What is NLU Natural Language Understanding?

In this project-oriented course you will develop systems and algorithms for robust machine understanding of human language. The course draws on theoretical concepts from linguistics, natural language processing, and machine learning. Learn how to extract and classify text from unstructured data with MonkeyLearn’s no-code, low-code text analysis tools. With natural language processing and machine learning working behind the scenes, all you need to focus on is using the tools and helping them to improve their natural language understanding. Many machines have trouble understanding the subtleties of human language.

Customer support agents can spend hours manually routing incoming support tickets to the right agent or team, and giving each ticket a topic tag. This drives up handling times and leaves human agents with less nlu in ai capacity to work on more complex cases. But with advances in NLU, virtual agents are able to do this job automatically. Interactive Voice Response (IVR) systems have become ubiquitous in customer service.

NLP; NLU and NLG Conversational Process Automation Chatbots explained

NLU is an evolving and changing field, and its considered one of the hard problems of AI. Various techniques and tools are being developed to give machines an understanding of human language. A lexicon for the language is required, as is some type of text parser and grammar rules to guide the creation of text representations. The system also requires a theory of semantics to enable comprehension of the representations.

Organizations need artificial intelligence solutions that can process and understand large (or small) volumes of language data quickly and accurately. These solutions should be attuned to different contexts and be able to scale along with your organization. Machines may be able to read information, but comprehending it is another story. For example, “moving” can mean physically moving objects or something emotionally resonant. Additionally, some AI struggles with filtering through inconsequential words to find relevant information.

Natural Language Understanding (NLU): Revolutionizing AI’s Understanding of Human Language

Request a demo and begin your natural language understanding journey in AI. Try out no-code text analysis tools like MonkeyLearn to  automatically tag your customer service tickets. Natural language understanding can help speed up the document review process while ensuring accuracy.

NLU integration enhances these systems, enabling more sophisticated and context-aware interactions. Customers can articulate their needs naturally, and the IVR can accurately route calls or address queries without frustrating and repetitive menu navigation. AI technology has become fundamental in business, whether you realize it or not.

When deployed properly, AI-based technology like NLU can dramatically improve business performance. Sixty-three percent of companies report that AI has helped them increase revenue. Functions like sales and marketing, product and service development, and supply-chain management are the most common beneficiaries of this technology.

However, NLG technology makes it possible for computers to produce humanlike text that emulates human writers. This process starts by identifying a document’s main topic and then leverages NLP to figure out how the document should be written in the user’s native language. Natural Language Understanding (NLU) connects with human communication’s deeper meanings and purposes, such as feelings, objectives, or motivation. It employs AI technology and algorithms, supported by massive data stores, to interpret human language. Intent recognition and sentiment analysis are the main outcomes of the NLU.