Shaping the Future: Policies for Generative AI in Sri Lankan Higher Education
Chatbots and Large Language Models: How Advances in Generative AI Impact Different Applications
The recent progress in large language models (LLMs), such as GPT, PaLM, and Llama, and their ability to generate artificial intelligence have attracted considerable interest from both the scientific community and the general public. While consumers and researchers may readily access these models through typical prompting interfaces, API calls, or static snapshots, there is a growing need for these models to offer customised and contextually aware replies. This need is necessary in many application settings where it is crucial to provide assistance and customisation for individuals and groups of users with varying backgrounds and preferences. Dependence solely on generic replies is inadequate for meeting the particular requirements and limitations of users in personal, group, or societal settings. Instead, these situations need the models to possess the capability to analyse and synchronise their replies with the preferences and aims of the users in the described environments.