Category: History
Latency Management for RAG Pipelines in Production LLM Systems
Learn how to cut RAG pipeline latency from 5 seconds to under 1.5 seconds using Agentic RAG, streaming, batching, and smarter vector search. Real-world fixes for production LLM systems.
Procurement Checklists for Vibe Coding Tools: Security and Legal Terms
Vibe coding tools like GitHub Copilot and Cursor speed up development but introduce serious security and legal risks. This guide gives you the exact checklist to safely adopt them in 2025.
How to Detect Implicit vs Explicit Bias in Large Language Models
Large language models can pass traditional bias tests while still harboring hidden, implicit biases that affect real-world decisions. Learn how to detect these silent biases before deploying AI in hiring, healthcare, or lending.
Why Transformers Replaced RNNs in Large Language Models
Transformers replaced RNNs because they process language faster and understand long-range connections better. With parallel computation and self-attention, models like GPT-4 and Llama 3 now handle entire documents in seconds.
Measuring Developer Productivity with AI Coding Assistants: Throughput and Quality
AI coding assistants promise faster development, but real-world results show trade-offs between speed and code quality. Learn how top companies measure true productivity using throughput and quality metrics-not vanity stats.
Bernard Xavier Philippe de Marigny: Louisiana's Forgotten Nobleman and Cultural Icon
Bernard Xavier Philippe de Marigny was a French Creole nobleman who shaped New Orleans by developing the Marigny neighborhood, allowing diverse communities to thrive together - laying the groundwork for jazz and Creole culture.
Infrastructure Requirements for Serving Large Language Models in Production
Serving large language models in production requires specialized hardware, optimized software, and smart architecture. Learn the real costs, GPU needs, and optimization strategies that separate successful deployments from costly failures.
Hybrid Search for RAG: Boost LLM Accuracy with Semantic and Keyword Retrieval
Hybrid search combines semantic and keyword retrieval to fix RAG's biggest flaw: missing exact terms. Learn how it boosts accuracy for code, medical terms, and legal docs-and when to use it.
Trademark and Generative AI: How Synthetic Content Is Risking Your Brand
Generative AI is copying trademarks without permission, confusing customers and putting brands at risk. Learn how AI-generated content threatens your brand and what steps you can take now to protect it.
Positional Encoding in Transformers: Sinusoidal vs Learned for LLMs
Sinusoidal and learned positional encodings were early solutions for transformers, but modern LLMs now use RoPE and ALiBi for better long-context performance. Learn why and how these techniques evolved.
Toolformer-Style Self-Supervision: How LLMs Learn to Use Tools on Their Own
Toolformer teaches large language models to use tools like calculators and search engines on their own, without human labels. It boosts accuracy in math and facts without needing bigger models.
Generative AI in Healthcare: How AI Is Transforming Drug Discovery, Medical Imaging, and Clinical Support
Generative AI is transforming healthcare by speeding up drug discovery, improving medical imaging accuracy, and reducing clinician burnout through automated clinical support. By 2025, it's already saving time, cutting costs, and saving lives.
