Anki AI Utils

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Anki AI Utils

Hi hn, I am nearly at the end of medical school so it is time I publish and "advertise" my open source scripts/apps for anki! Here's the pitch: Anki AI Utils is a suite of AI-powered tools designed to automatically improve cards you find challenging. Whether you're studying medicine, languages, or any complex subject, these tools can: - Explain difficult concepts with clear, ChatGPT-generated explanations. - Illustrate key ideas using Dall-E or Stable Diffusion-generated images. - Create mnemonics tailored to your memory style, including support for the Major System. - Reformulate poorly worded cards for clarity and better retention. Key Features: - Adaptive Learning: Uses semantic similarity to match cards with relevant examples. - Personalized Memory Hooks: Builds on your existing mnemonics for stronger recall. - Automation Ready: Run scripts daily to enhance cards you struggled with. - Universal Compatibility: Works across all Anki clients (Windows, Mac, Linux, Android, iOS). Example: For a flashcard about febrile seizures, Anki AI Utils can: - Generate a Dall-E illustration of a toddler holding a teacup next to a fireplace. - Create mnemonics like "A child stumbles near the fire, dances symmetrically, has one strike, and fewer than three fires." - Provide an explanation of why febrile seizures occur and their diagnostic criteria. Call for Contributors: This project is battle-tested but needs help to become a polished Anki addon. If you’re a developer or enthusiast, join us to make these tools more accessible! Check out my other projects on GitHub: [Anki AI Utils]( https://github.com/thiswillbeyourgithub ) Transform your Anki experience with AI—because learning should be smarter, not harder.

Visit product View on Hacker NewsDec 28, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, apps, chatgpt · Missing: agents, macos, agent

67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: ios, including · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · Missing: https docs, excited, just released

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: ios, personal, apps · Missing: mobile apps, entrepreneurs, video

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, smart · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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