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Products that do what I Built an AI Drone Controller does
Hey HN! I'm someone who both flies and programs drones. I've often struggled to make my drones perform perfectly, especially when the environment changes like a gust of wind. To solve this, I’ve trained ML Models to replace the Control Loops currently in charge of controlling most drones. These models perform better than Control Loops, require no tuning, and retain this performance in many more situations than Control Loops. Requiring no tuning also means that the same model can be used for multiple different drones/configurations, so it works out of the box. A high level model is also…
- 1IB
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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Hi HN, I'm the creator of this project. For the past months, I've been working on building an AI agent that could move beyond simple generation and tackle inventive challenges autonomously. The core idea was to create a system with a "metacognitive loop"—the ability to recognize when it's stuck on a fundamental problem and then launch a sub-mission to solve that specific bottleneck before continuing. The linked article is a deeper introduction to the system's architecture and a snapshot from a recent run. I tried to design it to be evidence-grounded and self-critical to avoid the pitfalls of…
2025 · robw1se.substack.com
- 6IB
Hi HN, I built ChatOne while working on a project and constantly switching between AI models like GPT-4 and newer ones like Claude 3.5. I kept wondering if I was missing out on better answers, so I created ChatOne to get responses from multiple models at once and compare them easily. -Teddy
2024 · chatone.io
- 7MC
Hey HN - I built ModelGuessr, a game where you chat with a random AI model and try to guess which one it is. A big open question in AI is whether there's enough brand differentiation for AI companies to capture real profits. Will models end up commoditized like cloud compute, or differentiated like smartphones? I built ModelGuessr to test this. I think that people will struggle more than they expect. And the more model mix-ups there are, the more commodity-like these models probably are. If enough people play, I'll publish some follow-up analyses on confusion patterns (which models get…
Dec 2025 · model-guessr.com
- 8WB
Hey HN, After GPT-3 created waves in the tech industry, a lot of AI tools were emerging and with that, some AI website builders But the results seemed way too generic to us. It felt like the developers were rushing to catch the wave instead of building a proper tool We took our time, did months of RnD and finally came up with something better than what others in the market are doing. It’s got better design output. While it’s still in beta, I wanted to show HN what we did. Will appreciate the feedback when you guys try it out. Here is the link to signup for the beta:…
2024 · dorik.com
- 9TN
Hi guys, I’m excited to share an update on ReproModel, an open-source toolbox designed to streamline the testing and reproduction of machine learning models. I, like many of you, have really struggled with benchmarking and comparing models, from missing code, to opaque experiment parameters slowing the process. I decided to take matters into my own hands, and created a mini-toolbox in my free time to streamline the process. The goal is to reduce the time and effort spent on replicating experiments, enabling researchers to focus on innovation rather than setup. Knowing this task is not an…
2024 · github.com
- 10AO
Hey HN, My workflow for any complex queries is to ask it in multiple AI chats (Gemini, Claude, o3,..) in parallel and then continue the conversation with the chat response that I found the most useful. I built a simple open source app that queries 10+ AI models at once and summarizes their answers with a selected combiner AI model. There's a GIF in the github repo that shows it in action. You can try it on your local machine: https://github.com/Nexarithm/multi_model_chat If you are interested, I also made a detailed blog post on technical details, feature of the personal…
2025 · github.com
- 11AB
Hello HN, new user here, so please let me know if I break some rules. Currently I've been working on training reinforcement learning agents, and OpenAI gym, while is great, runs only one agent at a time. Hence I decided to extend it. I built a wrapper around OpenAI gym, such that it now runs several environments concurrently. All while (mostly) having the same call signature as OpenAI gym. And it is published to PyPI for anyone interested. For more details, please visit: https://github.com/Chimpan-Z/agymc Feedback really appreciated! Have a good day everyone!
2020
- 12AA
Combining (1) open-source autopilots with (2) open-source ROS2 simulation/navigation/mapping packages and (3) open-source, hardware-accelerated computer vision should not be hard, but it is. aerial-autonomy-stack aims to solve this by collapsing (1) multi-robot, (2) software-in-the-loop, (3) hardware-in-the-loop simulation, (4) CI/CD, and (5) deployment into a single containerized workflow. The end-to-end stack can be re-created/simulated with a one-liner (45') build on Ubuntu >=22.
Jun 2026 · github.com
- 13WB
Hi everyone, We have been developing a platform to enable professionals to build AI assistants to help them through their work. After a few months, we realized people are trying to sell basic functionalities that can be built from scratch in a couple of hours. Due to this, individuals who are not familiar with the current SOTA are misinformed about the potential of generative models. So, we decided to open up some of our most popular templates as standalone tools for free to empower individuals and set a solid standard for what people should expect. We believe the barrier to accessing…
2024 · join.modularmind.app
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I built SpecMind, an open source developer tool for spec driven vibe coding. It keeps architecture and implementation aligned from the first commit instead of letting them drift apart. With AI assistants writing more of our code, projects move faster but architectural consistency is often lost. Each developer or AI can introduce new patterns, and after a few sprints, the structure becomes fragmented. SpecMind helps prevent that by generating and maintaining living architecture specs directly from your code. It works in three steps: 1. analyze – scans your codebase and generates…
Nov 2025 · github.com
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Hi there, looking for feedback on my new project "Featherless.AI" The idea is to allow users to run all the models on hugging face instantly. Via the OpenAI API compatible endpoint. Why? Because its a real chore to download models and spin up GPUs, especially if you want to test multiple models. Not to mention GPUs cost multiple dollars an hour to rent. And if we want more people to use open source AI, we got to make it easier for them to try and play with all of them. So what if instead of spinning up dedicated GPUs per model (which is what every provider is doing) We can startup a LLM…
2024 · featherless.ai
- 17IB
Hello everyone, I doubt this would be relevant to the kind of person who uses HN, but I thought I could share for some feedback. I built this site because there is a whole world of people who believe in new age spirituality and I am very much one of them. It is a site where you get the users gender their goals and their images and use AI and psychology to generate images of them in the process of achieving their goals. I am so deeply struggling with how to get this highly on Google. I don't even know if that is important anymore. What are your suggestions with distribution and getting in…
2025 · visionboardsai.com
- 18LT
Hey I'm Kieran and I've been playing with the intersection (pun intended) of generative AI and civil engineering for roadways. I did a test run training a LoRA on the new Flux 2 Dev model using Fal's trainer useing a custom dataset of paired images from publicly available striping CAD drawings of street layouts to aerial images of the same area. The use case here is to allow urban planners to instantly visualize their proposed changes as they work with their existing tooling. This was just a quick experiment with a small data size that exceeded my expectations so I wanted to share with you…
Jan 2026
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Hi folks, I built this guide after watching AI agent prototypes repeatedly fail in production. It demonstrates transforming a monolithic marketplace assistant into a resilient multi-agent system using orra, an open-source platform I also built for production-ready multi-agent applications. The patterns shown are valuable *even if you're building your own orchestration layer*. Each stage builds on the previous one, showing the evolution from fragile prototype to resilient system. What makes this guide valuable: * Architectural transformation with working code examples - split monolithic…
2025 · github.com
- 20IM
Hey HN! Thank you for all the support and feedback on my original submission 2 months ago. I've been improving the backend using a MCTS/AlphaZero approach and it's currently producing much better results. My long term goal is to allow users to manage multiple projects, deployed autonomously, both from scratch and by making continual updates all prompted with natural language. The cost of each project has been lowered to $9 as performance with smaller models has improved (I migrated from Claude-3-Opus to gemini-1.5-flash). Thanks for checking it out!
2024 · saas-quick.com
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Hi HN, I built this to address what I see as the fundamental problem with ReAct-style agents: compounding errors. Even a small mistake made early enough in the loop can snowball and ruin the final output. But with search, agents can look multiple steps ahead and backtrack before committing to a particular trajectory. This has already been shown in a few papers to help agents avoid mistakes and boost overall task performance, but there's no easy way to actually build these kinds of agents. So that's why I made this framework. I believe search will eventually become table stakes for building…
2024 · github.com
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Hey HN, it’s Russ - cofounder of LiveKit. An open source stack for building realtime AI applications. We’re sharing our first homegrown AI model for turn detection. Here’s a live demo: https://cerebras.vercel.app/ Voice AI has come a long way in the last year. We now have end-to-end systems that can generate a response to user input in 300-500ms — human level speeds! As latency reduces, a common problem that surfaces is the LLM responds too quickly. Any time there’s a short pause in a user’s speech, it ends up interrupting them. This is largely due to how voice AI applications…
2024
- 23CS
Tired of copy-pasting the same question across ChatGPT, Claude, Gemini, and Grok to find the best answer? I built ChatHawk to solve this exact problem: Ask once and get responses from all top AI models simultaneously, plus an AI-generated combined answer that pulls the best insights from each. Perfect for when you need accurate answers (verified across models), strategic decisions, or multiple AI perspectives. Stop the tedious switching between platforms – get comprehensive AI insights in one place. What questions would you want to run through all models at once?
Oct 2025 · chathawk.co
- 24PA
Hello Hacker News! I am Bertrand from Pruna AI. With my associates, John, Rayan, and Stephan, we are fellow researchers in AI efficiency and reliability coming from TUM. We are building an optimization engine that combines compression methods (e.g. quantization, pruning, compilation, batching…) in the aim of saving compute power when running AI models. This optimization engine take one base model as input and returns a compressed model as output. It aims to help for two things: - Make various AI models faster and/or smaller for various hardware (because they can require significant…
2024
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