Untitled Flashcards Set

Chatbot latency

The time delay between when a user submits a query to a chatbot and when the chatbot returns a response.

Linguistic nuance

Subtle variations in language that affect meaning, including tone, idioms, slang, and cultural references.

Lexical analysis

The initial NLP step that segments raw text into tokens for downstream processing.

Syntactic analysis

Examining token sequences against grammatical rules to build a parse tree and reveal sentence structure.

Semantic analysis

The process of interpreting the meaning of tokens and their relationships to capture intent.

Pragmatic analysis

Understanding language in context to resolve ambiguity based on user intent and conversational history.

Model training

Iteratively adjusting an AI model’s parameters on a labeled dataset to learn mappings of inputs to outputs.

Backpropagation

A learning algorithm for neural networks that propagates the error gradient to update weights and minimize loss.

Static dataset

A fixed collection of training data that does not change once the model is deployed.

Dynamic dataset

A continuously updated dataset that incorporates new examples, allowing the chatbot to evolve.

Parallel processing

Executing multiple computations simultaneously to reduce response time under heavy load.

Knowledge distillation

Training a smaller model to mimic a larger model’s behavior, creating a lightweight chatbot.

Embedding layer

A neural network layer that maps discrete tokens to continuous vectors, capturing semantic relationships.

Explainability

The degree to which a model’s internal reasoning can be understood by humans.

Transfer learning

Applying knowledge learned in one domain to a related task, reducing required training data and time.

Intent recognition

The NLP task of classifying a user’s overall goal from their input text.

Entity recognition

Identifying and classifying key information units within text.

Reinforcement learning

A learning paradigm where the chatbot improves by receiving rewards or penalties based on response quality.

Knowledge graph

A structured database of entities and their relationships for accurate fact retrieval.

Speech-to-text processing

Converting spoken language into written text via models, extending chatbots to voice interfaces.

GPU (Graphics Processing Unit)

A specialized processor optimized for parallel numeric computations, accelerating neural network inference.

TPU (Tensor Processing Unit)

A custom Google-designed ASIC for tensor operations in machine learning workloads.

CPU (Central Processing Unit)

The general-purpose processor that executes program instructions sequentially.

Tokenization

Breaking text into smaller units serving as the first step in NLP.

Word-based tokenization

Splitting text on whitespace/punctuation into whole words.

Character-based tokenization

Splitting text into individual characters; handles any input but results in long sequences.

Subword-based tokenization

Splitting text into frequently occurring character n-grams for vocabulary size balance.

Named Entity Recognition (NER)

Extracting and classifying real-world entities from text.

Sentiment Analysis

Automatically detecting the emotional tone of user input.

Deterministic rule-based chatbot

A chatbot that follows predefined rules and decision trees.

Probabilistic machine learning chatbot

A chatbot that uses statistical or neural models to generate responses.

Edge computing

Performing data processing on devices at the network edge instead of centralized servers.

Cloud-based infrastructure

Hosting chatbot services on remote data centers accessed via the Internet.

On-premises computing

Running chatbot services on local servers owned by the organization.

Class

A blueprint that defines data and behaviors for objects in OOP.

Object

An instance of a class containing concrete values for its attributes.

Encapsulation

Restricting direct access to an object’s internal state by using private variables.

Instance variable

A variable defined in a class, with each object getting its own copy.

Getter method

A public method that returns the value of a private instance variable.

Setter method

A public method that sets or updates the value of a private instance variable.

Inheritance

The mechanism by which one class acquires attributes and methods from another class.

Polymorphism

The ability of different classes to be treated through the same interface.

Abstract method

A method declared without implementation in a base class.

Refactoring

Restructuring existing code without changing external behavior.

Composition

Building complex types by including instances of other classes.

Modular programming

Designing software as a collection of loosely coupled, self-contained components.

Monolithic design

A non-modular approach where all functionality resides in a single codebase.

Static method

A method associated with the class rather than any instance.

Instance method

A method that operates on a specific object’s instance variables.

Interface

An abstract type that declares method signatures without implementations.

Method overriding

A subclass providing a specific implementation for a method in its superclass.

Method overloading

Defining multiple methods with the same name but different parameter lists within the same class.

Design pattern

A general, reusable solution template for common software design problems.

Singleton pattern

Ensures a class has only one instance and provides a global access point to it.

Factory pattern

Encapsulates object creation logic in a separate factory class or method.

Observer pattern

Defines a one-to-many dependency for object state changes.

Data hiding

Preventing external code from directly accessing an object’s internal data.

Procedural programming

A programming paradigm based on procedures or routines rather than objects.