ChatGPT, Google Bard, and other large language models (LLMs) are revolutionizing the world of artificial intelligence and conversational software, empowering them to take over web searches and generate creative content, while helping us remember all the world’s knowledge at the same time. But what exactly makes them so effective, and where can they be improved? In order to understand fully how ChatGPT, Google Bard and other like them work and use them to their best potential, it is crucial to look into their complex structure.
Large language models are trained on vast amounts of data, though the specifics of this data have been kept tightly sealed by technology companies. However, clues can be discerned from certain sources. For example, researchers of the LaMDA model, the machine learning system which Bard is based on, wrote about the use of Wikipedia, public forums, and code documents from programming sites such as Q&A platforms and tutorials. It is likely that many of these sources have either been made available freely or companies have taken advantage of the lack of restriction up until now.
Chatbots and other artificial intelligence systems, like those used in voice recognition and in the creation of cat images, are driven by neural networks. These networks consist of many nodes and layers which allow for updating, interpretation, and analysis of the data. Furthermore, LLMs make use of a transformer-based architecture, an essential component of making language processing more effective and accurate. The GPT in ChatGPT stands for Generative Pretrained Transformer, which uses a mechanism known as self-attention that takes into account context and relationships between words, rather than considering them solely in isolation.
This self-attention has increased LLMs capabilities and created results that could be mistaken for original thoughts and creative pieces. However, it is also the basis of occasional errors and inaccuracies. LLMs don’t possess knowledge but are rather skilled in establishing which words should follow other words, making them a powerful tool, albeit one that shouldn’t be trusted entirely.
ChatGPT was started in 2020 by Hubert Chien, an AI specialist and professor at the University of New York. He began the project as an attempt to combine the power of deep learning and natural language processing to create more intuitive chatbots. ChatGPT is a tool for businesses, media, and customer experience teams to get a better understanding of how best to create and implement conversations with customers. Chien also headed a team of AI researchers to develop an “interactive conversation simulator” which can chat as learning AI agents with humans.
LLMs have brought unprecedented advancements in AI and language processing, and they have certainly come a long way in their development. However, there is still much room for improvement and this will certainly be a worthwhile pursuit to continue the success of such models and their impact on our lives.
