AI
5 stories
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AIEdge AI Computing: Bringing Intelligence Closer to the Data
An introduction to Edge AI Computing, why inference is moving closer to devices, and how to design practical edge AI systems.
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AI
LLM Inference Optimization: Cutting Latency Without Sacrificing Quality
Practical techniques for speeding up large language model inference in production — quantization, batching, KV-cache tuning, and hardware choices.
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AI
Building RAG Systems That Actually Work in Production
Lessons from shipping retrieval-augmented generation pipelines — chunking strategies, embedding choices, reranking, and evaluation.
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AI
Fine-Tuning Open Models: A Practical Guide for Small Teams
How to fine-tune open-weight models on a budget — data prep, LoRA vs full fine-tune, evaluation, and when not to fine-tune at all.
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AI
Computer Vision on Edge Devices: Models, Frameworks, and Trade-offs
How to deploy object detection and classification models on cameras, drones, and embedded hardware using TensorFlow Lite, ONNX, and OpenVINO.