What does GPT stand for in Chat GPT, and how does it work?
The GPT technology reached an inflection point and burst onto the scene with ChatGPT in late 2022. Since its introduction to the world, ChatGPT has become the fastest application to reach one million users and holds the record for being the fastest to reach 100 million users.
It would be interesting to know how many people from those hundred million users can successfully answer the question, What does GPT stand for in ChatGPT? If you don’t know, don’t worry, I will quickly explain.
Simply put, GPT stands for “Generative Pre-trained Transformer.”
Now that is out of the way and we have answered what GPT means, we can dive into the how. In this article we will will also explain how ChatGPT works
What does GPT stand for? Explained
GPT stands for “Generative Pre-trained Transformer.” The diagram below goes into more detail about the concepts of GPT
Now that we know what GPT means let’s dive into how ChatGPT works.
How ChatGPT works
ChatGPT is a large language model (LLM). It creates answers that seem like something a human would say. It does this by using the information it learned during training and by choosing the right word sequence. This model has lots of parameters and can even understand tricky questions.
ChatGPT Generative AI
Generative AI is artificial intelligence that can generate new content rather than acting on or analysing existing data. Chat GPT interacts in a conversational way. The dialogue format of Chat GPT allows it to answer follow up questions, admit its mistakes and refuse to answer inappropriate requests.
ChatGPT can correct grammar, summarise simplly complex topics and can also fix bugs in code. The training for the GPT model was reinforcement learning from human feedback and professional known as RLHF.
ChatGPT Neural Network architecture
Chat GPT is based on a Neural Network Architecture that can process and generate responses for any sequences of characters that make sense. Neural networks are composed of an interconnected layer of nodes called neurons that process and transmit information. The Neural Network Architecture is made up from three layers that are classified as the input layer, the output layer and the hidden layer.
Over the past 20 years Neural Networks have become widely used in everything from driving cars to voice assistants. ChatGPT’s Neural Network is referred to as a transformer model architecture and was designed for natal language processing tasks that underpins ChatGPTS incredible ability to generalize.
ChatGPT Transformer Architecture and Attention Mechanisim
In the transformer architecture, something referred to as the attention mechanism helps the network process and comprehend complex data by identifying and emphasizing the most relevant information.
ChatGPT uses a 12-layer transformer network with a total of 175 million parameters known as its training set. This training set is a vast amount of data from a diverse range of sources that include a vast library of books and internet resources.
Training GPT models
Imagine yourself back in school. You are passionate about a topic and don’t mind studying it. You know it so well that you can explain it with different words to different types of people, and you can even create scenarios around it to make it easy to understand. It’s the same for ChatGPT. Not only is it trained on a lot of information, but it also learned how languages and communication work.
ChatGPT was trained with so much textual information that it can predict the next word that makes the most sense in a sentence. That’s the whole concept behind LLM.
But it has its downsides: ChatGPT will sometimes create a sentence that makes sense but that may be factually incorrect. It will also behave based on what the user wants, which means ChatGPT can give biased answers based on the prompt that the user writes.
The GPT versions
You might be thinking, if there’s a GPT 3.5 and 4, there is also a GPT 1, 2, and 3? Well, not really. Let’s look back into the history of ChatGPT:
At the end of 2022, OpenAI presented ChatGPT-3 to gather feedback. It was still considered a “research” period. Around that time, DALL-E 2, a text-to-image AI tool, was also released by OpenAI.
OpenAI kept working on making ChatGPT-3 better until it became the 3.5 version that we have now.
ChatGPT Plus was released in February 2023, it’s a subscription where paid users have access to GPT-4, which has more advantages: a faster response time, a bigger input and output limit, access to plug-ins, and the ability to browse the internet.
Since the release of Chat-GPT at the end of 2022, there have also been changes in the user interface. More and more options became available, even for free users.
The future of GPT
Despite the load of information online about ChatGPT and I in general, the future is still difficult to predict. However, OpenAI seems to know where it’s going. Scott Aaronson, a researcher, has reported that OpenAI is trying to develop digital print watermarking that would prevent people from using AI with bad intentions (like spamming, hacking, or using ChatGPT to write academic papers). It would make the output detectable as written by AI with 100% accuracy.
OpenAI will do its best to prevent bad people from doing malicious things with AI, and that’s great news.
Some things are pretty clear about the future of AI: it is a new piece of technology, and many things will change. Some jobs will change a lot. Think of customer service, where an AI chatbot could take the job of the customer service agent until it’s unable to find a solution. It’s possible that learning new skills related to AI will be needed to find or keep your job.
The growth of AI will also create new jobs. The role of prompt engineering is the most obvious. People studying AI now or just finishing their studies in that field might have job titles that didn’t exist a few years ago. Data experts will also be important. Lawyers might specialize in AI-related problems. We might even see jobs like “AI Manager”, “AI integration specialist,” or something similar.
We’ve all heard of the writer’s strike in Hollywood, and it raises a valid question: What will happen if a machine can generate scripts or videos with a simple command? Will people be able to buy customized movies in the future? Will we be able to say “I want a movie with this actor, happening in this country, with this type of scene”?
There’s also a possibility we have to keep in mind that OpenAI is a company, and it must obey the rules of the countries in which its services are available. This means that if a country decides to ban AI, then it will happen.
There is a possibility of a scenario where world leaders gather and decide to pull the plug on AI until laws and regulations are in place. Some countries have already banned ChatGPT. That’s why we must be patient and use ChatGPT wisely until there are clear laws.
Round Up
ChatGPT is a fascinating tool, and it has pushed people to learn things they never thought they’d be interested in, like coding or integrating an API. There’s no doubt that millions of people benefit from using ChatGPT every day.
While it is fun and the future will be interesting, we should always remember that ChatGPT is a tool and that a human expert will always be needed to fact-check the output.
If we all spend a little bit of our time fact-checking and helping ChatGPT produce meaningful output, then we can collectively push AI to the next level and make the internet a better place.
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