Glossary

❜Embed Model (Content personalization, discovery, moderation): Pre-built AI models by ❜Embed designed to offer personalized content, facilitate discovery, and ensure moderation. These models use rich datasets to provide accurate and relevant user experiences.

Content Personalization: Pre-built ❜Embed AI model to predict user interactions and tailor content feeds, such as social media posts, articles, and NFTs, based on individual preferences to increase engagement, retention, and revenue.

Discovery: Pre-built ❜Embed AI model that helps users find desired content through chat-based interfaces and improved search experiences, enhancing user satisfaction.

Moderation: Pre-built ❜Embed AI model that identifies inappropriate, spammy, or engagement-farming content, ensuring a safer online environment.

AI Label: Tags or classifications assigned by AI models to different types of content to facilitate organization, discovery, and moderation.

Dataset: Collections of data used to train AI models. In the context of ❜Embed, these include on-chain and off-chain data, multimedia, and multilingual datasets to improve the accuracy and relevance of AI models.

Endpoint (Content personalization, discovery, moderation): Specific points of interaction with ❜Embed's API that enable functionalities such for content personalization, discovery, and moderation models. Endpoints allow users to sub-categorize their AI models with a specific functionality such as “for you” vs “reranked”.

Handle: A unique identifier for users on social platforms integrated with ❜Embed's AI models, often used in conjunction with user profiles for personalized content delivery.

FID (Farcaster ID): A unique identifier within the Farcaster protocol, used to manage user identities and interactions within decentralized social networks.

Wallet Address: A unique identifier for blockchain-based wallets, used within ❜Embed's ecosystem to link user activities and preferences with their on-chain data.

❜Embed ID: A unique identifier assigned to each user within ❜Embed's ecosystem. This ID is used by ❜Embed's models on social platforms to manage user identities. It serves as the highest hierarchy data mapping tool, superseding other identifiers such as FID (Farcaster ID), wallet addresses, and handles

AI Model Scoring: The process of evaluating AI model performance based on various metrics to determine its accuracy and effectiveness in content personalization, discovery, and moderation models.

Custom Scores: User-defined scoring metrics used to tailor AI model outputs to specific needs or preferences, enhancing the customization of AI-driven content and interactions.

AI Recipe: A predefined configuration or set of instructions for creating specific AI functionalities using ❜Embed models. Recipes streamline the process of implementing AI for tasks like personalization, discovery, and moderation.

Model Training: The process of teaching an AI model to make accurate predictions by feeding it large amounts of data and adjusting its parameters.

Data Preprocessing: The steps taken to clean and prepare data for use in training AI models. This includes tasks like removing duplicates, handling missing values, and normalizing data.

Inference: The stage where the trained AI model makes predictions or decisions based on new, unseen data.

API Key: A unique code provided to developers to access ❜Embed APIs. It is used for authenticating and authorizing API requests, ensuring that only authorized users and applications can interact with ❜Embed's services and endpoints.

API Endpoint: A specific URL where an API can be accessed by developers. Endpoints are used to interact with different functionalities of the ❜Embed platform, such as content personalization, discovery, and moderation.