Agentic RAG: Teaching an LLM to Search Like a Researcher
Ask a friend a hard question, like “How did the failure of Silicon Valley Bank compare to the 2008 financial […]
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Text Embeddings: Turning Language into Meaningful Vectors
Search breaks down when wording changes but meaning stays the same. A user types “I forgot my credentials,” while the
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Document Ingestion: How Data Enters a RAG System
Document ingestion is the first mile of a Retrieval-Augmented Generation (RAG) system. Before retrieval, chunking, or embedding can work, raw
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Evaluating RAG Systems: A Complete Guide to Metrics and Best Practices
Retrieval-augmented generation (RAG) promises answers grounded in an external knowledge base. In practice, an answer can be wrong because the
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How to Debug a RAG Workflow Practically
Imagine you are fixing a restaurant order pipeline. A customer says, “My order is wrong.” That sentence alone does not
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When to Use RAG, and When Prompting or Fine-Tuning is Better
Think of four analysts preparing for an executive meeting. One analyst brings nothing and relies on memory. Another crams all
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Anthropic’s 4D Framework of AI Fluency Made Easy
Imagine you have just hired a brilliant consultant. Highly experienced, available around the clock, knowledgeable across dozens of fields. You
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Data Drift vs Concept Drift
Consider a spam filter trained in 2010. By 2020, users receive far more promotional newsletters than before. The types of
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When Not to Use an AI Agent
AI agents are often used where a script, workflow, or simpler model would do the job better. If the task
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DINO and DINOv2 Made Easy: Self-Supervised Visual Learning from Intuition to Foundation Models
Paper: DINO: Emerging Properties in Self-Supervised Vision Transformers (Caron et al., 2021), DINOv2: Learning Robust Visual Features without Supervision (Oquab
ConvNeXt Made Easy: A ConvNet for the 2020s
Paper: A ConvNet for the 2020s (Liu et al., 2022), ConvNeXt V2 ConvNeXt modernizes the classic convolutional neural network (CNN)
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Swin Transformer Made Easy: A Hierarchical Vision Transformer with Shifted Windows
Paper: Swin Transformer: Hierarchical Vision Transformer using Shifted Windows (Liu et al., 2021), Swin Transformer V2: Scaling Up Capacity and
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