Abstract In this paper, we explore the concept of cellular Large Language Models (ceLLMs) in biological systems, where DNA and its atomic interactions create a wireless network of neural weights and biases. These ceLLMs store the learned data from evolutionary processes to shape the geometry of latent space, producing probabilistic outcomes in response to environmental […]





