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 Precision Agriculture: Integrating Multimodal Data for Crop Yield Prediction and Resource Optimization
Introduction: The Data-Driven Farm The global agricultural sector stands at a critical juncture, tasked with the monumental challenge of increasing food production by an estimated 60% by 2050…
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Chain-of-Thought Prompting for Complex Problem Solving: A Systematic Evaluation of Reasoning Capabilities in Mathematical and Scientific Domains
Recent advances in large language models (LLMs) have demonstrated remarkable proficiency in generating fluent text, yet their capacity for deliberate, multi-step reasoning remains a subject of intense scrutiny.…
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The Democratization of AI Research: How Open Models Are Transforming Academic Collaboration and Reproducibility
The landscape of artificial intelligence research has undergone a profound structural shift over the past decade. Historically, the field’s most significant advances were often sequestered within the proprietary…
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AI-Assisted Legal Document Analysis: Benchmarking Large Language Models on Contract Review and Compliance Tasks
The integration of artificial intelligence into the legal profession represents one of the most consequential technological shifts in the field since the advent of digital databases. At the…
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The Carbon Footprint of Large Language Model Inference: Quantifying Environmental Impacts Across Deployment Scenarios
The rapid proliferation of large language models (LLMs) has catalyzed a paradigm shift in artificial intelligence, enabling capabilities from conversational agents to complex code generation. However, this technological…
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AI-Driven Market Intelligence Systems: Methodologies for Real-Time Sentiment Analysis and Competitive Landscape Mapping
Introduction: The New Terrain of Strategic Decision-Making In an era defined by data velocity and information overload, traditional market intelligence (MI) methodologies are increasingly insufficient. The static, quarterly…