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www.sheshbabu.com
| | bdtechtalks.com
9.2 parsecs away

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| | Retrieval augmented generation (RAG) enables you to use custom documents with LLMs to improve their precision.
| | www.s-anand.net
17.5 parsecs away

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| | I built podcast generator app in one-shot. I wrote a prompt, fed it to an LLM, and it generated the output without errors. I tested three LLMs, and all produced correct, working output. It still took me an hour to craft the prompt - even after I'd built a Python prototype and my colleague built [...]
| | www.augmentedmind.de
15.5 parsecs away

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| | Learn how to use LLMs (AI) to boost your shell productivity, having it generate shell commands or scripts, integrated right into your shell.
| | lancecarlson.com
86.6 parsecs away

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| Imagine a system that not only stores data but grasps its very essence. A system that can swiftly navigate through myriad data points to pinpoint the most relevant. That's the power of vector databases. They're tailor-made for QA systems, acting as memory boosters for large language models. Their ability to seamlessly link questions to exact answers showcases their pivotal role in modern AI. I'm going to show you how you can setup your very own vector database using Ruby on Rails so you can ask your data questions!