
Hanzi Easy
Grow Chinese Vocabulary
What it does
Learn Chinese characters faster—with less effort. This app helps you build Chinese character recognition in a way that feels simple, focused, and sustainable. 1. A focused, immersive learning experience 2. Low-pressure learning that sticks 3. Swipe-based learning that feels engaging 4. 3,500 Chinese characters included
Does the same job
all alternatives →

- AAAn “automatic” way to learn Chinese2018 · play.google.com · ▲57

- LCLearning Chinese and Japanese with graphs and trees2024 · github.com · ▲9
Just for fun, I built a language learning tool. It represents Chinese and Japanese as graphs of characters, with connections indicating given characters can form a word. It can also decompose characters to give clues on how they're pronounced, analyzes words to understand which ones are commonly used together, and more. It's fully interactive, supports offline use, generates flashcards, has sentences from humans and from AI, and plenty of other features. Check out the README for details. https://github.com/mreichhoff/HanziGraph
- JLJinbuPal – Learning Chinese doesn't have to be difficult2023 · jinbupal.com · ▲21
My co-founder and I built a Chinese language learning web app that helps you quickly master the most common Chinese characters and recognize 95% of real content. JinbuPal uniquely enhances learning for maximized progress by allowing effortless personalization of your daily study. When I dreamed up JinbuPal, I was a maker just like others in the HN community. I was working on my electronic hardware startup and I thought that learning the fundamentals of Chinese would help me communicate with manufacturers in Shenzhen. We designed JinbuPal to help you leverage data and your own curiosity to…
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Parallel agents, diff reviewer, and multi-model comparisons
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- 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…
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