What is Generative AI?
Generative AI (GenAI) has come a long way since its inception, evolving from simple rule-based systems to sophisticated models capable of generating complex outputs. Recent breakthroughs and an explosion in popularity has led to rapid growth in this field, with organizations across industries and business functions adopting GenAI to drive innovation and efficiency. But what is GenAI? It is a cutting-edge technology that businesses eagerly anticipate for driving revenue growth, operational efficiencies, and risk mitigation. It is a subfield of artificial intelligence that focuses on the development of algorithms and models capable of generating new data, often resembling, or mimicking, existing data. This is achieved using advanced machine learning techniques, such as deep learning and neural networks. The primary goal of GenAI is to create systems that can autonomously produce high-quality, realistic, and diverse outputs without explicit human intervention.
In simple terms, it is a technology that has an uncanny ability to understand the intent of your queries and generate outputs that you would be hard-pressed to determine whether it was generated by a human or a machine. In other words, applications that utilize this technology, such as ChatGPT, can become your very own personal assistants.
Speaking about ChatGPT, let us dive into where ChatGPT fits into all of this. ChatGPT is a language model, developed by OpenAI, based on the GPT (Generative Pre-trained Transformer) architecture. It is designed to understand and generate human-like text, enabling it to engage in interactive and dynamic conversations with users. ChatGPT is trained on a diverse range of internet text data, which allows it to generate contextually relevant and coherent responses to user inputs.
Broadly speaking, there are two types of models underpinning the GPT architecture (so far): Transformer-based models (e.g., GPT-3.5) for text inputs, and Multimodal models (e.g., GPT-4) for various data types. These are large language models (LLMs) and are pre-trained on large-scale datasets and fine-tuned for specific tasks, such as question-answering, summarization, or translation. The key strength of GPT models, including ChatGPT, lies in their ability to generate context-aware, fluent, and semantically meaningful text. At this point, many versions of these models are mature enough that one can converse with an application like ChatGPT as one would with another person.
Right now, GenAI excels in creative tasks such as drafting emails, customizing marketing content, providing customer support, and writing code. When paired with other AI models, quality data, governance rules, and analytics modules, it can create powerful solutions to power autonomous and semi-autonomous decision-making within organizations by blending their internal data with industry and market data.
In the rest of this whitepaper, we will explore the history and recent rise of GenAI, consider the opportunities it brings for the insurance industry, and discuss the importance of high-quality data and responsible AI practices in maximizing its potential.
