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The point of my homelab is replacing subscriptions. Family photos that used to live in a cloud photo service now live on a drive I own. Documents that used to mean an hour digging through a shoebox now OCR themselves into something searchable. Everything running here is cheaper, more private, or more useful than what it replaced, and usually all three.
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Everything in this post is illustrative. The scenarios are constructed to teach patterns; nothing here describes any specific system, plant, or employer.
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Most AI ships behind an API. The model lives on hardware the operator controls, upgrades happen in one place, and when something breaks, an engineer with dashboards is already looking at it.
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Everything in this post is illustrative. The scenarios are constructed to teach patterns; nothing here describes any specific system, plant, or employer.
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The deepfake detection literature has a distribution problem. The models exist, the papers are good, and almost nobody outside a lab can run any of it. Every research repo ships its own broken environment, its own weight files on a link that dies within a year, and its own Python version requirement. Meanwhile the fakes ship as consumer apps. DeepSafe is my attempt to fix that: take the best open detectors, make them run in one place, and put a single URL in front of them. The code is open source. This post is about how the engineering works, down to the import system and the calibration math.
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For the past year a team of ten of us has been building a 3D bioprinter during our undergrad. I lead the project. It’s called BioP, it swaps a desktop printer’s plastic filament for soft gels, and it has taught me more engineering than every course I’ve taken combined. This post is an account of what building it involves, with the numbers.
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For the past three years most of my pocket money has gone into foam. Foam board, thermocol sheet, hot glue, cheap servos, and propellers bought in fives because they break in fours. This is a look back at the aircraft years, with the numbers behind the builds, written while the last of the fleet still hangs from the hostel ceiling.
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Last month at Quark our table held three machines: the submarine, the wall-drawing plotter, and a 3D scanner built mostly out of 3D printed parts. This post is about the scanner, the geometry that makes it work, and the part the kit documentation skips, which is everything after assembly.
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We built a submarine out of PVC pipe. It’s called Vandubbi. It’s a wireless remotely operated underwater vehicle with a live video feed, and we showed it at Quark, our campus technical festival, earlier this month. This is the build story, with the numbers, while I still remember the details.
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Last week at Quark, on the library lawns, a whiteboard drew the Batman logo on its own while people ate breakfast around it. Behind it were two stepper motors, two cords, a pen in a 3D printed carriage, and a laptop. The machine is called Bono. It’s our version of the polargraph, a wall-drawing robot, and this post is about how it works, the math that decides where it can draw, and what we learned building it.