Natural language processing trendsTech companies are expecting more advanced natural language processing trends in the coming year.

Throughout 2021, we have encountered tremendous growth in the natural language processing space. Since we have come to the end of the year, it is time to invite new innovations and developments across the artificial intelligence sphere. Technology has brought many disruptions to every ecosystem. Today, organizations across many industry verticals are using artificial intelligence to streamline routine processes and provide better customer service. On the other hand, data processing is spearheading to be the core of every business decision. While small to large organizations embrace evolving technologies like NLP, they get more opportunities to explore futuristic business solutions and data pipelines. Besides, amazing natural language processing tools including GPAT-3 and Microsoft’s Turning-NLG are rocking the artificial intelligence sphere. In 2022, tech companies are expecting even more advanced natural language processing trends. IndustryWired has listed the top natural language processing trends and predictions to look out for in 2022.

Top Natural Language Processing Trends in 2022

 

Moderating Socia Media Content using NLP

Social media is now the core of every business transformation. Many organizations and famous brands are keeping a tab on social media platforms to know what people think about them. They also use social media to identify and address customers’ concerns. However, manually going through comments and messages are impossible as big brands bear huge responsibilities. Therefore, they automate the process with the help of NLP. Natural language processing help companies channel comments and content into three categories namely positive, neutral, and negative. This helps the organizations to take effective actions at a faster pace.

Shifting from Low-Code to No-Code NLP

Over the past few years, the tech sphere has come to a realization that even a non-tech employee can deal with tech-related applications and tools. The shift from technical workers to domain experts has put the ability to code in the hands of business leaders. Although low-code is performing well in the market, a new trend in no-code is expected to take over in 2022 and beyond. According to that, NLP will be democratized with the shift, and anybody can deal with the disruptive technology.

Bringing Multimodel Learning into Play

Natural language processing is a standalone technology that has been doing good so far. However, the expectations in the analysis have increased and NLP is having a hard time handling them all. Since NLP can only sort text data, it needs a support system that could help analyze all kinds of data. Fortunately, multimodal learning is coming into play. Multimodal learning can help stand alongside NLP and help companies find insights from visual content, reports, contracts, and other scanned documents.

Transfer Learning is Still on the Play

Although NLP is an amazing technology, it takes a lot of effort and money to implement it on full swing. Therefore, companies have been using transfer learning techniques to minimize cost, save time, and build solutions from existing content. Transfer learning is a machine learning division where a model is trained for one task and repurposed for a second task that’s related to the main task. Currently, NLP works like intent classification, sentiment analysis, and named entity recognition are using transfer learning at its core.

Multilingual Offering will Gain Traction

In the initial years of NLP development, services were available only in English and Mandarin. But as the technology evolved and people realized the advancements of NLP, we are seeing more languages getting added to the mechanism. Multilingual models are also introduced to data scientists globally while cloud providers can offer natural language processing support in over 100 languages.