When building actor-based systems for Artificial Intelligence (AI) applications, the aim is to be able to characterize and explain the multitude of conversations and real-world observations happening around us. In other words, the goals is to understand the linguistics of cognitive thoughts and how humans use language to convey meaning in a given context. The linguistic structures by which any language conveys meaning are not just in the words people choose, but in the way those words infer knowledge, both implicit and explicit, about the world around us—elements such as emotion, intent, and desired outcomes. When teaching computers to understand language, the trick is to not just statistically count words and match strings, but to convey context and intent in a way that can be computed upon for a data-driven approach to Business and Operations.
In order to understand the sequence of processes (algorithms) and the tools
(applications) necessary to translate between human and machine communications,
this blog aims to describe the theoretical background as well as the real-world
practice of Natural Language Processing (NLP). There are three themes to this
conversation:
I: Understanding how language works for both humans and machines
II: Understanding Machine Learning and NLP as a confluence of Linguistics
and Computing
III: Understanding how applications can leverage the power of Computational
Linguistics
Too often, books and information in the domain of Artificial
Intelligence assume a baseline understanding of Computer Sciences
and programming. This site is designed for the novice and business audience
alike. The goal is to make clear the underlying technologies and algorithms in
NLP without having to grasp the code.
Join us in the journey as the women of Boldingbroke sort out all the
technobabble for those people in the business community who are not full-time
programmers and data scientists.
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