Alternatives
Products that do what Luxonis – OAK 4: spatial AI camera that runs Linux, with up to 52 TOPS does
Hey everyone. This is Hunter, CPO at Luxonis! We built OAK 4 (www.luxonis.com/oak4) to eliminate the need for cloud reliance or host computers in robotics & industrial automation. We brought Jetson Orin-level compute and Yocto Linux directly to our stereo cameras. This allows you to run full CV pipelines (detection + depth + logic) entirely on-device, with no dependency on a host PC or cloud streaming. We also integrated it with Hub, our fleet management platform, to handle deployments, OTA updates, and collect "edge case" (Snaps) for model retraining. For this generation, we shipped a…
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Hi HN, I built a specialized inference engine for running 4-bit Gemma 4 26B-A4B-IT on any M-series Mac using about 2 GB of RAM. It is called TurboFieldfare and is written in Swift and Metal. I have always adored on-device AI. It feels like magic that you can run a powerful NN on your Mac or iPhone. So I wanted to push the limits a bit and run a model whose weights don’t fit in memory. The model’s 4-bit quantized weights occupy roughly 14 GB, which makes running it with conventional inference tools almost impossible on an 8 GB or even 16 GB Mac once the OS, applications, and KV cache are…
Jul 2026 · github.com
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We wrote our inference engine on Rust, it is faster than llama cpp in all of the use cases. Your feedback is very welcomed. Written from scratch with idea that you can add support of any kernel and platform.
2025 · github.com
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After building several Tauri desktop apps, I kept hitting the same wall: there's no reliable way to access cameras across Windows, macOS, and Linux. Every project meant reinventing camera integration, dealing with platform-specific APIs, and debugging permission issues. So I built CrabCamera – a Tauri plugin that handles all the camera complexity for you. What it does: - One API, three platforms: Same Rust code works on Windows (DirectShow), macOS (AVFoundation), and Linux (V4L2) - Permission handling: Automatically requests camera permissions on each platform - Format conversion: Takes care…
Sep 2025 · crates.io
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Jun 2026 · github.com
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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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I have been working on making WebRTC + Embedded Devices easier for a few years. This is a hackathon project that pulled some of that together. I hope others build on it/it inspires them to play with hardware. I worked on it with two other people and I had a lot of fun with some of the ideas that came out of it. * Extendable/hackable - I tried to keep the code as simple as possible so others can fork/modify easily. * Communicate with light. With function calling it changes the light bulb, so it can match your mood or feelings. * Populate info from clients you control. I wanted…
2025 · 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
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Hello Hacker News! We're Yangqing, Xiang and JJ from lepton.ai. We are building a platform to run any AI models as easy as writing local code, and to get your favorite models in minutes. It's like container for AI, but without the hassle of actually building a docker image. We built and contributed to some of the world's most popular AI software - PyTorch 1.0, ONNX, Caffe, etcd, Kubernetes, etc. We also managed hundreds of thousands of computers in our previous jobs. And we found that the AI software stack is usually unnecessarily complex - and we want to change that. Imagine if you are a…
2023 · lepton.ai
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Optimizes, delivers and manage images to improve performance
2020
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It's our new text-to-image model: a 9.3B single-stream diffusion transformer trained entirely from scratch. We focused heavily on controllability through structured JSON prompts, with strong text rendering, spatial awareness through bounding box guidance, and color palette control. It has the best text rendering of any open-weight model we've tested so far, and the NF4 quantized checkpoint runs on a single 24GB GPU. For more technical details and examples see our blog post: https://ideogram.ai/blog/ideogram-4.0/ We will be happy to answer any questions :)
Jun 2026 · github.com
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I made my first macOS utility app that ships with a bundled Gemma 4 model, specifically the Gemma E4B one. It made my app DMG have 5.3 GB in size, but I think it is a small size for the power that this free local model can provide. It runs fine on CPU, but can also run on Apple Silicon GPU, although I did not notice any performance improvements with GPU (tested on a M5 chip). I think these local lightweight and multimodal models will open multiple possibilities for new software tools where privacy is essential.
May 2026 · snapname.app
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Jul 2026 · github.com
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The excitement surrounding PrismML’s 1-bit/ternary Bonsai models has the industry closely watching how smartphone giants, particularly Apple, will implement LLMs on edge devices. Moving AI on-device is a brilliant and necessary strategy. It ensures absolute user privacy in alignment with EU regulations, fundamentally shifts the economics away from costly cloud inference, and paves the way for a significant hardware upgrade supercycle as users seek true AI-capable silicon. To create a smart on-device "Semantic Router," models need to reach the 27B+ parameter scale. Achieving this on a…
Jul 2026
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Hey HN! I just released a suite of AI models for deployment on UAV and other "overhead" devices to provide some understanding of the world below. The objective is to empower all sorts of open-source use cases around search and rescue, wildfire prevention, ground risk mitigation for flight over populated areas etc... The neural networks are trained for a bunch of different devices from big GPUs to tiny edge AI cameras like the Luxonis OAK, with some optimised ones for Nvidia TensorRT and other cool bits and pieces too. The main release package also includes some boilerplate code for running…
2023 · github.com
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