I.AI DICTIONARY

Hier finden sich Erklärungen zu den wichtigsten Begriffen

aus der Welt der Künstlichen Intelligenz.

Glossar-Einträge nach Anfangsbuchstaben:

I.AI DICTIONARY

A - B

Accuracy

Adapter

Advanced Query Parsing

Agent

Agentic Behaviour

AGI

AI Engineering

AI Role

Answer Correctness

Answer Relevancy

Assistant Role

Asynchronous Task Handling

Attention

Attention Header

Attention Layer

Attention Mechanisms

Automated Prompt Generation

Basis Model

Benchmark

BERT

Bias

bitsandbytes

C - D

Causal Language Model

Causal Reasoning Models

Chain

Chain-of-Thought Prompting

Chatbots

Chunk

Chunking

Cognitive Architecture

Concept Drift

Conditioning

Context Augmentation

Context Management

Context Precision

Context Recall

Context Window

Contextual Embedding Adaptation

Conversational Memory

Critic Model

Data Agent

Data Annotation

Data Privacy

Data Streaming

databricks-dolly-15k

Decoder

Decoding Strategies

Deployment

Distributed Systems

Dolly

E - F

Efficacy

Embeddings

Embeddings Management

Emergent Abilities

Emergent Properties

Entity Recognition

Evaluation

Evaluation of Long Text

Execution Agent

Explainability

Exploration

External Information Retrieval

Extraction

Fact-checking Models

Factoid

Failure Mode

Few-shot Learning

Fine-tuning

Foundational Model

G - H

GPT (Generative Pretrained Transformer)

GPT-4

Gradient Descent

Gradient-based Optimization

Grounding

Hallucination

Hands-on LLM

Hard Prompt

Hard Selection

Header Attention

Hugging Face

Hyperparameter

Hyperparameter Tuning

I - K

Information Retrieval

Inference

Interpretability

Iterative Prompting

Keyphrase Extraction

Knowledge Augmentation

Knowledge Distillation

Knowledge Graphs

L - M

LaMDA

Language Model Evaluation

Large Language Models (LLMs)

Latent Space

Lexical Semantics

Llama Index

Load Balancing

LoRA (Low-Rank Adaptation)

Loss Function

Machine Learning

Masked Language Model (MLM)

Memory in LLMs

Meta-learning

Meta-prompt

Model Architecture

Model Compression

Model Interpretability

Model Optimization

Model Scalability

Model Training

Model-based Reasoning

Multimodal Models

Multitask Learning

N - O

Named Entity Recognition (NER)

Natural Language Processing (NLP)

Natural Language Understanding (NLU)

Neural Architecture Search

Neural Networks

Next Word Prediction

NLP Pipeline

Noise Contrastive Estimation

Optimization

P - Q

Parameter-efficient Training

Parameterization

Pattern Recognition

Perplexity

Polyglot Models

Post-training Optimization

Predictive Text

Pretrained Language Models

Prompt Chaining

Prompt Engineering

Q-learning

Quantum Machine Learning

Query Optimization

R - S

Reinforcement Learning

Responsible AI

Retrieval-based Models

Reusability

Reward-based Learning

RLHF

Samplers

Scaling

Self-supervised Learning

Semantic Analysis

Semantic Search

Semi-supervised Learning

Sentiment Analysis

Sequence Modeling

Stability

Stable Diffusion

Stochastic Gradient Descent (SGD)

Summarization

Supervised Learning

Synthetic Data Generation

T - U

Targeted Data Augmentation

Task-oriented Models

Temporal Modeling

Text Classification

Text Generation

Text Preprocessing

Text-to-Image Generation

Tokenization

Transfer Learning

Training Data

Transformer Models

Unsupervised Learning

V - Z

Validation

Variational Autoencoders (VAE)

Wasserstein GANs

Weak Supervision

Zero-shot Learning

Zero-shot Transfer

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