Have you ever had a thought or wished that all you had to do was write two lines of an essay or a diary and the computer would do the rest? If your answer is yes, GPT-3 is the solution for you. Are you perplexed? People who got their hands on GPT-3 feel the same.
Every discipline of AI is progressing. Natural Language Processing(NLP) and Deep Learning are two such fields in the realm of AI that are advancing rapidly.A recently created technology known as GPT-3 has created a lot of buzz and enthusiasm in the Artificial Intelligence (AI) sector. Simply put, it’s an AI that’s better than anything else- whether it’s human or machine language, at creating content with a language structure.
What is GPT-3 ?
GPT-3 (Generative Pre-trained Transformer 3), is an Autoregressive (AR) Language model — which, given a context, predicts the future word from a set of words. It is developed by OpenAI, an artificial intelligence research laboratory in San Francisco. It is the third generation of such language models developed by them and uses Deep-learning to produce human-like texts. The distinguishing factor between GPT-3 and earlier variants is its size. GPT-3, with 175 billion parameters is 17 times larger than GPT-2 ( which had 1.5 billion parameters) and nearly 10 times larger than Microsoft’s Turing NLG model.
How does GPT-3 work ?
In terms of broad areas of AI Applications, GPT-3 is a language prediction model . It’s an algorithmic framework that takes one piece of language (an input) and converts it into what it thinks will be the most beneficial piece of language for the user. GPT-3 can accomplish this , because unlike other algorithms that have not been trained, a large body of texts have been used to “pre-train” it.
GPT-3 is essentially a transformer model. Transformer models are deep learning , sequence-to-sequence models that can generate a text sequence from an input sequence. These models are intended for activities such as question answering, text summarization, and machine translation that require text production.
It is also a form of Unsupervised learning wherein the training data does not include any information on what constitutes a “correct” or “wrong” answer. The training texts provide it with all of the data it requires to determine the probability that its output will meet the user’s demands. It examines all of the material in its training data –billions of words grouped into understandable language — to figure out which word to use to reconstruct the original sentence when any input is given by the user.
How was it trained?
GPT-3 was trained to create text in English and numerous other languages using this dataset containing billions of words. The training was carried out using a blend of the following big text datasets, as described in the original publication that presented this model:
- Common Crawl
- Wikipedia Corpus
The final dataset included a significant portion of the internet’s web pages, a massive collection of books, and the entire of Wikipedia.
Why is it so Powerful ?
GPT-3 has gained attention for its ability to execute a wide range of natural language tasks and create human-like content. It can summarise emails, create tweets, produce poetry, answer trivia, and translate languages, among other things. It may perform a variety of activities, including but not limited to:
- Answering a question
- Development of text
- Classification of text (ie. sentiment analysis)
- Summarization of the text
- Recognition of named entities
- Translation of languages
All of this is accomplished with very little manual assistance or guidance.We may think of GPT-3 as a model that can execute reading comprehension and writing activities at a near-human level, except that it has seen more text than any person would ever read in their lifetime. It has also been termed the “biggest Artificial neural network ever developed” by others.
How can you use GPT-3 ?
GPT-3 is currently not open-source, thus OpenAI opted to make the model available via a commercial API, which you can access here. Because this API is still in private beta, you’ll need to fill out the OpenAI API Waitlist Form to get on the list to access it. Academic researchers who wish to employ GPT-3 can use OpenAI’s special service. Fill out the Academic Access Application if you wish to utilise GPT-3 for academic study.
You’re not alone if you’re astonished by GPT-3’s abilities. We’re all like that, and the hype reflects that. This will have a profound impact on every business and pave the path for future generations of AI products, such as GPT-4 or GPT-5. Artificial intelligence is a fast-paced technology. If anything, its rapid speed is just becoming faster. The CEO of OpenAI , Sam Altman, has himself said, “The GPT-3 Hype is too much. AI is going to change the world, but GPT-3 is just a glimpse. “The area of artificial intelligence will appear quite different in five years than it does now. Approaches that are now regarded cutting-edge will be obsolete, whereas technologies that are currently regarded nascent or on the edges will become mainstream. In fact, a GPT-3 might have authored the entire blog.