theLernen AI — Learn 1000 Words
Master 1000 most frequent words in 4 languages with AI
What it does
Forget dry grammar rules. theLernen AI uses Zipf's law to teach you the 1000 most frequent words covering 85% of daily speech in German, English, Japanese, and Polish. Powered by spaced repetition (SM-2) and Gemini AI, it explains every word in context with real-life examples at A1-B1 levels. Play through 7 engaging learning modes (Flashcards, Quizzes, Anki export, etc.). 100% free, no sign-up required. Start understanding real conversations in just 30 days!
Does a similar job
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Hi guys, Hope everyone is well. This app was borne out of my own frustration. I thought that I was terrible at learning languages at school, since I didn't become conversational in French after 5 years of study. However, I later traveled with some French friends and, in just under 3 weeks, I was able to hold a reasonable conversation. I realized that there's no substitute for speaking to native speakers. I tried to adopt this approach for other languages, but it's much harder to find people to practise with when you aren't travelling. I started using iTalki to meet people from different…
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Hello Hacker News, When learning foreign languages, I made the most progress by speaking them throughout the day, every day. So I made a site where you can *speak* to an AI language teacher to practice both listening and speaking. # The product *What I have now:* * Multilingual speech recognition: You can ask a question in English and get an answer in your target language. * Feedback on your grammar. * Suggestions: See examples of what to say next to keep the conversation flowing. * Speed: Choose a lower speed for beginners or a faster one for advanced levels. * Translations: Click to see a…
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I'm Tim. I speak German, English, French, Turkish, and Chinese. I learned Turkish with lairner itself -- after I built it. That's the best proof I can give you that this thing actually works. The other four I learned the hard way: talking to people, making mistakes, reading things I actually cared about, and being surrounded by the language until my brain gave in. Every language app I tried got the same thing wrong: they teach you to pass exercises, not to speak. You finish a lesson, you get your dopamine hit, you maintain your streak, and six months later you still can't order food in the…
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Depending on the language, the top 1,000 most frequently used words account for ~85% of all speech and text, and the top 5,000 account for ~95%. It’s really important to learn these words. Learning words in context helps you naturally understand their meaning and use cases, while avoiding the rote memorization of definitions. ListLang helps you achieve fluency by learning the 5,000 most frequently used words in context. Most language learning apps never move past beginner level content. This method requires some basic knowledge, but otherwise it should rapidly increase your level past the…
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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.
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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