ChatGPT: How It Actually Works (A Guide for Non-Technical People)?
ChatGPT (Chat Generative Pre-Trained Transformer) is the next big thing in AI technology. Its debut on November 30, 2022 has drawn a great attention worldwide due to its capability to produce high-quality responses to human input.
Surprisingly, by December 4, 2022, it crossed one million users. Indeed, a big milestone for OpenAI! This can be attributed to its power of creating human-like text to all sorts of questions. It is much more advanced than other chatbots developed in the past.
The good part is that ChatGPT has been designed to perform a plethora of tasks such as writing code, content creation and translation, and many more. It is highly versatile, reliable, and efficient to propel your business to greater heights.
If you’re from a non-technical background and want to understand ChatGPT at its core in the simplest way possible, you’re on the right track. This post by IDS Logic is created to help you learn how ChatGPT works, so you can get the best out of this tool.
Without any further ado, let’s begin!
ChatGPT is Laid on the Foundation of Transformer Architecture
ChatGPT is transformer-based, which is a form of neural network that has been trained to understand the sequence of data like a text or a speech. It can create texts that are more humanly and relevant to the context using attention and self-attention mechanisms.
Its main components are encoder and decoder that analyze and comprehends the input and generates output in relevance to input respectively.
In easy words, ChatGPT is trained to interact in a conversational way and maintains relevancy in a conversation through accurate responses.
Role of NLP (Natural Language Processing) in ChatGPT
ChatGPT has pushed natural language processing to a new level by generating machine text that gives a human feel. Within NLP, an input undergoes following stages:
Preprocessing- sentence segmentation, tokenization (splitting text into small pieces), stemming (deleting suffixes and prefixes) are done to clean the text
Encoding- text conversion into a vector of numbers for model processing
Model Processing- the encoded input is passed to the model for processing
Fetching Result- gives result of potential words presented in vectors of numbers using the model.
Decoding– translating vectors in real words
Post-processing- refining output by spell checking, grammar checking, punctuation, and many more.
After passing through these stages, a meaningful and coherent output is generated!
Different Iterations of ChatGPT
GPT- As a generative model, it generates relevant output for the input provided. Its decoders can easily guess the next token in the sequence and processes it continuously using the past results to produce long sentences.
GPT2- It is an iteration of GPT that has 1.5B parameters along with corpus. It has been trained to handle a range of language-related tasks with ease.
GPT3- It comes with 175 billion parameters with huge number of words from the web and Wikipedia. It is considered as the dynamic version of ChatGPT that has self-attention layers to do multitasking and create an authentic response in real-time.
To ensure that GPT3 understands the human intent effectively, it has been fine-tuned using supervised learning and RLHF (Reinforcement Learning from Human Feedback), leading to the development of InstructGPT and ChatGPT.
Working of ChatGPT
Earlier, it’s quite challenging to create a conversational AI system that produces responses in context to the conversation. This is the biggest problem with traditional language models.
But, the inception of ChatGPT has solved this problem as it generates a response that maintains relevancy and coherency due to its training and fine-tuning. It uses a big set of data (conversational text) to understand the patterns and create responses in a meaningful way.
One more thing that conversational AI system struggles with its ability to maintain conversational flow and creating natural and different responses. Thanks to ChatGPT, this thing has been addressed too. Its deep learning techniques are extremely useful in generating varied responses that give a human touch.
Conclusion
There are very few tech innovations that have increased much interest on the internet. ChatGPT is amongst them. It comes with several capabilities, including text generation, summarization, translation, question-answering, and a lot more. It creates text that is in-line with the previous conversation and makes sense. Adding this AI-powered tool can boost business efficiency to a great extent.
If you’re interested in learning more about ChatGPT and where it’s heading, you should stay tuned to IDS Logic blog. We can provide you valuable insights on this tool to utilize its potential to the fullest.