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Today, I released FSRS v4.6.2. In one year ago, I submitted my first commit for FSRS.
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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Recently, I have run three comparisons for spaced repetition algorithms. They included SM-15, SM-17, SM-2, HLR, LSTM and FSRS series. The initial result shows that FSRS v4 beats all other algorithms in predicting probability of recall. It's a good news that the open-source algorithm can overperform SuperMemo's proprietary algorithm.
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Recently, I have run three comparisons for spaced repetition algorithms. They included SM-15, SM-17, SM-2, HLR, LSTM and FSRS series. The initial result shows that FSRS v4 beats all other algorithms in predicting probability of recall. It's a good news that the open-source algorithm can overperform SuperMemo's proprietary algorithm.
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Recently, I have run three comparisons for spaced repetition algorithms. They included SM-15, SM-17, SM-2, HLR, LSTM and FSRS series. The initial result shows that FSRS v4 beats all other algorithms in predicting probability of recall. It's a good news that the open-source algorithm can overperform SuperMemo's proprietary algorithm.
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Besides, dae, the lead developer of Anki, helped me integrate FSRS into Anki. We have merged FSRS Optimizer into Anki's main branch. The beta package will be released in a few weeks.
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Anki-Android
AnkiDroid: Anki flashcards on Android. Your secret trick to achieve superhuman information retention.
Good news again, AnkiDroid has completed its Rust backend update. FSRS will be supported in AnkiDroid in 2.17.