Blockchain Finality, Monetary Policy, Transformer Architecture, and Verifiable AI Infrastructure
Blockchain Finality
Finality describes the confidence that a transaction or block will not be reversed, supported by the network's consensus process and economic incentives.
FinalityConsensus ClientValidatorSlashing
- Finality: Finality is the point at which a blockchain transaction or block is considered highly unlikely to be changed or removed.
- Consensus Client: A consensus client is software that communicates with peers and applies a blockchain network's rules for agreeing on valid blocks.
- Validator: A validator is a network participant that helps propose or confirm blocks according to a proof-of-stake protocol's rules.
- Slashing: Slashing is a protocol penalty that can reduce a validator's stake when it violates specified network rules.
Monetary Policy Basics
Monetary policy uses interest rates and other tools to pursue goals such as price stability and sustainable economic activity.
InflationConsumer Price IndexCentral BankReal Interest Rate
- Inflation: Inflation is a sustained increase in the general price level, which reduces the purchasing power of a unit of currency over time.
- Consumer Price Index: A consumer price index measures how the prices paid by consumers for a selected basket of goods and services change over time.
- Central Bank: A central bank is a public institution that manages monetary policy and often supports payment systems and financial stability.
- Real Interest Rate: A real interest rate is an interest rate adjusted to account for the effect of inflation on purchasing power.
Transformer Architecture
Transformer models turn input into tokens and use attention-based layers to represent relationships among pieces of information.
TokenizerTransformerAttention MechanismFine-Tuning
- Tokenizer: A tokenizer converts text into smaller units called tokens that a language model can process.
- Transformer: A transformer is a neural-network architecture that uses attention mechanisms to model relationships within sequences such as text.
- Attention Mechanism: An attention mechanism lets a model assign different importance to parts of its input when producing a representation or output.
- Fine-Tuning: Fine-tuning continues training a pretrained model on a narrower dataset or task to adapt its behavior.
Verifiable AI Infrastructure
Verifiable AI infrastructure combines secure hardware, cryptographic proofs, dependable data feeds, and provenance records to support auditable systems.
- Trusted Execution Environment: A trusted execution environment is a protected hardware-backed area designed to run code and handle data with stronger isolation from the rest of a system.
- Zero-Knowledge Proof: A zero-knowledge proof is a cryptographic method for demonstrating that a statement is true without revealing all of the underlying information.
- Oracle: An oracle is a service that provides blockchain applications with information from outside the blockchain, subject to its stated data and security design.
- Data Provenance: Data provenance records where data came from and how it was collected, transformed, or used.
Educational vocabulary only. This site does not provide investment, tax, or trading advice.
How the answer key is structured
Each group is based on function. A stablecoin group might connect reserve, redemption, attestation, and depeg because they all describe how a token tries to keep a reference value. An AI group might connect prompt, context window, inference, and evaluation because they describe model workflow.
What to review after solving
Pick one missed group and read the definitions before moving on. The goal is not to memorize all 16 cards at once, but to notice the concept that made four terms belong together.