What is ChatGPT? The groundbreaking AI chatbot explained

ChatGPT, a conversational chatbot powered by artificial intelligence and natural language processing models, has taken the world by storm since OpenAI released it in November 2022. The buzz is driven by its various use cases and ability to generate accurate, detailed and human-like responses from simple text prompts.

OpenAI says ChatGPT works best when users input a question or request. These inputs are based on any subject or area of interest, which is what makes the bot such a compelling offering. Ask a question, and ChatGPT generates a reply. You can ask it to create code for an engineering project, for example, explain a major historical event, create a short story or translate languages. The use cases are near-limitless.

The science behind ChatGPT is staggering too. In layman’s terms, OpenAI says the model is “trained on a large corpus of text data” but there is a lot going on behind the scenes to make it so advanced in its text-generating abilities. Large language models are doing the bulk of the work, but there is also something called Reinforcement Learning with Human Feedback (RLHF) that helps the bot to train and learn from feedback to deliver high-quality responses.

Everything comes back to data, though, and lots of it. Stanford University says the computer program ChatGPT is built from — GPT-3 — allows for a huge increase in the number of data bots that can be trained on compared to the previous generation. GPT-3 has an incredible 175 billion parameters and leverages more than 570GB of text.

The university adds: “This increase in scale drastically changes the behavior of the model — GPT-3 is able to perform tasks it was not explicitly trained on, like translating sentences from English to French, with few to no training examples.”

ChatGPT is technically a large language model (LLM) and was trained using a variety of sources from across the web including Reddit discussions, which gave the bot its unerring ear for dialogue and creating responses that you would expect from a human being. The RLHF added a layer of complexity as it enabled ChatGPT to effectively ‘autocomplete’ responses based on what it believes humans expect from a reply.

This sets ChatGPT apart from previous chatbots as it is not simply being trained and then generating answers on pre-programmed conceptions. It is able to use human feedback to improve and evolve. Last year, a research paper discussed the breakthrough of using human feedback to train LLMs. It states the latest developments make bots more than just prediction models, and they are becoming more ‘helpful’ and ‘truthful’ as a result.

It is now obvious that many of the advancements in technology that will transform society and the wider world require a huge mass of data to operate. Big data is now big business, and many corporations will be looking to leverage data for data mining, machine learning, predictive models and AI, among other processes, during the next decade. Completing a data science online master’s degree will allow you to secure job roles in this exciting field. The Bureau of Labor Statistics (BLS) expects 15% job growth in computer science positions through 2029.

Getting the chance to work with some of the tech behind ChatGPT is a fascinating prospect for data science graduates who can potentially forge careers in data science, web development and software testing afterwards. When digging a little deeper, the science behind ChatGPT only becomes more compelling due to the complexity of tasks being completed ‘on the fly’ to deliver in-depth responses.

OpenAI fine-tuned the standard GPT-3 model to create ChatGPT, which involved the work of 40 independent contractors who created a vast dataset for inputs and outputs. Further work saw the creation of around 13,000 input and output samples for the new model to work from. This is known as a supervised fine-tuning (SFT) model, which is the first step in ChatGPT’s ‘genius’.

The bot can use all this data to generate responses that align with user prompts which is why ChatGPT’s output is so relevant and exciting. The second step is the ‘reward model’, which was trained by OpenAI based on ranking the outputs from best to worst. The final stage involves the reinforcement learning model mentioned previously. Reinforcement is based on rewards, with the rewards essentially enabling the model to learn, improve and evolve.

The model also conducts a series of evaluations based on ‘helpfulness’, ‘truthfulness’ and ‘harmlessness’ to ensure the responses are respectful and accurate. It all adds up to an incredibly versatile and high-quality form of AI, which has got many big tech corporations scrambling to either use it or incorporate some of its features.

Google has already recognised how transformative ChatGPT could be for search engines. It recently sounded an internal ‘code red’ and reports claim the company is planning to launch chatbot features sometime this year. Google believes AI can help it provide safer, more accurate search results and eradicate misinformation across its platforms. Other companies will look to ChatGPT and its feature set for similar goals and objectives.

Even though it only launched months ago, companies are already trying to leverage ChatGPT to improve their products and services. Web advertising company, Taboola, has stated that ChatGPT will enable it to generate more relevant and trustworthy content for visitors, which could have a profound impact on ad targeting strategies. Freelancers are already tapping into the power of Chat GPT as you can see here , and it’s becoming increasingly used by the general public as well.

Software company Intercom has also released new ChatGPT-powered bots to support its customer service team, and to create content for web pages. AI is expected to overhaul many marketing processes during the next decade. Gartner predicts that bots will create 30% of all outbound messages within three years, a development that would have been unthinkable only a few years ago.

Following the acclaim and buzz for ChatGPT, AI now looks set to disrupt every facet of business. Investment in data is likely to surge as a result, which highlights how important analysing and making sense of big data will be for companies as they attempt to drive growth and expansion with higher quality services and new cutting-edge products. ChatGPT is just the beginning of a new digital age.

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