Memorang has developed AIBL (Artificial Intelligence Based Learning), a proprietary system that combines advances in machine learning, cognitive science, pedagogy, personalization, and real-world constraints to make learning any topic more effective and time-efficient. In developing this system, we have leapfrogged many "spaced repetition" algorithms. While we can't share all the inner workings of AIBL, we can describe at a high level what is going on underneath the hood with respect to knowledge acquisition and retention.
Knowledge acquisition
When a student is first presented with content, AIBL determines whether this needs to be learned or if it is "pre-learned." If an item is not pre-learned, we use various techniques such as interleaving, over-learning, contextual variability, many-to-many connections, speed, relevancy, and confidence to calculate the appropriate "mini-spacing" intervals within the study session to achieve mastery. For example, if you are trying to memorize the side effects of certain drugs, AIBL will appropriately repeat certain facts multiple time within the same session in order to confidently assess them as "mastered."
Knowledge retention
Once an item is "mastered" it can now be forgotten. In order to prevent this from happening, AIBL uses dozens of "signals" to estimate the rate of decay for each item, for each learner, for each point in time. These signals include data such as previous performance, time intervals, estimated mastery score, confidence, related items, other learners' performance on the same items, and many, many other variables. Once AIBL determines that an item is at "risk" of being forgotten by crossing the forgetting threshold, it becomes "due" as part of your daily task.
Prioritization
In a world of learning where there's too much to know and too little time to study, AIBL ranks the relative importance of different items you've learned to help you focus. This is most important in case you miss a few days in your schedule and need to catch-up. Unlike other learning systems, AIBL will not overwhelm you with an insurmountable backlog of learning tasks. Instead, AIBL will smartly choose which items to review next and prompt you to come up with a plan to get back on track. For example, it may ask if you want to study extra today, or if you want to expand your daily study duration by a few minutes between now and your end goal date.