A 2022 Retrospective on NLP

The NLP industry has grown in 2022, let’s take time, reflect and have a look back to a 2022 Retrospective on NLP.


Here’s a look at how NLP has evolved in 2022, including some of the more exciting things to happen in the industry. A worthy time to have a 2022 Retrospective on NLP.

The Growth of GPT3

Generative Pretrained Transformer 3 or GPT3 has become increasingly popular in 2022. This system from OpenAI uses deep learning to create text based on the prompts it receives.

GPT3 has seen updates in 2022 that have helped make it more effective:

• Users can edit or insert content into existing reports, creating a more practical system for analyzing content.

• Generated content is being compared with current work to prevent plagiarism from being a threat. GPT3-based NLP systems can review synonyms and other words of parsing content to create unique data

• GPT3 has evolved to include increased accessibility to new data. GPT3 systems can review regular data repositories and add whatever new data appears.

What Applications Are Out There Today?

OpenAI has produced many intriguing applications with the GPT3 system. These include many outstanding systems:

• MessageBird helps authenticate company messages while displaying them when customers request them. The system ensures all data stays secure while messages are easy to deliver.

• CopyAI can automate marketing content based on prior marketing data. CopyAI can work for various ad copy formats, including for social media and blog posts.

• Jasper is another AI-powered copywriting system that uses GPT3. This system can produce digital marketing images, bullet points, and other segmented content that makes data easier to read.

• Anyword uses multiple modules for producing written content. Users can create target audience definitions that Anyword will use to produce content easier for those audiences to review. Separate modules for helping acquire and convert leads are also available.

• Debuild.io uses AI to review input data and create new web apps. The system is in its early stages and will require more specific or detailed content to create more effective and useful apps for all purposes.

The Introduction of ChatGPT

While OpenAI will release GPT4 at some point, OpenAI did release ChatGPT in 2022. This system is an improved version of GPT3, as it works as a chatbot that can handle back-and-forth communications with others.

ChatGPT uses billions of news articles, social media posts, and Wikipedia articles to analyze sentence and word relationships, helping create an idea of how communications can work.

The conversational layout of ChatGPT allows an AI system to sound more human. The AI can ask and answer follow-up questions, plus it can reject inappropriate statements or offer corrections when someone provides incorrect input. The AI can even acknowledge any mistakes or errors it comes across, although programmer input and recording may be necessary to prevent these errors from being problematic.

The AI can ask and answer follow-up questions, plus it can reject inappropriate statements or offer corrections when someone provides incorrect input.

How InstructGPT Helps ChatGPT

Not all pieces of online content are suitable for OpenAI, which is where the InstructGPT system comes in handy. InstructGPT is an extension of GPT3 and ChatGPT that prevents misinformation and toxic content from being a threat.

InstructGPT uses a reward model that analyzes the accuracy of a statement while avoiding content that may appear heavily biased or written with malicious intent. The system avoids content that might be hostile or inaccurate and focuses on more authoritative content written with certainty and without emotions getting in the way of the content.

How Cloud Systems Are Using NLP Today

Today’s cloud systems are becoming more reliant on NLP to make their projects easier to manage.


The Amazon Comprehend system has become more influential for AWS in 2022. Comprehend is an NLP-based system that extracts text and phrases from documents and inputs. The program analyzes the content to review its meaning and then reviews which actions are more likely to lead to positive outcomes.

Comprehend is ideal for call center analytics, as it helps a program automate support requests and produce more accurate responses. It’s also easier for people to find important details and insights in financial and legal documents through Comprehend.


Google’s Cloud system received an update in 2022 that helps Google accurately classify content. Google Cloud uses a large language model system that collects hundreds of content labels in multiple languages and sorts words over how they can hold different meanings surrounding the context.

Google Cloud’s NLP system now analyzes the definition of a word, the context of that word, and its positioning in a sentence or statement. The work produces more detailed connotations that can review something of value to individual parties.


Microsoft Azure also uses NLP to review content, and 2022 saw Azure evolve to include more features. Azure’s NLP setup can check named entities and other proper names and review how they appear alongside other critical words. Text can also be classified in multiple fields based on the context used and what purpose someone has for searching for content.

The AI can even acknowledge any mistakes or errors it comes across, although programmer input and recording may be necessary to prevent these errors from being problematic.
  • Exciting New NLP Startups In 2022

The last point to explore surrounding NLP in 2022 involves the many startups that have popped up in the past year. Here are a few of the more appealing startups that have been growing in 2022 and will make a positive impact in 2023 and beyond:

  • Deep Discovery reviews data pools and calculates connections based on what it finds. Data visualization is an important part of the Deep Discovery system, as it makes it easier for people to review what content is available online.
  • Biologit is a search automation system focusing on the science and medicine industries. The setup helps people find content through various scientific reports, improving how well content can appear.
  • Vernai is a sentiment analysis NLP platform that checks how people feel when interacting with a platform. Vernai reviews how often people post messages, the words they use, and the similarities between multiple inputs someone puts in at a time.
  • Mendel is an electronic medical record analysis program that checks medical data and ensures a data store remains compliant. The work helps reduce data loss while making it easier for professionals to find medical content as necessary.

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