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NLP vs NLU: Whats The Difference? BMC Software Blogs

What is Natural Language Understanding NLU?

nlp nlu

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. NLG is another subcategory of NLP that constructs sentences based on a given semantic. After NLU converts data into a structured set, natural language generation takes over to turn this structured data into a written narrative to make it universally understandable. NLG’s core function is to explain structured data in meaningful sentences humans can understand.NLG systems try to find out how computers can communicate what they know in the best way possible.

This enables machines to produce more accurate and appropriate responses during interactions. While natural language processing (NLP), natural language understanding (NLU), and natural language generation (NLG) are all related topics, they are distinct ones. Given how they intersect, they are commonly confused within conversation, but in this post, we’ll define each term individually and summarize their differences to clarify any ambiguities. In AI, two main branches play a vital role in enabling machines to understand human languages and perform the necessary functions.

What NLP does

You can see more reputable companies and media that referenced AIMultiple. Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem’s work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

nlp nlu

So the system must first learn what it should say and then determine how it should say it. An NLU system can typically start with an arbitrary piece of text, but an NLG system begins with a well-controlled, detailed picture of the world. If you give an idea to an NLG system, the system synthesizes and transforms that idea into a sentence. It uses a combinatorial process of analytic output and contextualized outputs to complete these tasks.

Top Large Language Model Examples in 2024

They are so advanced and innovative that they appear as if a real human being has written them. Natural Language Processing(NLP) is a subset of Artificial intelligence which involves communication between a human and a machine using a natural language than a coded or byte language. It provides the ability to give instructions to machines in a more easy and efficient manner. NLU can also be used in sentiment analysis (understanding the emotions of disgust, anger, and sadness). NLP can be used for information extraction, it is used by many big companies for extracting particular keywords.

nlp nlu

He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School. Before booking a hotel, customers want to learn more about the potential accommodations. People start asking questions about the pool, dinner service, towels, and other things as a result. Such tasks can be automated by an NLP-driven hospitality chatbot (see Figure 7). However, NLU lets computers understand “emotions” and “real meanings” of the sentences.

Future of NLP

Using NLU technology, you can sort unstructured data (email, social media, live chat, etc.) by topic, sentiment, and urgency (among others). These tickets can then be routed directly to the relevant agent and prioritized. Natural language understanding (NLU) is a subfield of natural language processing (NLP), which involves transforming human language into a machine-readable format. When it comes to natural language, what was written or spoken may not be what was meant. In the most basic terms, NLP looks at what was said, and NLU looks at what was meant. People can say identical things in numerous ways, and they may make mistakes when writing or speaking.

And if we decide to code rules for each and every combination of words in any natural language to help a machine understand, then things will get very complicated very quickly. While NLP will process the query NLU will decipher the meaning of the query. NLU will use techniques like sentiment analysis and sarcasm detection to understand the meaning of the sentence. It will nlp nlu show the query based on its understanding of the main intent of the sentence. NLU’s core functions are understanding unstructured data and converting text into a structured data set which a machine can more easily consume. Applications vary from relatively simple tasks like short commands for robots to MT, question-answering, news-gathering, and voice activation.

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