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RRishikantrishiii2.hashnode.dev5d ago · 6 min read

AeroGuard AI: Transcending Convolutional Architectures in Drone Surveillance

Building an autonomous, military-grade drone surveillance system introduces a specific class of problems that standard computer vision tutorials rarely cover. The project, codenamed AeroGuard AI, was

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RRishikantrishiii2.hashnode.devJul 3 · 8 min read

Revolutionizing 5G Networks with Intelligent Reconfigurable Surfaces and Deep Reinforcement Learning

The transition to fifth generation cellular networks marks one of the most significant leaps in telecommunications history. Unlike previous generations that relied heavily on sub six gigahertz frequen

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SCSiddharth Chaudharyblog.siddharthchaudhary.com.npJul 2 · 14 min read

How Neural Networks Learned to Remember — RNNs, LSTMs, and GRUs

It’s an afternoon of a beautiful summer day. You just learnt about backpropagation, gradients and artificial neural networks and you think you’ve unlocked some forbidden treasure of knowledge granted

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AGAlper GÖÇENinsideaimodels.hashnode.devJun 29 · 2 min read

Free from-scratch deep learning notes: tensors, attention, and a tiny GPT

I'm an AI PhD student, and I have started writing a free public notebook on how AI models work under the hood: https://insideaimodels.com/ The goal is to make the mechanics easier to reason about, wit

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RRishikantrishiii2.hashnode.devJun 29 · 5 min read

Bonus Chapter: Conquering Edge AI with the NVIDIA Jetson Nano

Throughout our 18-part Masterclass, we have operated with the luxury of infinite compute. We trained massive neural networks using high-end GPUs in the cloud, unconstrained by power limits or hardware

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RRishikantrishiii2.hashnode.devJun 28 · 6 min read

From Hardware to Edge AI: My Journey with the NVIDIA Jetson Nano

Have you ever wondered how autonomous robots "see" the world, or how a camera can instantly recognize your face without relying on an internet connection? The answer lies in Edge AI—running artificial

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OHOmer Hayatepoch.hashnode.devJun 26 · 10 min read

Backpropagation from First Principles: What I Finally Understood

Backpropagation becomes much less mysterious once you stop seeing it as “the algorithm that trains neural networks” and start seeing it as the chain rule moving backward through a computation graph. K

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MSManuela Schrittwieserneuralstackms.techJun 25 · 7 min read

Sentinel-LLM: A Hybrid Guardrail Architecture for OWASP LLM06 – Sensitive Information Disclosure

Published on NeuralStack | MS · AI Security Engineering · June 2026 Every production LLM deployment carries a category of risk that is simultaneously well-understood in theory and chronically under-e

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FIfor IT theieee-projects.hashnode.devJun 9 · 47 min read

Top 5 Super Resolution Datasets (LR-HR Pairs) Every Computer Vision Researcher Must Know

Introduction What Is Image Super Resolution Image Super Resolution (SR) is the computational task of reconstructing a high-resolution image from one or more low-resolution observations. The goal is to

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NSNeeloppher Syedneeloppher.hashnode.devJun 6 · 8 min read

Carbon-Aware Model Training: Scheduling GPU Workloads Around Electricity Carbon Intensity

Training ML models has an environmental cost that most practitioners do not measure. A model trained during peak grid hours, when coal and gas plants are meeting high demand - can emit significantly m

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#pytorch

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Trending tags this week

AeroGuard AI: Transcending Convolutional Architectures in Drone Surveillance

Revolutionizing 5G Networks with Intelligent Reconfigurable Surfaces and Deep Reinforcement Learning

How Neural Networks Learned to Remember — RNNs, LSTMs, and GRUs

Free from-scratch deep learning notes: tensors, attention, and a tiny GPT

Bonus Chapter: Conquering Edge AI with the NVIDIA Jetson Nano

From Hardware to Edge AI: My Journey with the NVIDIA Jetson Nano

Backpropagation from First Principles: What I Finally Understood

Sentinel-LLM: A Hybrid Guardrail Architecture for OWASP LLM06 – Sensitive Information Disclosure

Top 5 Super Resolution Datasets (LR-HR Pairs) Every Computer Vision Researcher Must Know

Carbon-Aware Model Training: Scheduling GPU Workloads Around Electricity Carbon Intensity