Generally AI - Season 2 - Episode 4: Coordinate Systems in AI and the Physical World
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Oct 23, 2024
Delve into fascinating discussions about coordinate systems in AI and the physical world. Explore the evolution from traditional library research to AI-driven tools that enhance information retrieval. Learn about the complexities of high-dimensional spaces, cosine similarity, and efficient search algorithms. Discover the historical significance of mapping, including challenges with the Mercator projection and unique systems like the Netherlands' triangle coordinates. Hear about the tragic outcomes related to mapping inaccuracies in the UK post office scandal.
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question_answer ANECDOTE
Library Research
Students used libraries and card catalogs to research topics like the Great Pyramid of Egypt.
They'd find call numbers to locate books on shelves, mimicking an index search.
insights INSIGHT
ChatGPT and RAG
ChatGPT can write essays but often lacks proper citations and may not be historically accurate.
Retrieval Augmented Generation (RAG) helps by retrieving relevant content to improve accuracy and add sources.
insights INSIGHT
RAG and Embeddings
RAG assigns a 'call number' to prompts, allowing it to retrieve relevant information.
It uses encoders to map text into vector spaces, finding similar meanings through proximity.
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In this podcast, Roland Meertens and Anthony Alford discuss coordinate systems, both in AI and the physical world. They explore how a library's classification systems mirror the concept of embeddings in AI, where documents are organized based on similarity and how AI tools like RAG use vector spaces to efficiently retrieve the right content. They then discuss physical coordinate systems and how different countries have developed various schemes to represent the Earth’s surface, such as the UK's Ordnance Survey and the Netherlands' Rijksdriehoekscoördinaten.
Read a transcript of this interview: https://bit.ly/3A6oUsL
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