A. Disruptive Technologies in the Context of Natural Language Processing (NLP) - fayeanjeli/mms142-DRAFT GitHub Wiki

Disruptive technology is a type of invention that drastically changes the behavior of markets and consumers. Because it has more high-end features, Disruptive Technology displaces, if not renders obsolete, old models, processes, and systems.

Even a small business with limited resources can disrupt technology by creating an entirely new way of doing things. They built traditional technologies to serve those who wield the most influence rather than risk a new market. They tend to go with the flow and disdain radical transformations.

It creates an opportunity for innovative enterprises to zero in on small client niches and establish a presence in the market. And, as old-timer businesses are usually unable to respond to these changes, technology disruptors can advance past them and capture consumer interests.

Disruptive technology is notorious for appealing only to a small audience and performing inefficiently. However, although it rarely happens, it is still the wise option in the long haul. In the beginning, it may not be able to meet sophisticated marketability, but when it shows to be lucrative, it can break the market ceiling.

Computers and humans have different languages. For computers to understand us: we have to structure the data (code) and import it to the system. Thus, verbal communication with technology was not possible until the 20th century (Rotelli, 2019). One major disruptive technology that happened is the arrival of Natural Language Processing, popularly known as Virtual Assistants.

NLP is a form of Artificial Intelligence (AI) that examines human speech. The main essence of its technology is it helps machines to understand and communicate with human language. Virtual assistant technology like Apple with Siri, Amazon Alexa, Google Assistant, and Microsoft with Cortana uses a system that translates our spoken words into text that the NLP system used. Precisely, Analytic Insights (2019) affirmed that the system listens to 10 to 20-millisecond clips of human sound. Then, seek for phonemes to correlate with a pre-recorded speech. Those virtual assistants work by approaching verbal commands, deciphering the meaning of the uttered words, and executing the requested task. But, it does not end there; NLP enables our technology to interact with unstructured data that we produce in disruptive ways.