Cricket Coach AI
AI-powered cricket technique analyser
What it does
AI-powered cricket technique analyser — upload a video, get instant pose-based feedback with angle overlays, smart auto-pause, and frame-level coaching. No subscription. No coach required. 📸 What It Looks Like Upload video → AI analyses every frame → Top 3 issues surfaced → Video auto-pauses at the exact wrong moment → Angle arc drawn on screen: "Knee: 142° — too BENT (needs 150–165°)" → Click Continue → slow-mo trail shows the joint moving incorrectly → Coaching tip + drill appears below
Does the same job
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I made SABR - an AI model that helps you visualize the beta/technique on any route, based on your body parameters. You can input a video of you climbing any route, in any orientation or lighting condition (it's truly versatile!). SABR then creates a virtual avatar of your body shape and uses it to climb the route you're climbing. Then, you can compare/contrast. You can see the demo here: https://www.youtube.com/watch?v=cnvNPWoYZz4 Will be open sourcing the model, backend, and frontend codebase soon!
More ai this month
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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.
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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