From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models

• Main Authors: Nisioti, Eleni, Glanois, Claire, Najarro, Elias, Dai, Andrew, Meyerson, Elliot, Pedersen, Joachim Winther, Teodorescu, Laetitia, Hayes, Conor F, Sudhakaran, Shyam, Risi, Sebastian
• Format: Journal Article
• Language: English
• Published: 14-06-2024
• Subjects: Computer Science - Artificial Intelligence; Computer Science - Neural and Evolutionary Computing
• DOI: 10.48550/arxiv.2407.09502

Large Language Models (LLMs) have taken the field of AI by storm, but their
adoption in the field of Artificial Life (ALife) has been, so far, relatively
reserved. In this work we investigate the potential synergies between LLMs and
ALife, drawing on a large body of research in the two fields. We explore the
potential of LLMs as tools for ALife research, for example, as operators for
evolutionary computation or the generation of open-ended environments.
Reciprocally, principles of ALife, such as self-organization, collective
intelligence and evolvability can provide an opportunity for shaping the
development and functionalities of LLMs, leading to more adaptive and
responsive models. By investigating this dynamic interplay, the paper aims to
inspire innovative crossover approaches for both ALife and LLM research. Along
the way, we examine the extent to which LLMs appear to increasingly exhibit
properties such as emergence or collective intelligence, expanding beyond their
original goal of generating text, and potentially redefining our perception of
lifelike intelligence in artificial systems.