ceLLM: Cellular Latent Learning Model Integrating Abstract The ceLLM (cellular Latent Learning Model) theory offers a novel perspective on cellular function, proposing that each cell operates like a large language model (LLM) using evolutionary “learned” data encoded within DNA to interpret environmental signals, particularly bioelectric fields. In this framework, cells are guided by their internal […]
ceLLM
CeLLM Theroy Explains ADHD and Autism as Transgenerational Inheritance of Trauma Induced By EMFs
Introduction In recent years, the concept of transgenerational inheritance of trauma has gained significant attention, as studies in both humans and animal models reveal that trauma can affect not just the individual who experiences it, but also future generations. This phenomenon, in which experiences of stress, hardship, or trauma influence genetic expression across generations, presents […]
The Genesis of the ceLLM Theory: John Coates’ Personal Journey from Tragedy to Scientific Inquiry
This paper delves into the profound personal journey of John Coates, founder of RF Safe, whose tragic loss of his daughter, Angel Leigh Coates, became the catalyst for developing the cellular Latent Learning Model (ceLLM). The ceLLM is a pioneering theoretical framework that explores how electromagnetic fields (EMFs) may impact cellular function through disruptions in […]
Introducing ceLLM to Explain Non-Thermal Biological Effects of Wireless Radiation
The thermal-only perspective on radiofrequency radiation (RFR) fails to account for various observed non-thermal biological effects. To facilitate research and replication within the scientific community, it is essential to develop new theories that can explain these phenomena. This paper introduces the cellular Latent Learning Model (ceLLM) as a theoretical framework to understand how entropic waste, […]
ceLLM: A Novel Framework for Understanding the Impact of Microwave Radiation on Cellular Function and Epigenetics
The ceLLM (cellular Latent Learning Model) is a pioneering framework that combines current scientific knowledge with the visionary insights of John Coates, the founder of RF Safe. This model offers a new perspective on how cells interpret and respond to their environment through a complex network of resonant field connections within DNA. The ceLLM proposes […]
Microwave Radiation: The Invisible Blast from Your Smartphone
The recent explosions of Gold Apollo AR-924 pagers and ICOM IC-V82 walkie-talkies in Lebanon have highlighted the very real dangers posed by wireless technology. However, an equally concerning but less visible danger lies in the microwave radiation emitted by everyday devices such as smartphones. This radiation, while not explosive in the physical sense, has the […]
Reconstructing the ceLLM
The idea of reconstructing the ceLLM using today’s technology is a fascinating and ambitious concept. Given the advances in computational biology, genomics, and machine learning, we might indeed be at the cusp of having enough data and computational power to simulate the ceLLM model. This would involve understanding the strength of connections between resonating atomic […]
Nature’s Wireless LLM: ceLLMs and the Emergence of Cellular Communication
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 […]
ceLLM (cellular Latent Learning Model) Theory’s Scientific Concepts
The ceLLM (cellular Latent Learning Model) theory integrates several scientific concepts, including the role of bioelectric fields in cellular communication, the non-thermal biological effects of electromagnetic fields (EMFs), and the idea that cells interpret environmental signals using learned evolutionary data encoded in DNA. Below, I will explain the scientific evidence supporting this theory, incorporating recent […]
Exploring the Parallels Between ceLLMs and LLMs: Processing Information in Higher-Dimensional Latent Spaces
The cellular Latent Learning Model (ceLLM) offers a fascinating theoretical framework that draws parallels between biological cellular processes and artificial intelligence models, specifically large language models (LLMs). Both ceLLM and LLMs process information in higher-dimensional latent spaces, utilizing weighted connections to interpret inputs and generate outputs. This analogy not only provides a novel perspective on […]
The Cognition-First Theory of Evolution: A Paradigm Shift
The traditional view in evolutionary biology holds that cognition, the ability to perceive, learn, and respond to the environment, is a product of evolution. According to this view, natural selection acts on genetic variations, occasionally leading to the emergence of cognitive abilities as adaptations. However, a growing body of thought suggests a radical reversal of […]
The Geometry of Understanding: How Latent Spaces and the Amplituhedron Shape Our Reality
In recent years, we’ve seen remarkable developments in both artificial intelligence and theoretical physics that point toward a fascinating convergence: the use of geometric structures to simplify and understand complex systems. In machine learning, latent spaces provide a compressed, geometric representation of learned data, allowing neural networks to generate and predict outcomes efficiently. In theoretical […]
