Artificial Intelligence in 2025: Scientific Foundations, Generative Content, and the Age of the "Dead Internet"

Abstract. This paper explores the contemporary landscape of Artificial Intelligence (AI), with a particular emphasis on generative models, transformer architectures, and the epistemological consequences of replacing authentic digital content with synthetic outputs. It examines the technological foundations of deep learning, the ethical and societal challenges posed by cognitive automation, and the provocative "Dead Internet Theory" - which suggests that a significant portion of online content is now machine-generated. Combining scientific rigor with philosophical reflection, the work offers an impartial and critical perspective on the future of human-machine symbiosis in an era of digital hyperreality. Special attention is given to issues of trust, algorithmic bias, and the ontological status of AI-generated media. Keywords: Artificial Intelligence, Generative Models, Large Language Models (LLMs), Deep Learning, Transformer Architecture, Synthetic Content, Epistemology of AI, Dead Internet Theory, AI Ethics, Algorithmic Bias, Automation and Labor Displacement, Digital Authenticity, Symbolic AI, Connectionism, Neural Networks, Content Provenance, Post-Synthetic Epistemology, Human-Machine Symbiosis, Cognitive Automation, AI-Generated Media, Ontology of Intelligence For citation: Perovskii Aleksei. Artificial Intelligence in 2025: Scientific Foundations, Generative Content, and the Age of the "Dead Internet"