February 18, 2026
Accio Copyright Chaos
Microsoft offers guide to pirating Harry Potter series for LLM training
Microsoft's AI demo uses full Harry Potter books—fans yell 'WTF'
TLDR: Microsoft’s tutorial showcased AI built on full-text Harry Potter books from Kaggle to make Q&A and fanfic. Commenters erupted over piracy concerns, debated whether rights holders care, and feared AIs might recreate entire novels, with some archiving the page expecting a takedown—raising big questions about AI and copyright.
Microsoft quietly dropped a step-by-step AI tutorial that uses the full text of the Harry Potter books from Kaggle, and the internet immediately cast the spell Accio controversy. The walkthrough shows how to slice the novels, feed them into an AI (a large language model), and build a Potter Q&A or even auto-generate fan fiction. Cue gasps, swears, and a flurry of copyright side-eye. One commenter flat-out screamed "what in the absolute…?" while others wondered why J.K. Rowling’s team hasn’t swooped in with legal owls yet.
Some viewers shrugged that Warner Bros. and the Potter empire make so much money they won’t chase a "plain text copy," likening it to Star Wars scripts floating around. But the spiciest thread asked the scary question: what happens when AI can recreate entire books word-for-word? One user imagined an online library that prompts an AI to reconstruct bestsellers with 100% accuracy. Another dropped an archive link “in case the page disappears,” like they’re bracing for a takedown.
Between the "is this piracy?" camp and the "big studios don’t care" crowd, the mood was chaotic, meme-y, and very Hogwarts-meets-law-firm. Microsoft’s tech flex became a fandom/legal drama, with fans joking about lawyers sharpening wands while devs whisper, “but the demo is kinda cool…”
Key Points
- •Microsoft added native vector search to Azure SQL and SQL in Microsoft Fabric.
- •The langchain-sqlserver package enables SQL Server/Azure SQL as a LangChain Vectorstore.
- •A tutorial demonstrates building Q&A and fan-fiction features using a Harry Potter text dataset from Kaggle.
- •Workflow steps include loading from Azure Blob Storage, chunking with langchain-text-splitter, and generating embeddings via Azure OpenAI.
- •Similarity search with optional metadata filters retrieves context for answers from the vector store.