Hidden goals can undermine AI teamwork, study finds
Large language models (LLMs), the computational models that underpin conversational agents such as Gemini and ChatGPT, are now widely used by people worldwide to rapidly find information, summarize documents and generate texts for specific purposes. Some computer scientists are now combining two or more of these models to create multi-agent systems, which prompt multiple artificial intelligence (AI) agents to interact, cooperate and/or compete with the goal of completing specific tasks.
The rapid advancement of natural language processing (NLP) models and large language models (LLMs) has enabled the development of new use-specific conversational agents designed to answer specific types of queries. These range from AI agents that offer academic support to platforms offering general financial, legal or medical advice.
Large language models (LLMs), the computational algorithms underpinning ChatGPT, Gemini and other artificial intelligence (AI)-powered conversational platforms, are now widely used worldwide. These models can rapidly answer questions, source information online, assist users with specific tasks and produce text tailored for specific purposes.