GPT-3 and Everything You Need to Know About It!
What even is GPT-3?
GPT-3 is a relatively new concept in Artificial Intelligence. It is a natural language processing model, machine learning platform that uses deep learning to produce human-like text. Also, it enables developers to train and deploy AI models and is said to be scalable and efficient with the ability to handle large amounts of information and data. It is the successor to the widely-used GPT-2 model.
The deep convolution neural network in GPT-3 is a machine learning model with 175 billion parameters. To put things in context, until GPT-3, the largest trained language model was Microsoft’s Turing NLG model, which contained 10 billion parameters. As of early 2021, GPT-3 is the world’s largest neural network. As a result, GPT-3 exceeds any previous model when it comes to producing text that appears to be written by a human.
Where did GPT-3 come from?
GPT-3 was created by OpenAI, a company based in San Francisco dedicated solely to the creation of artificial general intelligence devices or systems that are fit for humans; the beta version was released in June 2020, so it hasn’t been out for long. The platform is based on the Transformer, a deep learning model that is capable of learning from large amounts of data. The Transformer was originally developed by Google Brain and is the basis for the popular BERT.
Why is GPT-3 so important for the future of technology?
We’re seeing a shift in how we input data into computers, as well as how they respond to our commands and what they can do with them. When computers were first introduced, we used punch cards to input data. After that, there were computer keyboards and a screen for input and response, followed by a mouse with a drag-and-drop interface. Then came touch screens and technology like Alexa, which could recognise simple sentences and offer a mix of spoken words — very basic spoken words — that would appear on our touch screens.
The next logical step is natural text recognition and response, which will allow us to have considerably more conversational interactions with computers by taking data and patterns from the internet and applying them to our own voice.
Imagine being able to tell your computer exactly what you want in your report, how you want it to sound, and what sorts of graphs you want to see.
The computer could construct the report for you in a matter of seconds since it recognises the patterns you’re referring to, as well as the data and the most efficient ways to collect and display it. With this technology, you’ll be able to say things like, “That’s not quite right; I need that to be more like this, and this to be more like that.” It can assist you in refining and producing the entire procedure. This is a brand-new way of interacting with computers. It’s a developed form of the back-and-forth concept, integrating a model response with a progressive description of models.
Proposals, sales, documents, academic papers, and even books become more enticing when we consider the process in this light. We’re not removing the human soul from the process; rather, we’re dramatically speeding it up by utilising all of the resources at our disposal, which we already use; this simply adds to what we already have. We normally go online to study what we need for an academic paper and then consolidate our results. We then write it down in our own words, which is exactly what GPT-3 excels at doing in a fraction of the time.
Why am I so interested in GPT-3?
Personally, I think the idea of being able to do so much with so little is such an amazing concept, no matter what context you put it into. I really believe that so much could be done with this piece of technology in the future and it could go really far. So much could come out of it, and we really don’t know what will happen with it as it is too early on to confirm anything.
Thank you so much for reading my article, I hope you enjoyed learning more about this amazing creation GPT-3.
By: Riona Rajeev
Published: 12th June 2022