GPT-3 has emerged as the most promising AI solution for transforming the learning experience. The content creation capabilities of GPT-3 have already created a lot of buzz among learners and educationists. Here we try to try to reveal its possibilities and promises.
While Artificial Intelligence (AI) continues to break new paths in every sector, in the world of education it is brought mainly through Natural Language Processing (NLP) models. Detecting common grammatical and syntactic errors, proofreading mechanisms, deciphering speech in natural language, and converting them to text are some of the common offerings of first-generation AI tools for education and learning environments.
But the recent over-pouring of interest in AI among learners, educators, institutions, and learning system developers can be traced back to one massive and path-breaking technology called GPT-3. Unlike other AI-based technologies that are more into pattern detection and garnering rich insights, GPT-3 is more into customized content creation. This is precisely why it is now at the center of all the buzzes in the education sector.
But still, most learners, teachers, course designers, and developers are not fully aware of GPT-3’s promises and capabilities in revolutionizing content creation for learners. This is why we feel it necessary to explain what GPT-3 brings to the table for learning communities. Let’s begin.
What exactly is GPT-3?
Third Generation Generative Pre-trained Transformer or GPT-3 is a neural network machine learning model based on neural networks that can create unique content based on precise inputs. Created by OpenAI, this open-source solution is capable of generating a huge volume of context-relevant text through machines.
The deep learning neural network that empowers GPT-3 trains the model with 175 billion different input parameters which is the largest volume of inputs compared to any comparable deep learning model in the market now. Thanks to this never-before size, depth, and extensive coverage of learning parameters, GPT-3 is more capable of delivering human-like text content that looks completely relevant and audience-specific.
What are the biggest promises of GPT-3 for the education sector?
Natural language processing (NLP) refers to a host of different data-driven models such as Natural Language Understanding (NLU), Natural Entity Recognition (NER), and Natural Language Generation (NLG). By involving all of these and particularly by using NLG GPT-3 generates text content in natural human language. This text content generated by GPT-3 can range from articles, reports, news items, blogs, poetry, dialogue scripts, and even programming language code.
For many content creators, this brings the freedom of creating the first draft of content easily that can further be improved with value additions by human collaborators. This brings down a huge load of copywriting for regular content creation tasks in the education sector.
To understand what GPT-3 brings to learners and educators it is important to have a basic understanding of the various Language Models (LM). The way you get predictive text inputs while you write emails or text on Google Docs is a basic output of language models. These models based upon the written or spoken word just predict and provide the next possible word, phrase, or even a full sentence.
This exceptional capability of machine models to deliver human language text can be useful for a variety of educational purposes such as extracting patterns, recognizing common entities in content, deciphering semantic insights, decoding complex text into comprehensible documents, classifying text, extracting sentiments, replying questions, generating text content such as articles, etc.
Since its release and its evolution up to the third-generation version, GPT has been at the center stage of numerous innovative NLP use cases such as intelligent conversational Chatbot and query engine, proofreading and text extraction, and several others. The latest version GPT-3 brings the ability to create any content having a text structure.
“Learn physics from Einstein” approach
“Learn physics from Einstein”, that’s the correct saying to describe GPT-3’s unique approach of using any renowned name in the world of science and other disciplines and getting precise answers to queries in a conversational manner. If you name Einstein, you can just start asking a GPT-3 bot about the Theory of Relativity and start getting quick and precise answers on the subject. Already we have an app powered by GPT-3 called Learn from anyone. That’s somewhat like giving the language model even a versatile and interactive personality for fulfilling the quest of the learners.
As a long-term impact, these prompt and precise answering capabilities can play a great role in training students with objective knowledge. This ultimately can make the tuition free of cost and less time-consuming. With this interactive education readily available through GPT-3 based bots and interfaces, there will be a ground-breaking shift in the way learners get access to content and learn from them.
Future Implications of GPT-3 are huge
After being trained with hundreds of billions of data-driven learning parameters, GPT-3 based solutions need far less training for particular domains compared to any other AI tools and language models. Since edtech applications and solutions focus on intelligent learning systems, GPT-3 will be a key component in the burgeoning online education sector.
GPT-3 has proved to be more viable and effective for primary and intermediate-level education. Particularly to impart basic knowledge and skills to young minds, GPT-3 bots can be more effective and useful. But the way this era-defining technology can now produce well-articulated text content across different genres, GPT-3 seems to be all capable as a tool to accompany higher education and even academic research.
If you think GPT-3 is only capable of imparting objective and informative knowledge and is likely to have limitations for creative content, there are still surprises for you. GPT-3 has been proven to be effective for highly creative and artistic content and there are instances of poetry written by GPT-3.
The future of content creation in the education sector is invariably linked to different AI capabilities, especially, language models. If human-machine collaboration for content creation is to dominate learning systems and future educational environments, GPT-3 has already paved the way in that direction. By the way, GPT-4 is already in the making and is going to be released soon. Get ready for the next round of surprises in content creation.
Originally posted 2022-09-13 18:09:56. Republished by Blog Post Promoter