Axiom Flow
Learn by teaching an AI that gets it wrong
What it does
Axiom Flow is an edtech platform where you master topics by teaching an AI student named Sam. Upload notes, paste text, or use YouTube to create a session. Sam generates thoughts filled with misconceptions, and your job is to correct them through conversation. If your explanation is incomplete, Sam asks questions until it’s clear. Then send Sam to a mock exam to see how well you truly understand.
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I think graph is a wrong abstraction for building AI agents. Just look at how incredibly hard it is to make routing using LangGraph - conditional edges are a mess. I built Laminar Flow to solve a common frustration with traditional workflow engines - the rigid need to predefine all node connections. Instead of static DAGs, Flow uses a dynamic task queue system that lets workflows evolve at runtime. Flow is built on 3 core principles: * Concurrent Execution - Tasks run in parallel automatically * Dynamic Scheduling - Tasks can schedule new tasks at runtime * Smart Dependencies - Tasks can…
- AAAxiom – A math-native OS where x² is valid syntax (built from scratch)Feb 2026 · fawazishola.ca · ▲20
Hi HN, I'm a 19-year-old aerospace student. I spent the last 13 months building a custom Linux distro from scratch because I wanted to see if we could treat the OS kernel as a mathematical engine rather than a deterministic administrator. The Stack: Flux (The Shell): A custom math-native shell where x² and ∑ are valid syntax. It parses mathematical notation directly into optimized SIMD instructions (no Python wrapper). Tenet (The Scheduler): Written in Tenet (my custom DSL for game theory). The scheduler is a Nash Equilibrium solver compiled to native code. In my benchmarks (Ryzen 7 5800HS),…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 18d ago · simedw.com
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AI · 19d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
