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Quantization in Plain English: 8‑bit, 4‑bit, and What You Lose

Quantization in Plain English: 8‑bit, 4‑bit, and What You Lose

  • Post author:Filip Lapiński
  • Post published:October 5, 2025
  • Post category:Local & Edge AI

Model Quantization Explained: Why It Matters and How to Do It Right Reduce model size and latency with safe quantization—learn trade-offs, methods, validat

Continue ReadingQuantization in Plain English: 8‑bit, 4‑bit, and What You Lose
Metadata Matters: Tags that Supercharge Retrieval

Metadata Matters: Tags that Supercharge Retrieval

  • Post author:Filip Lapiński
  • Post published:October 4, 2025
  • Post category:RAG & Knowledge Retrieval

Metadata and Tagging Best Practices for Retrieval Better metadata makes assets findable and usable — improve retrieval accuracy, reduce friction, and deplo

Continue ReadingMetadata Matters: Tags that Supercharge Retrieval
Chain‑of‑Thought Alternatives: 6 Safer Reasoning Tricks

Chain‑of‑Thought Alternatives: 6 Safer Reasoning Tricks

  • Post author:Filip Lapiński
  • Post published:October 3, 2025
  • Post category:Prompting & Workflows

Practical Techniques to Reduce AI Hallucinations Proven steps to minimize AI hallucinations, improve factuality, and increase trust in outputs — practical

Continue ReadingChain‑of‑Thought Alternatives: 6 Safer Reasoning Tricks
What Makes a ‘Parameter’? A Non‑Math Guide to Model Size

What Makes a ‘Parameter’? A Non‑Math Guide to Model Size

  • Post author:Filip Lapiński
  • Post published:October 2, 2025
  • Post category:AI Fundamentals

What a "Parameter" Means for Machine Learning Models Understand what a parameter is, how parameter count affects model behavior, and practical steps to pic

Continue ReadingWhat Makes a ‘Parameter’? A Non‑Math Guide to Model Size
Ollama vs. LM Studio vs. cloud APIs: Picking Your Runner

Ollama vs. LM Studio vs. cloud APIs: Picking Your Runner

  • Post author:Filip Lapiński
  • Post published:October 1, 2025
  • Post category:Tools & Ecosystem

Choosing a Local LLM Runner: Ollama vs LM Studio vs Cloud APIs Decide the best LLM runner for your product: balance performance, latency, cost, and securit

Continue ReadingOllama vs. LM Studio vs. cloud APIs: Picking Your Runner
Consent Flows: Collect, Withdraw, Audit

Consent Flows: Collect, Withdraw, Audit

  • Post author:Filip Lapiński
  • Post published:September 30, 2025
  • Post category:Privacy, Law & Governance

How to Define, Collect, and Manage Consent Across Your Systems Practical guidance to define consent scope, collect clear permissions, and enforce user choi

Continue ReadingConsent Flows: Collect, Withdraw, Audit
Structure Your Posts for Rich Results (HowTo/FAQ/Article)

Structure Your Posts for Rich Results (HowTo/FAQ/Article)

  • Post author:Filip Lapiński
  • Post published:September 29, 2025
  • Post category:Search/SEO & Content

How to Add Structured Data for Google Rich Results (HowTo, FAQ, Article) Add the right structured data to earn rich results, improve CTR, and guide search

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Generating Synthetic FAQs for Cold‑Start RAG

Generating Synthetic FAQs for Cold‑Start RAG

  • Post author:Filip Lapiński
  • Post published:September 27, 2025
  • Post category:Data & Synthetic Data

How to Build Synthetic FAQs with Retrieval-Augmented Generation (RAG) Create high-quality synthetic FAQs using RAG to improve search, support, and content

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AI for Recruiters: Faster, Fairer Screening

AI for Recruiters: Faster, Fairer Screening

  • Post author:Filip Lapiński
  • Post published:September 26, 2025
  • Post category:Vertical Use‑Cases

AI-Powered Candidate Screening: Goals, Metrics, and Implementation Define measurable screening goals, deploy targeted AI for faster, fairer candidate selec

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Receipt & Invoice Parsing: A Practical Playbook

Receipt & Invoice Parsing: A Practical Playbook

  • Post author:Filip Lapiński
  • Post published:September 25, 2025
  • Post category:Multimodal (Vision/Audio)

Document Data Extraction: Goals, Strategy, and Implementation Checklist Define clear goals, pick the right extraction strategy, and implement a robust pipe

Continue ReadingReceipt & Invoice Parsing: A Practical Playbook
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