What is GPT? Ahead of GPT-4, know all about this AI-based content generation model

Artificial intelligence or AI has been one of the most fascinating aspects of technology in the 21st century. AI began in myths and science fiction novels and today, it is used everywhere from a smartphone to advanced robotics. Put in simple terms, AI is a simulation of human intelligence in a mechanized form. So any machine or software that is capable of simulating “thought” can be considered an AI. Some common examples include maps and navigation systems and voice assistants in smartphones as well as self-driving cars. But the application of AI is constantly increasing in today’s world. AI is now fully capable of generating sensible content without any manual input. Yes, we are talking about Generative Pre-trained Transformer (GPT). As rumors around the development of GPT-4, the fourth iteration of the software, rises to fever pitch, we take a look at what this intriguing piece of technology is all about. 

What is GPT? 

Language processing and conversations have always been considered a big leap for AI. An AI which can, not only understand when you say something to them, but also reply in a meaningful way has been a challenge that data scientists have been trying to solve for decades. Natural Language Processing (NLP) models used to be the standard even a few years ago, which were capable of performing a specific task given to them.

However, OpenAI, a San Francisco-based company made a breakthrough with its GPT model. GPT is a deep learning model trained on the data available on the internet. It can answer a question, have conversations, write codes as well as generate and summarize content.

GPT-1 paper was published in 2018 which focused on sentiment analysis, classification and learning from unlabeled data. It had 117 million parameters which could be fine tuned for a number of applications. GPT-2 with 1.5 billion parameters came in 2019 and GPT-3 with 175 billion parameters is in beta testing from 2020. 

What can GPT do 

One of the most popular use cases of GPT is sentiment analysis. It does not only classify data on keywords but also reads them as phrases and sentences to understand the tone and mood of it. This is very helpful for companies who give out surveys or want to better process feedback.

Another popular use case is content generation. Much like DALLE-2, the text-to-art generation AI tool created by OpenAI, GPT-3 can write an essay, news articles, have conversations and much more without the need to provide any input. It can scour through the internet to find relevant information and then can use the data to process it as well as learn from it.

Other uses include answering specific questions, text translations, customer support and so on. 

Regulatory issues around GPT 

Some experts have raised concerns around GPT’s learning methods since it largely relies on the information provided on the internet. Since the method includes a high volume of data extraction and processing at an extremely high speed, there are some issues that can potentially cause legal disputes.

The first concern is on personal privacy as some of the data available online could be sensitive information of people which has been leaked online by bad actors. Another concern is defamation as the AI could process negative information on a topic and use it in its responses. Further, with biases, discriminatory comments and misinformation present everywhere online, the AI could also become plagued with this problematic information.

As we wait for GPT-4, and the technology itself becomes more accessible, it will be interesting to see how all these issues are tackled.