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Engineers Are 10x Faster with AI, Why Aren’t We Seeing 10x More SaaS?
No AI used in this post.
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How to design a RAG System : A Boilerplate
🎥 Watch the demo on Vimeo GitHub Link A RAG system that is : Chunking with propositional model + late chunking, and simple recursive overlap retrieval Using Qdrant as a Vector DB, utilising its hybrid search (BM25 + Dense Search) Reranks via LLMs Using qu…
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Clever Chunking Methods Aren’t (Always) Worth the Effort
I was reading about fancy chunking strategies on RAG systems.
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Information Retrieval Fundamentals #1 — Sparse vs Dense Retrieval & Evaluation Metrics: TF-IDF, BM25, Dense Retrieval and ColBERT
Information Retrieval could be defined as a field of study interested in ways to finding relevant material of an unstructured nature (usually text) from a collection of data (i.e.: files stored in your file system) to satisfy user information need.
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LLM-SQL Tools
I reviewed SQL-LLM-Agent tools and libraries, sorted by GitHub stars.
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LLM Interviews : Hosting vs. API: The Estimate Cost of Running LLMs?
I’ll use any resource that helps me to prepare faster.
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LLM Interviews : Prompt Engineering
I’ll use any resource that helps me to prepare faster.
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LLM Interviews : Vector DBs
I’ll use any resource that helps me to prepare faster.
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GPT1 Implemented with NumPy : Generate Jokes
I love implementing DL algorithms with NumPy, it’s best way to learn the engine.
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Easy-to-use NoSQL Prompt Database for Small Projects
Ever needed a database for your LLM project that: Your project isn’t really big You don’t have to expose your prompts to business team, and even you are not really changing frequently.