Tokenization
Tokenization splits text or other input into units that an AI model converts into identifiers and processes.
#NaturalLanguageProcessing
Explore AIstify's latest reporting, research, and expert analysis tagged with "natural language processing", collected in one continuously updated archive.
Related Posts
Transformer
A transformer is a neural network architecture built on attention and used in modern language, vision, audio, video, and multimodal AI models.
Attention Mechanism
An attention mechanism helps an AI model focus on the most relevant parts of its input when interpreting information or generating an output.
Semantic Search
By
Daniel Mercer
• 1 min read
Semantic search uses embeddings to retrieve information by meaning and context, finding relevant results even when documents use different words.
Perplexity
By
Ethan Caldwell
• 1 min read
Perplexity measures how uncertain a language model is when predicting a sequence, with lower values indicating better prediction.
Recurrent Neural Network (RNN)
By
Daniel Mercer
• 1 min read
A recurrent neural network (RNN) is a deep learning model that carries information across sequential inputs such as text, speech, and time-series data.
Natural Language Understanding (NLU)
By
Ethan Caldwell
• 1 min read
NLU enables computer systems to identify meaning, intent, entities, and relationships in human language.
Natural Language Generation (NLG)
By
Ethan Caldwell
• 1 min read
NLG is the branch of AI that produces human-readable language from data, prompts, representations, or structured plans.
Prompt Engineering
By
Daniel Mercer
• 1 min read
Prompt engineering is the practice of designing instructions, context, examples, and output rules that help generative AI perform tasks reliably.
Masked Language Modeling (MLM)
By
Ethan Caldwell
• 1 min read
Masked language modeling trains a model to reconstruct hidden tokens using the surrounding context on both sides.
XLM-R
By
Marcus Lee
• 1 min read
XLM-R is a multilingual transformer encoder that supports cross-lingual classification, entity recognition, and language understanding tasks.
Named Entity Recognition (NER)
By
Daniel Mercer
• 1 min read
Named entity recognition (NER) is an NLP task that finds and classifies people, places, organizations, dates, products, and other entities in text.
Embedding
By
Daniel Mercer
• 1 min read
An embedding is a numerical representation that places related words, images, documents, or other items close together in a mathematical space.
Multimodal AI
By
Daniel Mercer
• 1 min read
Multimodal AI is artificial intelligence that understands or generates multiple data types, including text, images, audio, video, and sensor input.
Word Error Rate (WER)
By
Marcus Lee
• 1 min read
Word error rate (WER) measures speech-recognition accuracy from word substitutions, deletions, and insertions compared with a reference transcript.