Context: There is a close connection between machine learning and compression: a system that predicts the posterior probabilities of a sequence given its entire history can be used for optimal data compression (by using arithmetic coding on the output distribution) while an optimal compressor can be used for prediction (by finding the symbol that compresses best, given the previous history). This equivalence has been used as a justification for using data compression as a benchmark for "general intelligence."

Question: What is Machine learning closely related to?
Answer: compression

Question: What type of compressor can be used for prediction?
Answer: optimal

Question: What has been used as a benchmark for "general intelligence"?
Answer: data compression

Question: What type of compressor can be used for general intelligence?
Answer: Unanswerable

Question: What can a benchmark compressor be used for?
Answer: Unanswerable

Question: What has a close connection to machine equivalence?
Answer: Unanswerable

Question: What can be used for optimal justification?
Answer: Unanswerable

Question: How is an arithmetic compressor used for prediction?
Answer: Unanswerable