Tensor Times
An academic-grade journal of artificial intelligence research — peer-reviewed analysis of large language models, machine learning frameworks, and the engineering behind today’s most consequential AI systems.
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AI-Driven Drug Discovery Pipelines: Integrating Large Language Models with Molecular Simulation and High-Throughput Screening
The convergence of artificial intelligence (AI) and biotechnology is catalyzing a paradigm shift in pharmaceutical research, promising to accelerate the historically arduous and costly journey from target identification…
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The Role of Synthetic Data in Mitigating Dataset Bias: Generation Techniques and Validation Methodologies
The pursuit of unbiased, high-performing machine learning models is fundamentally constrained by the quality and composition of their training data. Dataset bias—systematic skews in data collection, annotation, or…
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Differential Privacy in Federated Learning Systems: Theoretical Guarantees and Practical Implementation Challenges
The convergence of federated learning (FL) and differential privacy (DP) represents a paradigm shift in privacy-preserving machine learning. Federated learning, which enables model training across decentralized devices without…
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Supply Chain Optimization with Reinforcement Learning: Adaptive Decision-Making in Dynamic Industrial Environments
Introduction: The Imperative for Adaptive Supply Chains The modern global supply chain is a paradigm of complexity, characterized by volatility, uncertainty, and interconnectedness. Traditional optimization models, often reliant…
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AI Governance in Democratic Societies: Comparative Analysis of Regulatory Approaches in the European Union and United States
Introduction: The Imperative of Governing Intelligence The rapid ascent of artificial intelligence, particularly foundation models and generative AI, presents a profound governance challenge for democratic societies. These technologies…
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The Epistemology of Machine Learning: Philosophical Foundations of Knowledge Acquisition in Data-Driven Systems
Introduction: Beyond the Algorithmic Black Box The rapid ascent of machine learning (ML) as a dominant paradigm for knowledge generation compels a critical examination of its philosophical underpinnings.…