Exciting New Trends In Natural Language Processing
Natural language processing engineering is a fast-growing and lucrative career path, with an average salary of $138,394 per year. In particular, natural language processing is an exciting branch of computer science that essentially helps computers understand human language; it's already used in a host of technologies used everyday like Apple's Siri, Amazon's Alexa, chatbots, and translators. And, as unstructured data only continues to grow, natural language processing technology is also transforming in order to get a better handle on the endless nuances and complexities of human language.
Exciting New Trends In Natural Language Processing
- The rise of ChatGPT
- Sentiment analysis
- Named-entity recognition
The rise of ChatGPT
Last year, OpenAI launched ChatGPT – a powerful chatbot and real "milestone in the field of natural language processing". ChatGPT uses deep learning methods to generate text responses that are accurate, in-depth, and grammatically-correct – to such an extent that was considered impossible only a few short years ago. As such, ChatGPT is transforming how humans communicate with machines, and making it much easier for us to do so naturally.
It's therefore not surprising a number of researchers are already attempting to replicate this impressive model. For example, Stability AI recently launched StableLM, an open-source chatbot that learns through reinforced learning from human feedback (RHLF). It's an alternative to ChatGPT that aims to make AI technology more transparent and accessible to all.
Sentiment analysis
Sentiment analysis (also known as opinion mining) is a natural language processing technique used to determine the emotional tone or sentiment of text. Sentiment analysis is a valuable way of monitoring market research, social media, brand reputation, and product analysis, in particular. TextBlob, for example, is a Python library used to perform a host of natural language processing tasks, including, sentiment analysis. This tool returns both polarity and subjectivity scores to indicate whether text is positive, negative, or neutral.
Additionally, TextBlob can also be used to perform complex analysis on textual data. Complex analysis is a powerful mathematical tool that "studies analytical properties of functions of complex variables". By taking the time to learn Complex Analysis from experts, you'll be rewarded with the key skills needed to progress in your STEM career.
Named-entity recognition
Named-entity recognition is another natural language processing method that identifies, categorizes, and extracts key information from text. For example, it's used to identify information like names, brands, and businesses, as well as times, dates, and numerical measurements. So, for example, HyperGlue, a San Francisco-based natural language analytics company, recently launched software designed to transform unstructured text into actionable insights in as little time as possible.
The software employs a host of natural language processing methods, including named-entity recognition, sentiment analysis, and topic clustering. As a result, businesses are easily able to benefit from AI powered metrics and reports, discover any anomalies in customer data, detect nascent themes, and monitor emerging key trends.
The world of natural language processing is continually evolving. ChatGPT, sentiment analysis, and named-entity recognition are just some of the latest trends helping build smart natural language processing systems.
