AI glossary for content assistants
Plain-English definitions of 13,917 AI terms for branded assistant teams.
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13,917 terms. Open one for definitions and related concepts.
Test-Time Compute
Test-time compute refers to using additional computational resources at inference time to improve AI model output quality, rather than relying solely on larger training runs.
Inference Scaling
Inference scaling describes the phenomenon where AI model quality improves predictably as more computation is allocated during inference rather than training.
Process Reward Models
Process reward models score each step in a reasoning chain rather than just the final answer, enabling more precise supervision for complex multi-step AI tasks.
Superalignment
Superalignment is the research challenge of aligning AI systems that may become smarter than humans, using techniques that do not require superhuman oversight.
Sparse Autoencoders
Sparse autoencoders are interpretability tools that decompose neural network activations into human-interpretable features by enforcing sparsity constraints.
Activation Patching
Activation patching is an interpretability technique that replaces neural network activations from one run with those from another to identify which components causally influence specific model behaviors.
Circuit Discovery
Circuit discovery is a mechanistic interpretability technique that identifies the specific components (attention heads, MLPs, residual stream) responsible for a particular model behavior.
Grokking
Grokking is the phenomenon where neural networks suddenly generalize after a long period of apparent memorization, discovered through studying algorithmic tasks.
Double Descent
Double descent describes the phenomenon where model test performance initially worsens then improves again as model complexity increases beyond interpolation threshold.
Compute-Optimal Training
Compute-optimal training maximizes AI model performance for a given compute budget by optimally balancing model size and training data quantity.
Synthetic Data for Training
Synthetic data for AI training uses model-generated or procedurally created data to augment or replace human-curated training datasets.
Multi-Task Learning
Multi-task learning trains a single AI model to perform multiple different tasks simultaneously, often improving performance on each task compared to single-task training.
Scaling Laws
Scaling laws are mathematical relationships describing how AI model performance predictably improves with increases in model size, training data, and compute.
Direct Preference Optimization
DPO is an alignment technique that directly fine-tunes language models on human preference data without requiring a separate reward model or reinforcement learning.
Mechanistic Interpretability
Mechanistic interpretability aims to reverse-engineer the exact computations neural networks perform, discovering the algorithms and circuits implementing specific behaviors.
Process Supervision
Process supervision trains AI models by providing feedback on each reasoning step rather than only on final outcomes, enabling more accurate learning for complex tasks.
Alignment Tax
The alignment tax is the performance cost incurred when making an AI model safer or more aligned with human values, reducing some capabilities in exchange for better behavior.
Feature Steering
Feature steering controls AI model behavior by directly activating or suppressing interpretable features in the model's residual stream, enabling fine-grained behavioral control.
Test-Time Training
Test-time training updates model parameters on test examples at inference time, adapting the model to the specific distribution of each query.
API
An API (Application Programming Interface) is a set of rules and protocols that allows different software applications to communicate with each other.
REST API
A REST API uses HTTP methods and resource-based URLs to create a standardized interface for web services communication.
GraphQL
GraphQL is a query language for APIs that allows clients to request exactly the data they need in a single request.
gRPC
gRPC is a high-performance remote procedure call framework that uses Protocol Buffers for efficient binary serialization.
WebSocket
WebSocket is a communication protocol that provides full-duplex, bidirectional communication between a client and server over a single persistent connection.
Server-Sent Events
Server-Sent Events (SSE) is a standard for pushing real-time updates from server to client over a single HTTP connection.
SSE
SSE (Server-Sent Events) is a lightweight HTTP-based protocol for streaming real-time updates from server to client.
Webhook
A webhook is an HTTP callback that automatically sends data to a specified URL when a specific event occurs in a system.
Endpoint
An endpoint is a specific URL in an API that represents a resource or action, serving as the point of interaction between systems.
HTTP
HTTP (HyperText Transfer Protocol) is the foundation protocol of the web, defining how messages are formatted and transmitted between clients and servers.
HTTPS
HTTPS is the secure version of HTTP that encrypts all communication between client and server using TLS/SSL encryption.
GET
GET is an HTTP method used to request and retrieve data from a server without modifying any resources.
POST
POST is an HTTP method used to submit data to a server, typically to create new resources or trigger actions.
PUT
PUT is an HTTP method used to update or replace a resource at a specific URL with the provided data.
DELETE
DELETE is an HTTP method used to remove a specified resource from the server.
Status Code
HTTP status codes are three-digit numbers returned by servers to indicate the result of a client request.
Pagination
Pagination is the practice of dividing large datasets into smaller pages, allowing APIs to return results in manageable chunks.
API Key
An API key is a unique identifier used to authenticate and authorize requests to an API, controlling access to its resources.
Bearer Token
A bearer token is an authentication credential sent in HTTP headers that grants access to whoever possesses it.
OAuth
OAuth is an authorization framework that allows applications to access user resources from other services without exposing user credentials.
JWT
JWT (JSON Web Token) is a compact, URL-safe token format for securely transmitting claims between parties as a signed JSON object.
API Versioning
API versioning is the practice of managing changes to an API while maintaining backward compatibility for existing consumers.
OpenAPI
OpenAPI is a specification standard for describing REST APIs in a machine-readable format, enabling documentation and code generation.
Swagger
Swagger is a suite of API development tools that generates interactive documentation, client SDKs, and server stubs from OpenAPI specifications.
Token Streaming
Token streaming is the technique of delivering AI-generated text token by token as the model produces them, creating a real-time typing effect.
Real-Time
Real-time refers to systems that process and deliver data with minimal latency, providing immediate feedback to users.
Push Notification
A push notification is a message sent from a server to a user device proactively, without the user having to request or check for updates.
Pub/Sub
Pub/Sub (Publish/Subscribe) is a messaging pattern where senders publish messages to topics and receivers subscribe to receive them.
Event-Driven Architecture
Event-driven architecture is a software design pattern where system components communicate by producing and consuming events asynchronously.
Turn owned content into answers
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Product FAQ
What is InsertChat?
InsertChat is a white-label AI assistant for your website. Train it, brand it, publish it, and learn from visitor questions.
How does InsertChat use my website content?
Connect approved pages, docs, videos, FAQs, policies, and other sources. InsertChat turns them into source-backed answers and next steps.
Can I control the assistant's tone and sources?
Yes. Choose its sources, tone, welcome message, and prompts so it stays on brand.
How does InsertChat stay accurate?
Answers use approved content and source links. Analytics show unclear or missing answers so you can improve coverage.
Can it collect leads or route support questions?
Yes. InsertChat can collect details, qualify intent, add context, and send chats to the right inbox, CRM, workflow, or person.
Can I control how the assistant behaves?
Yes. Control prompts, model choice, tool access, and the branded assistant experience so behavior stays consistent.
Which AI models can I use?
InsertChat supports multiple model providers. Choose each assistant's model for quality, speed, and cost, or use BYOK.
Can I pick different models for different workflows?
Yes. Use a faster model for common questions and a stronger model for complex reasoning. InsertChat supports that balance per conversation.
Where can I deploy an assistant?
Use a widget, embed, full-page assistant, custom domain, in-app embed, or API. Reuse one setup across surfaces.
Do I need coding skills?
No. Build and deploy AI assistants using our visual builder. The embed code is one line of JavaScript.
Can I customize the branding and UI?
Yes. Customize the assistant name, logo, colors, welcome message, suggested prompts, tone, domain, and white-label presentation.
Can I use my own domain?
Yes. Custom domains are supported, typically via enterprise options.
Does InsertChat support voice?
Yes. Voice dictation and text-to-speech let users speak instead of type.
Does InsertChat support vision?
Yes. Enable vision for assistants when images help clarify a request or context.
What tools and integrations are supported?
Zendesk, HubSpot, Shopify, WooCommerce, calendar booking, web search, Perplexity, and webhooks for your own systems.
Can I control which tools the assistant is allowed to use?
Yes. Tool access is controlled per assistant so you enable only what you need.
Can the agent hand off to a human?
Yes. Configure human handoff so the agent escalates when needed. Full conversation history is passed along.
Do you provide analytics?
Yes. Track chats, leads, feedback, top questions, unanswered questions, most-used sources, and content gaps.
Is it mobile friendly?
Yes. The widget and embeds work well on desktop and mobile with no separate experience needed.
What's the fastest path to a successful deployment?
Start with one assistant and a small set of high-value sources. Iterate using real questions from analytics.
What is the fastest way to get started?
Create an account. Connect one key source. Ask a test question, brand the assistant, then publish it on one page.