What is NLP? To a person without a machine learning or data science background, it might be hard to grasp how important it is. To give you a better sense of what NLP can do, let’s take a look at how you are using NLP daily and what you can do with it in the near future.
Natural Language Processing, commonly referred to as NLP, is a field of artificial intelligence (AI) that focuses on enabling machines to understand, interpret, and respond to human language in a way that is both meaningful and contextually relevant. In simpler terms, NLP empowers computers to comprehend and interact with human language as if they were fluent speakers.
NLP involves a range of tasks, including text analysis, language generation, and language translation. The ultimate goal is to bridge the gap between human communication and computer understanding, allowing for seamless interaction and enhanced user experience. NLP is not an abstract concept limited to tech labs; it is deeply embedded in our daily lives. Examples include:
- Search Engines: When you type a query into a search engine, NLP algorithms analyze your input to provide relevant search results.
- Virtual Assistants: Voice-activated virtual assistants, like Siri or Alexa, use NLP to comprehend and respond to spoken commands.
- Language Translation: Apps like Google Translate utilize NLP to translate text from one language to another while maintaining context.
- Email Filtering: NLP helps in spam detection by analyzing the language patterns in emails to distinguish between legitimate and unwanted messages.
The hype of AI is that in the next two to three years, even small businesses can utilize what the big techs are currently doing. To give you a better sense of what you can achieve, let's take a closer look at how the big techs are using it right now.
Google leads in effectively monetizing NLP, seamlessly integrating it across various products to improve user experience. In Google Search, NLP algorithms analyze queries, yielding precise results. The 18 SERP features showcase Google's adept understanding of user intent. The company's significant impact on the digital landscape led to the creation of specialized marketing roles, such as SEO and SEM, to navigate and optimize for Google's system.
Amazon
Amazon employs Natural Language Processing (NLP) in eCommerce through its recommendation system, a powerful tool for personalization. NLP algorithms analyze user activity, product details, and user metadata to provide personalized product recommendations. Amazon's recommendation types include "Recommended for you," "Related Products," and suggestions based on previous purchases, enhancing user engagement and driving over 35% of sales according to McKinsey. The company's AI-based recommendation system relies on machine learning algorithms, specifically utilizing Amazon Personalize, a fully managed machine learning service available on AWS. This service processes user platform activity and metadata to deliver accurate and personalized product suggestions, contributing to increased conversions and customer satisfaction.
Facebook employs NLP to enhance user engagement and content understanding on its platform. NLP algorithms analyze the language used in posts, comments, and messages to improve content recommendation systems and target advertisements more effectively. Moreover, NLP plays a crucial role in sentiment analysis, helping Facebook understand the emotional tone of user interactions. Chatbots on the platform also utilize NLP to provide automated and context-aware responses in real-time.
Apple
Apple integrates NLP into its ecosystem, primarily through Siri, the voice-activated virtual assistant. Siri uses NLP to interpret and respond to spoken commands, allowing users to perform various tasks hands-free. Whether it's setting reminders, sending messages, or answering questions, Siri's NLP capabilities contribute to a more natural and intuitive user interface. Additionally, NLP is employed in Apple's keyboard suggestions, enhancing the accuracy and relevance of auto-corrections and predictions. By leveraging NLP, Apple enhances the overall user experience across its devices and applications.
Salesforce
Salesforce leverages NLP through its AI-powered platform, Einstein. Einstein uses NLP to analyze and understand unstructured data, such as emails, social media interactions, and customer feedback. This enables businesses to gain valuable insights into customer sentiments, preferences, and trends. NLP also plays a crucial role in chatbots integrated into Salesforce, providing more interactive and personalized customer interactions. By incorporating NLP into its CRM solutions, Salesforce empowers businesses to make data-driven decisions, enhance customer relationships, and streamline various aspects of their operations.
