The task at hand is drawing the circuit schematics for a robot I'm working on. I had already written down the components and the connections, all that's left is to draw it in KiCad. I had already started doing that, but then... I got sidetracked forcing Gemini to create the circuit using KiCad. I would have made progress if I had continued doing it by hand. I spent yesterday trying to generate an
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Building AI calling agents shouldn't require a commercial license or massive per-minute markups. If you are a Python developer, you should be able to spin up a sub-500ms latency voice agent on your own machine. Prerequisites Python 3.10+ A Twilio or Telnyx SIP Trunk LiveKit Credentials An OpenAI API Key First, clone the Siphon repository and install the requirements. pip install siphon-ai Next, c
This is part three of a series on display consistency in embedded systems. The first two parts were technical. This one is about why the technical parts worked. The picture: ATtiny85 thermometer. Neural network inference. QUAD7SHIFT display. Built from datasheets. He had datasheets. No Stack Overflow. No libraries to install. No AI to generate boilerplate. No tutorials that abstracted away the in
If you've ever used a bottleneck calculator, you've probably seen a simple percentage telling you whether your CPU or GPU is holding your system back. But here’s the truth most people don’t realize: Bottlenecks are not fixed numbers — they are dynamic, workload-dependent behaviors. In this post, we’ll go beyond basic tools and break down how CPU and GPU bottlenecks actually work in real-world scen