Artifacts
Synthesis and analysis of AI research. Evidence-based insights backed by our data.
Scaling Intelligence: AI's Rising Power Demands
ResearchAI's exponential growth in power demand is reshaping the intersection of technology and energy. Analysis of compute scaling, hardware efficiency, and business implications from EPRI research.
AI and the Futures Turn
ResearchRethinking AI in futures work - exploring anticipatory infrastructures and anticipatory realism. Based on Sarah Pink's research on AI as infrastructure that shapes how futures are imagined.
Limitations of AI Circa 2025
ReflectiveField notes documenting observed limitations, failure modes, and practical constraints of AI systems. ARCR-formatted observations covering hallucinations, context limits, reasoning gaps, and more.
AI in Customer Support: Evidence from BFSI
Coming SoonComprehensive analysis of AI customer support implementations across banking and financial services, showing 32% time savings and 18% cost reduction.
Copilots vs Agents: A Framework
Coming SoonFramework for understanding the architectural and operational differences between AI copilots and autonomous agents, with implementation guidance.
LLM Cost Optimization Strategies
Coming SoonAnalysis of cost reduction techniques for LLM deployments including prompt caching, batching, and model selection across major providers.
AI Adoption in Healthcare: 2024 Review
Coming SoonComprehensive study of AI implementation patterns in healthcare organizations, covering diagnostic tools, patient management, and operational efficiency.
RAG System Performance Field Notes
Coming SoonSystematic evaluation of Retrieval-Augmented Generation systems across different embedding models, vector databases, and chunking strategies.
Enterprise AI Governance Framework
Coming SoonFramework for establishing AI governance in enterprises, covering risk management, compliance, ethical guidelines, and monitoring practices.
Fine-tuning vs RAG: Performance Comparison
Coming SoonComparative analysis of fine-tuning and RAG approaches for domain-specific tasks. Cost, accuracy, and latency benchmarks across different use cases.
AI in Legal Services: Implementation Guide
Coming SoonPractical guide to implementing AI in legal workflows including document review, contract analysis, and legal research automation.
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