Essential terms for developers new to building AI applications.LLM (Large Language Model) The AI model that generates text responses,
like GPT-4, Claude, or Llama. Think of it as the “brain” that powers your
chatbot or AI assistant.Prompt The text you send to an AI model to get a response. This includes
user messages, system instructions, and any context you provide.Token How AI models count and limit text. Roughly 1 token = 0.75 words.
Models have token limits (like 4,000 or 128,000 tokens) that determine how much
text they can process at once.Context Window The maximum amount of text an AI model can “remember” in
one conversation. Once you exceed this limit, the model starts “forgetting”
earlier parts of the conversation.Embedding Converting text into numerical vectors that computers can
understand and compare. Enables “smart search” that finds similar content based
on meaning, not just keywords.Semantic Search Search based on meaning rather than exact keyword
matching, often using embeddings.Agent An AI system that can take actions and make decisions, not just
generate text responses. Agents can use tools, call APIs, and interact with
external systems.
Global Representation Derived context of a specific peer, synthesizing
insights from interactions across all sessions, including arbitrary data
ingested by this specific peer. With arbitrary data, a global representation
can be made independent of sessions.Local Representation One peer’s persistent context of another based on
observed interactions/messages.
Cognitive science terms that are used throughout the inspiration and
implementation of HonchoTheory of Mind The ability of a computer to understand, remember, and
interact with its own mind, enabling it to form representations of the world
and make decisions based on its own knowledge and behavior.Social Cognition The mental processes by which we perceive, interpret, and
respond to information about others and social situations. It includes the
encoding, storage, retrieval, and application of social knowledge.Cognitive Architecture In CogSci, frameworks describing fixed structures & mechanisms underlying
human cognition. Such frameworks aim to explain how various components of the mind—perception, memory,
reasoning, learning, etc—combine to produce intelligent behavior across diverse environments. In
AI, it’s a computational implementation of these theories—a designed framework to replicate human
cognitive functions.Predictive Coding A theory in CogSci proposing the brain is an active prediction machine,
continually generating & updating internal world models to anticipate sensory input, rather than
passively receiving it—closely linked to Bayesian brain hypotheses, which hold that the brain
interprets the world probabilistically, weighing prior knowledge against new evidence to minimize
uncertainty.
