Last updated on April 6th, 2023 at 05:06 am
ChatGPT is an artificial intelligence chatbot created by OpenAI and introduced in November 2022. It is created on OpenAI’s GPT-3 clan of huge language frameworks. It has been fine-tuned incorporating both reinforcement and supervised learning methods. It was initially launched as a Minimum Viable Product (MVP) on 30th November 2022 and rapidly gathered attention for its comprehensive answers and communicative responses across various domains of knowledge.
For this reason, we have gathered a list of reasons for the ways ChatGPT is improving software development.
It Helps To Make Coding Very Accessible
There are a lot of technological advancements in the history of computer science. This has allowed the majority of people to become developers. The main credit goes to the ways of abstraction. It has become very simple for the majority of people to leverage difficult technologies that were previously understood by expert engineers.
For example, high-level programming languages, in trail bikes with IDEs and compilers permit present-time engineers to scribble code without writing machine code. Similarly, the enhancement of artificial intelligence assists like Copilot is a good indication that we are progressing towards making coding a more enjoyable and accessible experience for everyone.
ChatGPT Can Also Serve As A Research Assistant
ChatGPT has been assessed on more than 45 terabytes of text data from different sources. This includes CSS, JavaScript, HTML, code in python, WebText2, and CommonCrawl.
This advantage can assist us in organizing our research for the latest and relevant knowledge when coding. Developers cannot know everything and some questions are guaranteed to come to mind every time. OpenAI Tan and ChatGPT reply to the questions. This can save a huge amount of time allocated on researching. ChatGPT should not be used to extract all your information. It is an outstanding way to attain an answer in a few seconds.
Decreasing Monotony with ChatGPT
If software development companies incorporate ChatGPT, it will make code bug-free and productive. It accommodates very difficult requirements. This in turn will help to eradicate grunt work and increase testing and productivity.
Due to this majority of the difficult tasks that have occupied the developers in the past could go away in the next ten years. This includes:
- Automation of the unit tests
- Producing test cases built on strictures
- Examining code to recommend security best techniques
- Automating Quality Assurance
Another main advantage is automating the ordinary task of developing documentation. ChatGPT assists the developers to create documentation for their code like technical and API documentation. This automation can save the developers from wasting time and effort that would otherwise be devoted to manually making important documentation.
Incorporating ChatGPT for Natural Language Processing
NLP is a sub-category of machine learning that incorporates software to operate and generate natural languages. This includes that text that gives the impression when you ask ChatGPt a query or the talk you hear from an AI bot like Siri or Alexa. Things such as automatic text generation, speech recognition, text analysis, and translating between languages everything come under the category of NLP.
Here are a few ways through which ChatGPT assists developers with NLP.
- Sentence Parsing: ChatGPT can analyze natural language inputs and take out the requested information like actions and entities. This information is incorporated to pinpoint the required information.
- Text Classification: Classifying natural language inputs into pre-defined constraints, and non-functional and functional requirements.
- Summarization: Summarizing natural language inputs into a very actionable and concise form to assist the developers to comprehend the main requirements.
- Dialogue-based: Developers ask questions to collect more clarification on the needs.
It is extremely beneficial for software development companies to incorporate ChatGPT. It uses natural language processing techniques to assist the developers to see the requirements articulated in natural language. They can convert this information into actionable requirements for development.