SuperMemo

Definition:

SuperMemo is the first computer-based spaced repetition software, created by Piotr Wozniak in Poland beginning in 1985. It introduced the concept of algorithmic SRS scheduling — automating the review timing manual systems like the Leitner System did by hand — and produced the SM-2 algorithm that became the foundation for Anki and most modern SRS tools.

Also known as: SM (shorthand in SRS communities), the Wozniak system

In-Depth Explanation

SuperMemo emerged from Wozniak’s personal self-experiment: dissatisfied with the rate at which he forgot things he studied, he began tracking his own retention of biology and English vocabulary, recording review dates and recall accuracy manually. This data allowed him to model his own forgetting curve empirically — not from published tables, but from his actual memory behavior. He derived interval schedules from this data: an item recalled correctly after 1 day should next be reviewed after approximately 7 days; if recalled correctly then, approximately 16 days, and so on. This cumulative, individually calibrated approach was the core innovation.

Wozniak formalized these observations into SM-0 (a hand-written schedule), then progressively into software versions: SM-2 (1987) became the most widely known because it was mathematically clean enough to be reimplemented by others, and because Wozniak published the algorithm openly. SM-2 uses a per-card “easiness factor” that adjusts based on rated recall quality (0–5 scale), applying a formula to calculate the next interval. This formula was hand-tuned to Wozniak’s own data but proved to generalize reasonably well across learners and material types.

SuperMemo continued to evolve through many algorithm versions: SM-5 introduced a matrix-based model; SM-8 used neural networks; SM-11 through SM-18 progressively increased personalization and algorithm complexity. The later algorithms are substantially more sophisticated than SM-2 but also significantly harder to reimplement independently — one reason SM-2 propagated while newer versions did not.

SuperMemo’s key historical importance is threefold:

1. It proved that algorithmic scheduling based on empirical memory data could produce dramatically better retention than manual study methods.
2. SM-2’s public documentation enabled Anki and dozens of other tools, seeding a global SRS ecosystem.
3. Wozniak’s ongoing research and writing on spaced repetition, memory, and learning methodology at supermemo.com continues to influence SRS theory.

SuperMemo today is a Windows desktop application with a focused development community. It has never achieved the mainstream adoption of Anki, primarily due to its proprietary nature, Windows-only availability for much of its history, and a learning interface that prioritizes power over accessibility.

Common Misconceptions

“SuperMemo and Anki are the same.”

They share a scheduling lineage (Anki’s SM-2 derives from SuperMemo’s SM-2), but SuperMemo has continued developing its algorithms through SM-18+ with substantially more sophistication than Anki’s original SM-2 implementation. Modern SuperMemo and modern Anki (with FSRS) are different products with different algorithms, interfaces, and communities.

“SuperMemo is obsolete because Anki exists.”

SuperMemo’s current algorithms (SM-17, SM-18) are arguably more sophisticated than any publicly available SRS algorithm. Wozniak and his team have continued active research and development. For power users willing to invest in its interface, SuperMemo remains technically competitive and is the origin of much SRS research that tools like FSRS now build upon.

“You need SuperMemo to use SM-2.”

SM-2’s formula was published openly and is reimplemented in dozens of tools, most famously Anki. The algorithm that most people use when they use “SM-2” is Anki’s reimplementation of Wozniak’s 1987 formula, not SuperMemo itself.

Criticisms

SuperMemo has been critiqued for its proprietary nature, steep learning curve, dated interface, and the complexity of its later algorithms (SM-15, SM-18) which are not fully disclosed. While Piotr Woźniak’s research on spaced repetition is foundational, the software itself has been largely superseded in the language learning community by Anki (which adapted SM-2) and more recently by FSRS-based tools.

Social Media Sentiment

SuperMemo is recognized in language learning communities as the pioneer of spaced repetition software, though most learners today use Anki or other more accessible tools. Discussions about SuperMemo often focus on Piotr Woźniak’s extensive writings about memory and learning optimization. The SuperMemo website’s “Guru” content on sleep, learning, and memory is occasionally shared and discussed.

Last updated: 2026-04

History

• 1982–1985: Piotr Wozniak begins manually tracking his own vocabulary and biology study to model his forgetting curves empirically. He derives the first hand-written interval schedule (SM-0) from this personal data. This is the empirical foundation on which SuperMemo is built.

• 1985: First software version of SuperMemo (SM-1) is developed as a DOS program. Wozniak optimizes interval schedules using his expanding personal database of learning data.

• 1987: SM-2 algorithm is developed and incorporated into SuperMemo. It is the most well-known version: mathematically simple, openly documented, and effective. SM-2’s core formula — easiness factor, interval multiplier, reset-on-failure — becomes the template for Anki and most other SRS implementations.

• 1991: SuperMemo World is founded as a company in Poland. SuperMemo begins commercial distribution.

• 1990s–2000s: Algorithm versions progress through SM-5 (matrix model), SM-8 (neural network elements), and into the teens. Each version uses more learner data and more sophisticated statistical models to improve scheduling accuracy. SuperMemo also develops into a comprehensive knowledge management system beyond simple flashcards.

• 2006: Damien Elmes releases Anki using SM-2. Anki’s free, open-source, cross-platform nature achieves mainstream adoption that SuperMemo’s proprietary model never did, but Anki’s success is built entirely on SuperMemo’s algorithmic foundation.

• 2022–present: FSRS — the next generation of SRS scheduling — is philosophically grounded in SuperMemo’s two-component memory model (Piotr Wozniak‘s theoretical work on memory retrievability and stability). SuperMemo continues active development under Wozniak’s direction.

Practical Application

• Understand SuperMemo’s historical importance as the birthplace of computerized spaced repetition algorithms
• For practical use, newer tools like Anki (with FSRS) offer more accessible interfaces with comparable or improved scheduling
• Read SuperMemo’s freely available articles on memory and learning theory for foundational understanding of SRS principles
• If using SuperMemo, leverage its incremental reading feature — a unique capability for processing large amounts of reading material
• Apply the core insight from SuperMemo’s research: consistent, spaced review dramatically outperforms massed study for long-term retention

Related Terms

• SRS (Spaced Repetition System)
• SM-2 (SuperMemo 2)
• FSRS (Free Spaced Repetition Scheduler)
• Anki
• Forgetting curve

See Also

• Piotr Wozniak
• Damien Elmes
• Leitner System
• Spacing effect
• Long-term memory

• Sakubo

Research

• Wozniak, P.A. (1990). Optimization of learning [Master’s thesis]. University of Technology, Poznan. https://www.supermemo.com/en/archives1990-2015/english/ol
  Summary: Wozniak’s primary documentation of SuperMemo’s methodology and the SM-2 algorithm — the original source. Explains the empirical basis for the interval formula, the easiness factor, and the design choices that made SM-2 both practical and replicable.

• Wozniak, P.A., & Gorzelanczyk, E.J. (1994). Optimization of repetition spacing in the practice of learning. Acta Neurobiologiae Experimentalis, 54, 59–62.
  Summary: Academic analysis of SuperMemo’s spacing approach, providing empirical evidence that algorithmic scheduling produces measurably better retention than manual review in controlled conditions.

• Wozniak, P.A. (1995). Economics of learning. supermemo.com. https://supermemo.com/en/blog/economics-of-learning
  Summary: Wozniak’s analysis of the return on investment of spaced repetition study — quantifying how much time SRS saves over conventional study for equivalent retention. Foundational for understanding the practical efficiency case for SuperMemo and SRS generally.

• Wozniak, P.A. (1995). Two components of long-term memory. supermemo.com. https://www.supermemo.com/en/blog/two-components-of-long-term-memory
  Summary: The two-component model of memory (retrievability and stability) that Wozniak developed from SuperMemo data — the theoretical foundation that FSRS later operationalized with machine learning. Essential for understanding how modern SRS algorithms conceptualize memory.