Term tag: NLP

Attention Mechanism

Each token emits a query, key and value; dot-product scores scaled by √d become softmax weights over every other token. The cost grows as n².

Conversational AI

Conversational AI holds a multi-turn dialogue in natural language. Unlike an intent-based chatbot, it generates each reply rather than picking one.

Embedding

What an embedding vector actually is, why cosine similarity beats Euclidean distance, what dimensions buy you, and where the geometry misleads you.

Large Language Model (LLM)

A large language model predicts the next token of text. How that produces answers, where its knowledge is stored, and why an LLM is not a chatbot.

Natural Language Processing (NLP)

NLP is the field; large language models are now the answer to most of it. What sixty years of work was for, and which parts are still unsolved.

Recurrent Neural Network (RNN)

A recurrent neural network reads a sequence one element at a time, carrying a hidden state that summarizes everything seen so far to model order and context.

Self-Attention

The transformer operation that lets every token in a sequence weigh every other token by relevance, computed as softmax(QKᵀ/√d_k)·V.

Semantic Understanding

Whether an AI grasps meaning well enough to act correctly on novel inputs, or is pattern-matching that breaks on rephrasing — and why that line is contested.

Speech-to-Speech

Speech-to-speech AI takes audio in and returns audio out — conversation or translation — via a cascade (ASR to text to TTS) or one end-to-end model.

Text Analysis

Turning unstructured text into structured data — the concrete NLP task catalog: classification, sentiment analysis, entity extraction and topic modeling.

Text Generation

Text generation is a language model producing text one token at a time: at each step it predicts a distribution over its vocabulary, picks a token, repeats.

Token

The unit an AI model reads, writes and bills by — roughly 1.3 tokens per English word. Input, output and cached tokens are priced up to 10x apart.

Tokenization

How text becomes the integers a language model reads: BPE, WordPiece and Unigram, why " strawberry" is one token, and what that breaks.

Transformer

The 2017 neural-network architecture that processes a whole sequence in parallel using self-attention instead of recurrence — the basis of modern LLMs.

Voice Recognition

How AI turns spoken words into text (speech recognition / ASR) — and how that differs from identifying who is speaking (speaker recognition).