Natural language processing (NLP) and deep learning are two powerful components of AI that simplify data processing and make data more readily accessible. NLP focuses on simplified communication between humans and computers in real-time, making computational power more accessible for practical business purposes. Deep learning is a machine learning specialization that enables machines to learn from large datasets using artificial neural networks (ANNs) and identify relevant patterns for informed decision-making.
While AI is the first phase in developing the machine’s ability for problem-solving, machine learning (ML) is the next phase in evolution whereby machines learn by themselves. With ML, machines learn from data and provide predictions based on the data. Deep learning is the newest phase in the evolution of machine technology and involves computers processing patterns that mimic how the human brain processes information.
NLP combines computer science, AI, and linguistics as the machines must understand human linguistics like pragmatics (conversational), semantics (meanings and vocabulary), morphology (word structure), and syntax (sentence structure). NLP uses machine learning and AI to comprehend human language, make sense of the unstructured content, and give meaning to words.
Deep learning across industries
Below are a few examples of industries revolutionized by deep learning applications.
The energy sector fluctuates regularly and is expansive. With a growing population, the demand for energy and electricity is also increasing. Based on the current user consumption data, the energy sector can use technology powered by deep learning capabilities to adjust production and meet the increasing demand. Deep learning-powered predictive analytics and infrared technology make the complex tasks of maintenance and monitoring easier.
Deep learning is the driving force behind bringing self-driving cars to life. Data gathered from cameras, geo-mapping, and sensors are helping in creating sophisticated models that help in navigating through traffic, identifying signages, paths, pedestrians, real-time elements like monitoring traffic volumes, road blockages, etc. Advancements in deep learning are allowing autonomous cars to navigate without any 3-D mappings in prime locations.
Deep learning’s capabilities to discover hidden opportunities in data allow the healthcare sector to diagnose and treat diseases more effectively. As deep learning involves analyzing trends, patterns, and behaviors from the data gathered from medical images and reports, it uses predictive diagnostics to identify timely treatments, which will help save lives. Furthermore, deep learning helps with new drug discovery, new efficiencies, and possibilities that empower physicians, clinicians, and researchers in finding a cure to untreatable diseases.
Each transaction and moment of customer engagement from in-store and online retail outlets generates data, and deep learning algorithms learn about customer preferences and purchasing patterns from such data to offer them personalized products and services. Thus, deep learning helps make the products and services stand out to customers. When combined with NLP techniques, deep learning models power virtual and digital assistants who learn more about the customers by interacting with them in a human-like manner by learning the language and accent. These assistants learn to understand the commands given by evaluating natural human language and executing them.
Deep learning technology drives modern manufacturing, including predictive maintenance. Identifying when to service and fix machinery before breakdown saves production cycle time, money, and energy. This technology-driven industry also uses deep learning to forecast sales and advanced analytics to understand and monitor supply and demand levels and make informed production decisions.
Applications of NLP in various businesses
NLP is an integral part of modern business infrastructure, as discussed below.
Finance and commerce widely depend on NLP-powered sentiment analysis to identify opinions and emotions through written or verbal language clues. Through these clues, accurate predictions are devised for stock market movements and price fluctuations. NLP with AI and machine learning analyzes data gathered from the internet, social media, news, blogs, and other channels to predict trade fluctuations and help investors to make the right decisions at the right time. NLP also filters emails, identifies spam, enhances security through voice recognition, improves customer service via virtual/digital assistants, promotes business intelligence, offers personalized products and services, analyzes customer behavior based on feedback, ratings, reviews, etc.
As NLP analyzes data and text, it enhances teaching by focusing on reading, writing, and speaking. Along with proofreading, detecting errors in machine translation, and assessing students’ work, NLP-powered chatbots can be integrated with gaming technologies to promote active e-learning environments, foster student engagement by motivating them by using innovative media features, provide accurate real-time information to learners, and much more. NLP effectively helps in research, processes qualitative data, converts audio translations from one language to another, and assists in data analysis.
Like manufacturing, healthcare is another industry that is fast-growing and technology-driven, thereby overcoming regional disadvantages like accessing healthcare services in rural areas through eHealth. The data generated from EHRs, sensors, diagnosis and monitoring, healthcare operations, and management is vast. NLP parses through this data to extract critical strings and generate meaningful insights that offer an opportunity to leverage unstructured data. NLP handles the surge in clinical data, improves clinical documentation, enhances patient and healthcare provider interactions, reduces physician burnouts, and deals with increasing amounts of healthcare claims.
Both, NLP and deep learning are an integral part of a larger field of study, which is AI. While NLP redefines how machines understand human language and behavior, deep learning is further enriching NLP applications with more accurate insights without reliance on human intervention. There is tremendous potential for NLP and deep learning and we have just started to scratch the surface.
If you are interested in learning more about how deep learning and NLP can help you with your business, send an email to firstname.lastname@example.org. Intellect Data, Inc. is a software solutions company incorporating data science and artificial intelligence into modern digital products with Intellect2TM. IntellectDataTM develops and implements software, software components, and software as a service (SaaS) for enterprise, desktop, web, mobile, cloud, IoT, wearables, and AR/VR environments. Locate us on the web at www.intellectdata.com.