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Show HN: A language model that lives in a boot sector All the ideas came from the boot sector demo scene where people had been writing chess and BASIC games in 512 bytes, even a C compiler. I wondered what one can do using a neural network instead of a program and generating boot logs for non-existent hardware was something fun to try. Entire inference engine is 510 bytes of MBR, weights, vocab, and strings reside in the sectors following MBR. Small char-level neural network was trained on dmesg generated by machine, so machine produces Linux boot messages infinitely. train.py performs precisely the same integer arithmetic operations as the asm code does and thus produces an output identical character-by-character to the one produced by QEMU. The difference analysis revealed my favorite bug. The characters at the beginning matched those generated by the simulator, but then the output diverged. I retrieved the hidden layer via QEMU’s debug port and compared the neurons' values with ...

Show HN: I rebuilt Kubernetes for ESP32 microcontrollers https://ift.tt/K1XONGR October 29, 2026 at 10:05PM

Show HN: Pho – TUI for GitHub PRs https://ift.tt/IBRlDMS October 30, 2026 at 12:32AM

Show HN: SLCR – An open standard for agent-native software requirements https://slcr.dev/ October 29, 2026 at 10:13PM

Show HN: I built a map of billboards and banners in Poland (gpy.pl) https://gpy.pl/ October 29, 2026 at 01:24AM

Show HN: Measuring how much of an AI-assisted design is yours https://ift.tt/ilbXgNS October 29, 2026 at 12:11AM