An educational crypto, finance, and AI vocabulary puzzle about payment rails, trade execution, model serving, and blockchain risk signals.
Stablecoin Settlement
These terms cover issuance, redemption, reserve backing, and peg behavior.
- Mint: Minting creates new stablecoins or tokens according to the protocol's rules.
- Redeem: Redeeming swaps a token back for its backing asset or settlement value.
- Reserve: Reserves are assets held to support redemptions or maintain a stablecoin's target value.
- Depeg: A depeg happens when a stablecoin trades meaningfully away from its intended reference price.
Order Book Basics
These terms explain quoted prices, available size, and execution quality.
- Spread: Spread is the difference between the best buy price and the best sell price in a market.
- Market Depth: Market depth shows how much buying or selling interest exists at different price levels.
- Slippage: Slippage is the difference between the expected trade price and the price actually filled.
- Limit Order: A limit order executes only at the price you specify or a better one.
Model Serving Basics
These terms cover request speed, work batching, output size, and text processing.
- Batching: Batching groups multiple AI requests so a system can process them more efficiently.
- Latency: Latency is the delay between sending a request and receiving a model's response.
- Throughput: Throughput measures how many requests or tokens a system can process in a given time.
- Tokenizer: A tokenizer splits text into the tokens that an AI model can read and generate.
Chain Risk Signals
These terms help describe wallet concentration, bridge flow, and suspicious patterns.
- Mempool: The mempool is a waiting area for transactions that have been broadcast but not yet confirmed.
- Whale Wallet: A whale wallet is an address believed to hold a very large amount of a crypto asset.
- Bridge Inflow: Bridge inflow measures assets moving into a chain or protocol through a cross-chain bridge.
- Anomaly Detection: Anomaly detection looks for patterns in data that differ from the expected baseline.