Apogee Suite: AI-Powered Legal Document Research Platform
By VICTOR ANJOS
Natural Language Processing (NLP) is not just a buzzword; it’s a revolutionary technology that is shaping the way we interact with machines and computers. From virtual assistants like Siri and Alexa to predictive text on your smartphone, NLP is an integral part of our daily lives. But what exactly is NLP, and why is it so important? In this beginner’s guide, we will delve into the world of NLP, exploring its significance and its transformative potential. To understand NLP, we must first grasp its fundamentals.
What is NLP?
At its core, Natural Language Processing is a branch of artificial intelligence that focuses on the interaction between computers and human language. It enables computers to understand, interpret, and generate human language in a valuable way. Simply put, NLP helps machines understand us, whether we are typing, speaking, or even writing in a natural language such as English, Spanish, or Chinese.
Dr. Jurafsky and Dr. Martin, authors of “Speech and Language Processing,” define NLP as follows:
“Natural Language Processing is a field of study that focuses on the interaction between humans and computers through natural language. The ultimate goal of NLP is to read, decipher, understand, and make sense of human language in a way that is both valuable and meaningful.“
To better understand the significance of NLP, let’s explore some key areas where it plays a pivotal role.
The Significance of NLP
1. Communication Breakthroughs
NLP has been a catalyst for communication breakthroughs. With the help of machine translation systems, language is no longer a barrier. Google’s AI Blog highlights this aspect:
“NLP has brought about a new era of communication, breaking down language barriers, and enabling seamless global interactions. Translation tools like Google Translate leverage NLP to make information universally accessible.”
Imagine traveling to a foreign country and being able to understand and communicate effortlessly through your smartphone. NLP has made this possible.
2. Sentiment Analysis
Understanding human emotions and sentiments is critical in today’s data-driven world. NLP techniques like sentiment analysis are used to gauge public opinion, which is invaluable for businesses, governments, and organizations. Forrester Research emphasizes its importance:
“Sentiment analysis, powered by NLP, is a game-changer for businesses. It allows them to gauge public sentiment towards their products and services, helping them make data-driven decisions to improve customer satisfaction.”
3. Chatbots and Virtual Assistants
Have you ever chatted with a customer service representative online and realized you were actually talking to a chatbot? NLP is the magic behind these conversational agents. IBM’s Watson blog explains:
“Chatbots, powered by NLP, are enhancing customer support and service industries. They can understand and respond to user queries, providing instant solutions and improving the overall customer experience.”
This innovation has not only improved customer service but has also led to cost savings for businesses.
Apogee Suite of NLP and AI tools made by 1000ml has helped Small and Medium Businesses in several industries, large Enterprises and Government Ministries gain an understanding of the Intelligence that exists within their documents, contracts, and generally, any content.
Our toolset – Apogee, Zenith and Mensa work together to allow for:
- Any document, contract and/or content ingested and understood
- Document (Type) Classification
- Content Summarization
- Metadata (or text) Extraction
- Table (and embedded text) Extraction
- Conversational AI (chatbot)
Search, Javascript SDK and API
- Document Intelligence
- Intelligent Document Processing
- ERP NLP Data Augmentation
- Judicial Case Prediction Engine
- Digital Navigation AI
- No-configuration FAQ Bots
- and many more
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Check out our next webinar dates below to find out how 1000ml’s tool works with your organization’s systems to create opportunities for Robotic Process Automation (RPA) and automatic, self-learning data pipelines.
