Speaker 1: Meet John, a software developer. John develops a program and now he realizes the program is surrounded by a lot of bugs. John starts exploring a solution. He surfs through the internet, checks programmer communities. Doubting every step of the way, John feels his problem is not solved. Desperate to find the solution, John meets his friend Adam. Adam comes up with an idea of an artificially intelligent and practical solution called the ChatGPT. Adam says ChatGPT has the caliber to systematically resolve all the bugs with an elaborate explanation for every step it makes. ChatGPT is an AI-trained model that works in a conversational way, developed by OpenAI. Fascinated by hearing this, John asks Adam to explain him in detail. After Adam explains that, GPT, aka Generative Pre-Training Transformer, has come a long way. Before the introduction of GPT, natural language processing used to deal with a specific task with large amounts of data. GPT was first released in 2018, which contained 117 million parameters. GPT, GPT-2, and GPT-3. Each one is stronger than the one before it. The main reason why GPT received little attention was that it was more of an idea or test than a finished product. But after the introduction of GPT-2, it gained a lot of attention, as it could accurately predict the word that would begin a test. Then they introduced GPT-3, which is a strong language model, achieving translation, question answering, and performing three-digit arithmetic. But ChatGPT stands tall compared to all other achievements of OpenAI. So, how does it work? ChatGPT uses deep learning techniques to generate human-like text. It is based on the machine learning model derived from the class called the Large Language Model. ChatGPT is a byproduct of InstructGPT. InstructGPT introduced a strategy for integrating human feedback into the training process to match model outputs. This innovative technology made ChatGPT exceptional. It is trained on the massive datasets of text from the Internet and learns from the patterns and relationships between words and phrases. It responds to a prompt by determining the next word based on the context, then repeats the process until a stop condition is met. As a result, ChatGPT can produce various logical responses to various queries and prompts. The most important components of ChatGPT are the transformer model and language model. Coming to the transformer model, it is a neural network architecture designed to process sequential data. It consists of multiple layers of self-attention and a feed-forward network. After the transformer model has processed the input, a decoder generates the output. The decoder uses the context provided by the encoder to generate the response. The model is trained using unsupervised learning and fine-tuned on specific tasks using supervised learning. For successful completion of tasks, it needs pre-trained data. The model first encodes the input text, then converts it to a numerical representation, which can be processed by the model's neural network. This encoding is done using the embedded layer that maps the word. Then comes the language model. ChatGPT is trained as a language model, trained to predict the next word in a sequence given the previous words. The language model intends to produce rational, consistent, and meaningful output. The pre-trained ChatGPT can be tuned for a specific task. So, ChatGPT passes a fine-tuning test by answering questions, generating text summaries, or generating text in response to a query. Overall, ChatGPT is a powerful language model with a combination of techniques like deep learning, machine learning, neural networks, and natural language processing. Can ChatGPT change a wide variety of business tasks? John asked. ChatGPT possesses the ability to automate content creation on social media, create chatbot and e-commerce sites, provide medical assistance by acting as a symptom checker, write code, and assist a developer. Thus, ChatGPT can change the working of every industry. Now John can resolve any coding issue without looking into any other resources. But like any other technology, ChatGPT comes with a few limitations that can be its Achilles' heel. ChatGPT is capable of developing content up to 2021. It finds difficulty in providing logical reasoning in certain situations. And also, ChatGPT lags in translation, summarization, and sometimes question answering. But above all, ChatGPT has shown remarkable ability by providing accurate answers flawlessly in a creative way in very short periods of time. But before we end, I have a question for you. Which language model does ChatGPT belong to? Give the answer with reasoning and stand a chance to win an Amazon voucher. 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