Arda Baysallar·Nov 3I wanted subtitles for my own life. I built the app in two days.A phone app that catches me up in German, an AI coding agent, and the afternoon it got humbled.
Arda Baysallar·Oct 31Most Security Cameras Try to Show You More. I Built One That Shows Me Less.A hobby-kit chip, a tiny neural network, and one very short email.
InAxonect BlogbyAxonect Engineering·Oct 21TinyML: Bringing Machine Learning to the Edge of PossibilityBy Ruvindi Mudalige
Abioye Oluwadamilola Joy·Oct 13How I Wrote My Very First Edge AI Research Proposal (And What I Learned Along the Way)To be completely honest, writing a formal research proposal was completely new ground for me.
Abioye Oluwadamilola Joy·Oct 9Why Shrinking AI for Edge Devices Can Go Wrong (And What I Learned)Everyone is talking about putting artificial intelligence directly onto tiny devices things like smart thermostats, farm sensors, or…
Mehmet Özgen ÖZDOĞAN·Oct 7Taking AI From the GPU Rack to a Coin-Cell Battery: Micro AI on ESP32-Class HardwareEverything in this series so far has been about more — more VRAM, more machines, more GPU sharing. This post goes the opposite direction on…A response icon1A response icon1
InStackademicbyAbhinandan Bhadauria·Oct 4Gaming Meets AI: Why the Future of Edge Computing Looks a Lot Like a 90s Game Console 🎮🤖How a classic design philosophy solves the biggest headache in bare-metal TinyML deployment.
A Manav Prasath·Oct 2Space Complexity in IoT Devices — Low memory constraints.How O(1) thinking, streaming algorithms, and careful memory management keep constrained devices running
Lahiru Udayakumara·Sep 30Machine Learning on an ESP32: Building TinyML Systems at the EdgeWhen we think about machine learning, we usually picture powerful GPUs, cloud servers, and models containing billions of parameters.
Daniel Brown·Sep 24The Ananse Reports: TinyML Reality Check, Part III: What It MeansPart III turns Report №1 into hardware guidance: model file size is not SRAM use, latency and energy point to different boards, and…
