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.
Latest Analysis
-
The Economics of Foundation Model Training: Analyzing Compute Costs, Energy Consumption, and Environmental Impact
Introduction: The Unseen Ledger of AI Progress The rapid ascent of foundation models—large-scale neural networks trained on vast datasets—has redefined the frontiers of artificial intelligence. From generating human-like…
-
Federated Learning in Healthcare AI: Privacy-Preserving Approaches for Sensitive Data Environments
Introduction: The Privacy-Paradigm Problem in Medical AI The development of robust, generalizable artificial intelligence models for healthcare hinges on access to vast, diverse, and high-quality datasets. However, this…
-
Algorithmic Bias in Clinical Decision Support Systems: An Interdisciplinary Framework for Ethical Implementation
Introduction: The Promise and Peril of Clinical Algorithms The integration of Artificial Intelligence (AI) and Machine Learning (ML) into Clinical Decision Support Systems (CDSS) heralds a transformative era…
-
Prompt Engineering as a Scientific Discipline: Methodologies for Systematic Instruction Optimization
Introduction: From Artisanal Craft to Systematic Inquiry The rapid proliferation of large language models (LLMs) has foregrounded a seemingly simple interface: the text prompt. What began as an…
-
The Open-Source Frontier: Evaluating the Performance and Governance of Community-Driven Language Models
Introduction: The Shifting Landscape of Model Development The paradigm of large language model (LLM) development is undergoing a profound transformation. Once the exclusive domain of well-resourced corporate laboratories,…
-
Beyond Fine-Tuning: Parameter-Efficient Adaptation Strategies for Enterprise AI Deployment
The deployment of large-scale foundation models in enterprise environments presents a formidable paradox. While models like GPT-4, LLaMA, and Claude offer unprecedented capabilities in natural language understanding and…