F1 Virtual Engineer
F1 analytics, Motosport Engineering
What it does
Most people watch F1 for the racing and Netflix dramas. I built this for people who watch the data. Built for sim racers, engineering students, analysts, and fans obsessed with the technical side of Formula 1. Still developing and open to feedback.
Does the same job
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- UFUndercutf1 – F1 Live Timing TUI with Driver Tracker, Variable Delay2025 · github.com · ▲301
undercutf1 is a F1 live timing app, built as a TUI. It contains traditional timing pages like a Driver Tracker, Timing Tower, Race Control, along with some more detailed analysis like lap and gap history, so that you can see strategies unfolding. I started to build undercutf1 almost two years ago, after becoming increasingly frustrated with the TV direction and lack of detailed information coming out of the live feed. Overtakes were often missed and strategies were often ill-explained or missed. I discovered that F1 live timing data is available over a simple SignalR stream, so I set out…
- FCF1 COSMOS – Live timing and data dashboard for F1 fans2025 · f1cosmos.com · ▲8
Hey everyone! I'm a huge F1 fan and got tired of juggling multiple tabs and apps during race weekends, so I built F1 COSMOS. What it does: - Live timing: Real-time data updates in milliseconds - sector times, telemetry, team radio, you name it. No more refreshing pages or waiting for delayed updates. - Replay feature: Missed qualifying or fell asleep during practice? You can replay the live timing from any past session. Pretty handy when you're in a bad timezone. - Proper data visualization: I went beyond just showing lap times. There's race analysis with telemetry data, championship…
More ai this month
the category →
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 · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d 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
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com