Show HN: Watch 14-Byte AI "brains" attempt to solve a 2D maze (Its hard) https://ift.tt/Vo4N5RC

Show HN: Watch 14-Byte AI "brains" attempt to solve a 2D maze (Its hard) Hey HackerNews, I built this project over the last few weeks as a palette cleanser from a failed game launch. I wanted to learn a bit about AI/Neural-Networks and naively thought I could build a tiny maze-solving AI in a weekend with a 100% solve rate. Well - I couldn't, but I got pretty close. 14 Bytes total model size, and a 96.5% solve rate on unseen mazes. Trained across 46 phases experimenting with different ideas to improve the model (better performance, smaller size). Its quite fun to watch the model attempt to solve the maze, when they fail its usually due to getting stuck in a loop. The models have no access to coordinates, map-data, or external memory scratches - they must navigate using only immediate local neighbourhood observations. There is a model dropdown and you can see how the model has progressed over each phase, constantly getting smaller and increasing its solve rate. Total trained models number in the thousands - I just expose the winning models from each phase. Overall a fun experiment, with much implementation help from AI agents to scaffold and implement the code (I'm a lazy software dev). https://con-dog.github.io/MINIMIO-PUBLIC-FRONTEND/ July 27, 2026 at 04:15AM

Show HN: Descript wanted $24/mo, I built an open-source alternative in a weekend https://ift.tt/o8vmLhN

Show HN: Descript wanted $24/mo, I built an open-source alternative in a weekend Descript costs $24/mo, so I built this over a single weekend with Fable! Introducing Rescript: edit videos by simply editing the transcript text. Drop in a video and it is transcribed locally with per-word timestamps and speaker labels. Delete words in the transcript and the corresponding clip is cut from the video. Runs fully in the browser: Local, free, offline and open source. → Github https://ift.tt/FY6WL2I → App https://wassgha.github.io/rescript https://ift.tt/FY6WL2I July 27, 2026 at 03:22AM

Show HN: ASL V6 – Open-source AST red-teaming engine for Python AI agents https://ift.tt/OWVu5Cf

Show HN: ASL V6 – Open-source AST red-teaming engine for Python AI agents https://ift.tt/iL3Tuj0 July 27, 2026 at 12:50AM

Show HN: What 180k words look like as a temporal knowledge graph (Oz series) https://ift.tt/uEeJAPN

Show HN: What 180k words look like as a temporal knowledge graph (Oz series) The graph is free to explore and requires no registration. SynapTale builds a model of a story as a temporal graph made up of nodes (entities) and edges (their actions and relationships). The graph is not a visualization of the wiki. The wiki, timelines, relationship histories, and analytics are projections of the graph. The current demo contains 232 entities, 1,852 edges, and a snapshot of the story’s state at every chapter. By chapter 100, it still remembers a promise made in chapter 8 and turns the story into a set of source-verifiable facts. The most interesting things can be found in the graph itself and in the Analytics tab. A few things I found: 1. The character with the highest kill count is the Tin Woodman—the same character who cries over a beetle he accidentally crushed. Dorothy comes second, with three killing events. 2. Dorothy never deceives anyone during the first 100 chapters of the series. 3. The Scarecrow’s debt to the stork has remained active for 92 chapters, starting in chapter 8. 4. The Cowardly Lion ranks third by number of threats. 5. The first 100 chapters contain 60 secrets and 254 dialogue events. Technical details 1. Five different multi-agent pipelines combining LLMs and NLP: a prescan, ontology construction, chapter-by-chapter graph extraction, retrospective validation over spans of dozens of chapters, and a linguistic prescan for speech profiles and linguistic edges. 2. A living story needs a living graph. It has to account for time, because entities and the relationships between them evolve. A simple is_active field is not enough. I ended up with three types of edges: event: an instantaneous action; identity: a fact; state: a persistent action whose termination requires justification and a supporting quote from the text. The vast majority of edges are events and end in the same chapter in which they began. This allows the system to scale well, since only a minority of state and identity edges remain continuously active. 3. Ontology. You cannot simply ask an LLM to extract entities and relationships into a graph. With every chapter, even the smartest model will keep inventing unimportant fields, creating new aliases for existing fields, and representing the same fields inconsistently. Before extracting the graph, the system therefore performs an ontology scan across the entire story. It captures story-specific entity and edge types, along with their fields and descriptions. 4. Epistemics. Events are only one part of a story. It is also important to understand how information is distributed, which is difficult to represent using event edges alone. I addressed this by introducing a new node type: epistemic nodes, which capture different entities’ perspectives on the same fact. Subtle hints can still be missed, the system is not yet perfect in this area. https://ift.tt/1EM49dm July 25, 2026 at 11:18PM

Show HN: Nostalgia – A shareable Windows 98 desktop builder https://ift.tt/kyVdUiG

Show HN: Nostalgia – A shareable Windows 98 desktop builder https://ift.tt/YMdHuv7 July 25, 2026 at 05:57AM

Show HN: WhipDesk – Control your full dev machine from your phone https://ift.tt/OqkjJB3

Show HN: WhipDesk – Control your full dev machine from your phone Hi HN, I built WhipDesk, an open-source, mobile-friendly remote desktop tool for controlling your full development machine and managing AI coding agents from your phone’s browser. It gives you access to the entire desktop while also adding workflows for monitoring and managing tools such as Claude Code, Codex, GitHub Copilot, and others The two questions I hear most are: How is it secured, and how is it different from existing tools? Security Following the modern approach taken by open-source remote access tools such as RustDesk, WhipDesk is fully open source, so its client, agent, protocol, and security model can be inspected rather than trusted as a black box. Local connections can run entirely within your network without an account. Remote connections use end-to-end encrypted WebRTC. Most connections are peer-to-peer; when a TURN relay is required, it only forwards encrypted traffic. Each connection also requires the machine’s access PIN as an additional security layer. More details are available in the GitHub README. Why not Claude Code, Codex, or other agent remote-control tools? Those tools are useful for interacting with the agent session, but sometimes I need access to the rest of the machine: the IDE, browser preview, emulator, logs, desktop applications, or the UI the agent just changed. WhipDesk gives you access to the full development environment directly from your mobile browser, regardless of which coding agent is running. That is why I built it: I did not want to be limited to a single agent interface. Why not TeamViewer, RDP, or RustDesk? Traditional remote desktop tools work, but they are usually designed for controlling one large desktop from another computer. On a phone, text can become difficult to read, and they do not include workflows specifically designed for monitoring and managing coding agents. WhipDesk is designed specifically for mobile browsers. It can stream only the selected mobile viewport, keeping text crystal clear when zoomed in and allowing it to work well on lower-bandwidth connections. I built it because I often need to step away from my desk while agents are still working. I use it to answer prompts, inspect UI changes, review progress, and course-correct from my phone. Source and installation: https://ift.tt/xE5F8DN npm install -g whipdesk I’d especially appreciate feedback on your first impression. Building a tool that requires this level of user trust has been challenging, and I would love to improve it based on honest feedback. https://ift.tt/xE5F8DN July 24, 2026 at 11:49PM

Show HN: Forje Studio – data-driven design and motion, entirely client-side https://ift.tt/Th7N3i4

Show HN: Forje Studio – data-driven design and motion, entirely client-side https://ift.tt/qPi2bMf July 24, 2026 at 05:36AM