ‘The field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience’

Bereft of confusing buzzwords, AI is basically a technique to look for a pattern from training on a set of data. The key here is the data. Unless you start with the right data and preprocess the data and massage that for learning, you will end up with poor results.

We, at TargetWoman have been working at the Natural Language Processing from the year 2004 onwards – around the time we started. Simply put Natural Language Processing is the process of using specialized computer algorithms to identify key elements in everyday language and extract usable meaning from unstructured input. Microsoft says this about languages: “Understanding language means, amongst other things, knowing what concepts a word or phrase stands for and knowing how to link those concepts together in a meaningful way. "

We started working on the concept of Natural Language Progression way back in the year 2004 – long before the term Artificial Intelligence became a buzz word. We worked on the premise that to convey an idea or a thought – words are only a transport layer. It is not the word per se that conveys the idea/thought but the collection of words, their proximity to each other and the context. With that said, we turn our attention to using computers to understand the logical progression of our language which some call as Natural Language Processing. We have created a working model which can understand the subtlety of the language we speak – at least limited in context to health and medical topics.

A real world working example for the NLP is the ‘TargetWoman Health App’.

The computing power required to learn from millions of words in real time is humongous. But the technology is improving in leaps and bounds. These days you get the complete AI baked into a slice of silicon chip for the specific task. You get to see them even in mobile phones.