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KAKimkpe Arnold Sylvianarnold8kimkpe.hashnode.devJun 17 · 11 min read

Training and Deploying a Custom Bird Detector on the Google Coral Dev Board Micro

Why I Started This Project I have been exploring TinyML and edge AI because I am interested in how machine learning can move from notebooks and cloud servers into real physical devices. It is easy to

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Bbl4zeh3xbl4zeh3x.hashnode.devJun 17 · 7 min read

Two Mistakes Hiding Behind One Good-Looking Number

I'm starting an Electronics and Communication Engineering degree this year, and a few weeks before classes began I decided to build something instead of waiting for a syllabus to tell me what to learn

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DADavid Aronchickdistributedthoughts.orgMay 5 · 9 min read

Edge ML Has a Size Obsession

UPS could deliver your Amazon package on a cargo e-bike. In most cities, for most packages, this would actually be faster. No parking. No traffic. Straight to your door. Instead, a 16,000-pound truck idles outside your apartment building while the dr...

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OWOliver Wengedge-insights.hashnode.devApr 8 · 6 min read

🚀 Edge AI & Efficient Computing | Bi-Weekly News: # 2

🎉Welcome to the second post of Edge AI & Efficient Computing! 👋 I’m Yuqin (Oliver) Weng, and I’m incredibly passionate about pushing the boundaries of AI on constrained devices. 🧠I created this spa

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NNavindanavindatinyml.hashnode.devApr 4 · 6 min read

TinyML in 2026

Welcome to my first blog on Hashnode! I'm starting this series to explore TinyML ,a field that's quietly transforming how we think about artificial intelligence. Let's begin. What is TinyML? Remember

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OWOliver Wengedge-insights.hashnode.devMar 23 · 7 min read

🚀 Edge AI & Efficient Computing | Bi-Weekly News: # 1

🎉Welcome to the very first edition of Edge AI & Efficient Computing! 👋 I’m Yuqin (Oliver) Weng, and I’m incredibly passionate about pushing the boundaries of AI on constrained devices. 🧠I created t

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AAuckamauckamzone.hashnode.devMar 11 · 7 min read

TinyML vs Traditional Embedded Design: Key Differences Engineers Should Know

Why Engineers Are Re-Thinking Embedded Design Today Can microcontrollers run machine learning reliably without cloud dependency or high power consumption? That question is now shaping modern embedded

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CMCharan Manikanta Nallamlnotes.devDec 26, 2025 · 3 min read

Day 1 Of Learning ML: Choosing A Path To Machine Learning

Introduction Today’s Day 1 of learning Machine Learning. So, I picked up a course called “Introduction to TinyML,” to start learning ML. This course is a little bit special, compared to your other ML courses. TinyML is about Machine Learning on Embed...

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CMCharan Manikanta Nallamlnotes.devDec 23, 2025 · 3 min read

My Starting Point

I’m writing this just to leave some clarification as to where exactly I’m starting. Identifying where you’re starting might help with understand which parts you can do well and which ones you need improve on, such that you can learn whatever that is ...

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IInfolksinfolks.hashnode.devOct 8, 2025 · 5 min read

TinyML & Edge AI: How Lightweight AI Models Are Reshaping IoT Devices

Did you know that by 2030, more than 25 billion IoT devices will be connected worldwide (Statista)? Imagine if each of those devices, whether your smartwatch, home sensors, or even farm drones, could think and act intelligently without relying on the...

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Trending tags this week

Training and Deploying a Custom Bird Detector on the Google Coral Dev Board Micro

Two Mistakes Hiding Behind One Good-Looking Number

Edge ML Has a Size Obsession

🚀 Edge AI & Efficient Computing | Bi-Weekly News: # 2

TinyML in 2026

🚀 Edge AI & Efficient Computing | Bi-Weekly News: # 1

TinyML vs Traditional Embedded Design: Key Differences Engineers Should Know

Day 1 Of Learning ML: Choosing A Path To Machine Learning

My Starting Point

TinyML & Edge AI: How Lightweight AI Models Are Reshaping IoT Devices