Self‑Supervised Learning

Learning signals are derived from the data itself (e.g., next‑token prediction), enabling large‑scale pretraining without manual labels.

Supervised Learning

Training models on labeled examples (input, desired output) to learn mappings, common for classification and regression tasks.

SFT, Supervised Fine‑Tuning

Fine‑tuning a pretrained model on instruction/response pairs to teach task formats and improve helpfulness before alignment steps like RLHF.

Rehypothecation

Practice where custodians or lenders reuse client assets as collateral for their own borrowing, a risk factor in centralized crypto finance if not transparently disclosed.

Rollback

Reverting a chain’s state to a prior block height. Generally avoided in public chains except during reorgs or critical incidents with community consensus.

Ring Signature

Privacy‑preserving signature scheme where a signer is indistinguishable within a group, used in some cryptocurrencies to hide the true signer.

RBF, Replace‑By‑Fee

Bitcoin mempool policy allowing an unconfirmed transaction to be replaced with a version that pays a higher fee, improving confirmation reliability under congestion.

Rate Limiting

Controlling the number of requests a client can make in a period, protecting RPCs or APIs from abuse and helping ensure fair access.

RANDAO

On‑chain randomness mechanism where participants commit to and reveal random values, combined to produce an unpredictable beacon for consensus or leader selection.

Rust

Systems programming language with strong safety guarantees and performance, widely used for blockchain clients, provers, and smart contracts on some chains.

RSA

Public‑key cryptosystem based on the difficulty of factoring large integers; used for signatures, encryption, and randomness beacons in some protocols.

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