Alternatives
Products that do what How much of the Linux kernel is written by AI? does
- 1AA
I pretty much always have a kernel project going on, and have been that way for decades. Over the past couple of years, that's been Anos, which has gotten further along than any of my previous hobby kernels, supporting IPC, multitasking, SMP (x86-64 only right now) and running on real hardware. LLMs (mostly Claude Code) have been used during development, but I learned early on that it's not _great_ at code at this level, so I've restricted its use to mostly documentation and tests. There's _a little_ AI code in the user space, but I have a strict "no AI code" rule in the kernel itself. I…
Apr 2026 · github.com
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2021 · github.com
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2014 · github.com
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A 3.16M-parameter INT4 transformer running entirely in the on-chip memory of a Xilinx Kria KV260. Zero DRAM in the token loop, 59,965 tok/s on the fabric, bit-exact. Chat with it live.
27d ago · mikeayles.com
- 11AK
Mar 2026 · github.com
- 12IM
This is a personal project I've been working on and off for the past few years. It's a set of tools that have allowed me to prototype quickly small (and increasingly bigger) kernels, and create userspace programs to interact with them. Supports riscv64, amd64 and i386. The intel port has been tested and used on real hardware, from big dual-socket Xeon machines to an old X220. It is all C, I have plan to make rust bindings for the kernel library. But again, they're plans at this stage. Porting to new architectures is relatively simple, a basic port to riscv took me a couple of weeks of…
2024 · github.com
- 13IB
You know that old TI calculator you used in high school, then put in a box and forgot about? Have you ever wished you had an operating system for your calculator with preemptive multitasking, dynamic memory management, a tree filesystem conforming to the FHS, and all the comforts of Unix? Well, good news: that's totally a thing that exists. I've been working on my kernel for about three and a half years now and I'm looking for new contributors to help out. It's written entirely in z80 assembly, and it's both challenging and fun to work on. There's an IRC channel for contributors or people…
2014
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2023 · github.com
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Democratisation of local AI is key. I've been working on pushing the limits of commercial hardware, squeezing any extra bit possible. My Scientific Agentic AI hareness helped me to reallocate every single bit of it. I rewrote the Kernel, I went down the CUDA rabbit hole until I have been able to explain any bit and any ms of computational power involved in the process pushing the Qwen 30B-A3B from 8 tok7s to 19 tok/s with llama.cpp up to 22.2 tok/s with my project and 109 tok/s on not novel content and speeding up the prefill by 5-9X
Jul 2026 · github.com
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Jan 2026 · github.com
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Hello HN! I'm an Android OS engineer. I've worked with AOSP and Linux kernels all my career and always wondered about lack of sophisticated tools to debug and analyze system-level logs. Always had to resort to manually skimming through large log files to find something I needed to. With the rise of LLMs and the AI-age, I felt it was a great opportunity to build something for OS engineers, which is what led to logcat.ai! We are building the industry-first observability platform for system level intelligence. Think "Datadog for operating systems" instead of applications. Currently, we support…
2025 · logcat.ai
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2023 · kernelconfig.io
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Been working on data sovereignty recently and started this list. Hope you can contribute too.
2025 · github.com
- 22AA
Aug 2026 · github.com
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We've built InferX, a specialized runtime environment that fundamentally changes how LLMs are served. The core problem we solve is the latency bottleneck in AI inference, especially with large models. Current systems waste resources or suffer from painfully slow cold starts. InferX's AI-native architecture, with its "snapshot" technology, enables: * *Sub-2s cold starts:* Spin up models instantly. * *High density:* Serve more LLMs on the same GPUs. * *Optimal efficiency:* Maximize GPU utilization. This isn't just another API; it's a new execution layer designed from the ground up for the…
2025 · github.com
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I wanted to build an inference provider for proprietary AI models, but I did not have a huge GPU farm. I started experimenting with Serverless AI inference, but found out that coldstarts were huge. I went deep into the research and put together an engine that loads large models from SSD to VRAM up to ten times faster than alternatives. It works with vLLM, and transformers, and more coming soon. With this project you can hot-swap entire large models (32B) on demand. Its great for: Serverless AI Inference Robotics On Prem deployments Local Agents And Its open source. Let me know if anyone…
Nov 2025 · github.com
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