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Dec 07, 2024 4 min read AI & Machine Learning

Building Production-Ready RAG Systems with Python and Vector Databases

Retrieval-Augmented Generation (RAG) has become the go-to approach for building AI applications that need accurate, contextual responses. I've built several RAG systems in production, and here's what I learned about making them reliable, fast, and maintainable.

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Dec 06, 2024 1 min read AI & Machine Learning

My Home AI Lab Setup — GPU Computing for Local LLMs

From experimenting with speech-to-text to training lightweight predictive models, I've created a personal AI lab at home powered by high-end consumer hardware. The goal? Run local LLMs, real-time voice agents, VLMs, and GPU-accelerated automation workflows without relying on cloud costs.

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Dec 05, 2024 3 min read AI & Machine Learning

Building Generative AI Workflows with Gemini Pro 3: From Prototype to Production

Google's Gemini Pro 3 represents a major leap in multimodal AI capabilities. I've integrated Gemini Pro 3 into production workflows for content generation, code assistance, and intelligent automation. Here's how to build scalable AI workflows that leverage its advanced reasoning and multimodal understanding.

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Dec 02, 2024 4 min read AI & Machine Learning

Edge AI and Compact Models: Running Generative AI on Resource-Constrained Devices

Not every AI application needs cloud-scale infrastructure. Edge AI and compact models like Nano-sized language models enable generative AI on devices with limited resources. I've deployed AI workflows on Raspberry Pi, embedded systems, and low-power servers—here's how to optimize models for edge deployment.

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