AIエージェント

An AI system that can autonomously plan, reason, and take actions to accomplish goals, often using tools and making decisions along the way.

AIアライメント

The challenge of ensuring AI systems pursue goals and behaviors that are aligned with human intentions and values.

AI自動化

Using AI to automate repetitive tasks, workflows, and decision-making processes that previously required human effort.

AIチップ

Specialized processors designed specifically for AI workloads, optimized for the matrix math that neural networks require.

AI倫理

The study and practice of ensuring AI systems are developed and used responsibly, fairly, and transparently.

AIガバナンス

The policies, regulations, and organizational structures that guide how AI systems are developed, deployed, and monitored.

AIリテラシー

The ability to understand, use, and critically evaluate AI tools and their outputs, regardless of technical background.

AI投資対効果

The measurable return on investment from implementing AI solutions, comparing costs (development, compute, data) against business value gained.

AI規制

Laws and policies created by governments to control how AI systems are developed, deployed, and used in society.

AI安全性

The research field focused on ensuring AI systems behave as intended and don't cause unintended harm.

AIスタートアップ

A new company that builds its core product or service around artificial intelligence technology.

サービスとしてのAI

Cloud-based platforms that provide ready-to-use AI capabilities via APIs, so businesses don't need to build models from scratch.

アプリケーション・プログラミング・インターフェース

A set of rules and protocols that allow different software applications to communicate with each other.

エージェント型AI

AI systems that can plan, use tools, and take autonomous actions over multiple steps to accomplish complex goals.

アンソロピック

An AI safety company that builds Claude, focusing on creating AI systems that are helpful, harmless, and honest.

汎用人工知能

A hypothetical AI system that can understand, learn, and perform any intellectual task that a human can, across all domains.

人工知能

Computer systems designed to perform tasks that normally require human intelligence, such as understanding language, recognizing images, and making decisions.

アテンション機構

A technique that allows AI models to focus on the most relevant parts of the input when producing output, like how humans focus on key words in a sentence.

自律型システム

Systems that can operate and make decisions independently without human intervention, using AI to perceive and respond to their environment.

自動運転車

A vehicle that can navigate and drive itself using AI, sensors, and cameras without human intervention.

バート

Bidirectional Encoder Representations from Transformers — Google's model that understands context by reading text in both directions simultaneously.

ベンチマーク

A standardized test or dataset used to measure and compare the performance of different AI models on specific tasks.

バイアス

Systematic errors in AI outputs that reflect prejudices in training data or model design, leading to unfair or skewed results.

思考連鎖

A prompting technique where you ask the AI to explain its reasoning step by step, which improves accuracy on complex tasks.

チャットボット

An AI-powered program that can have text or voice conversations with users, answering questions and performing tasks.

クラウドコンピューティング

On-demand access to computing resources (servers, storage, GPUs) over the internet, without owning physical hardware.

コンピュータビジョン

The field of AI that enables computers to interpret and understand visual information from images and videos.

コンテキストウィンドウ

The maximum amount of text (measured in tokens) that an AI model can process in a single conversation or request.

対話型AI

AI technology that enables natural, human-like conversations through chatbots, voice assistants, and messaging interfaces.

畳み込みニューラルネットワーク

A type of neural network designed for processing grid-like data such as images, using filters that detect visual features like edges and shapes.

コパイロット

An AI assistant embedded within a software application that helps users accomplish tasks by suggesting actions, generating content, or answering questions.

データラベリング

The process of tagging or annotating data (images, text, audio) with meaningful labels so AI models can learn from it.

データパイプライン

An automated system that collects, processes, cleans, and delivers data from source to destination for AI training or analysis.

ディープラーニング

A type of machine learning that uses neural networks with many layers to learn complex patterns in large amounts of data.

ディープフェイク

AI-generated synthetic media — usually video or audio — that convincingly replaces one person's likeness with another.

拡散モデル

A generative AI model that creates images by starting with random noise and gradually refining it into a coherent image.

デジタルツイン

A virtual replica of a physical object, system, or process that uses AI and real-time data to simulate and predict behavior.

エッジAI

Running AI models directly on local devices (phones, cameras, IoT sensors) rather than sending data to the cloud.

埋め込み表現

A numerical representation of data (text, images, etc.) as a list of numbers that captures its meaning, enabling AI to compare and search similar items.

連合学習

A technique where AI models are trained across multiple devices or servers without sharing the raw data, preserving privacy.

フューショット学習

Providing an AI model with a few examples of a task in the prompt so it can learn the pattern and apply it to new inputs.

ファインチューニング

The process of taking a pre-trained AI model and further training it on a specific dataset to specialize it for a particular task.

基盤モデル

A large AI model trained on broad data that can be adapted to many different tasks, serving as a base for specialized applications.

ジーピーティー

Generative Pre-trained Transformer — OpenAI's family of large language models that generate text by predicting the next token.

グラフィックス・プロセッシング・ユニット

A specialized processor originally designed for graphics that excels at the parallel computations needed for AI training and inference.

生成AI

AI systems that can create new content — text, images, music, code, or video — rather than just analyzing existing data.

敵対的生成ネットワーク

An AI architecture where two neural networks compete — a generator creates fake data while a discriminator tries to tell real from fake.

ギットハブ・コパイロット

An AI-powered code completion tool that suggests code as you type, trained on public code repositories.

ハルシネーション

When an AI model generates information that sounds plausible but is factually incorrect or entirely made up.

ハギングフェイス

An open-source platform and community for sharing, discovering, and deploying machine learning models and datasets.

推論

The process of using a trained AI model to make predictions or generate outputs on new data.

ナレッジグラフ

A structured network of real-world entities and their relationships, used to organize information so AI can reason about it.

大規模言語モデル

A massive AI model trained on vast amounts of text data that can understand and generate human-like language.

ローラ

Low-Rank Adaptation — an efficient fine-tuning technique that adapts large models by training only a small number of additional parameters.

エムエルオプス

The practice of deploying, monitoring, and maintaining machine learning models in production, combining ML with DevOps principles.

機械学習

A subset of AI where systems learn patterns from data instead of being explicitly programmed with rules.

ミッドジャーニー

A popular AI image generation service known for producing highly artistic and stylized images from text prompts.

混合エキスパート

A model architecture that uses multiple specialized sub-networks (experts), activating only relevant ones for each input to improve efficiency.

モデル崩壊

When an AI model trained on AI-generated data progressively degrades in quality, losing diversity and accuracy over generations.

マルチモーダルAI

AI systems that can understand and generate multiple types of data — text, images, audio, and video — simultaneously.

自然言語生成

The ability of AI to produce human-readable text from structured data or internal representations.

自然言語処理

The branch of AI focused on enabling computers to understand, interpret, and generate human language.

自然言語理解

A subfield of NLP focused on enabling machines to truly comprehend the meaning, intent, and context behind human language.

ニューラルネットワーク

A computing system inspired by the human brain, made up of interconnected nodes (neurons) that process information in layers.

ノーコードAI

AI tools and platforms that let non-programmers build, train, and deploy AI models using visual interfaces instead of writing code.

オープンソースAI

AI models and tools whose code and weights are publicly available, allowing anyone to use, modify, and distribute them.

オープンエーアイ

The AI research company behind ChatGPT, GPT-4, DALL-E, and the most widely used commercial AI models.

過学習

When a model learns the training data too well, including its noise and quirks, and performs poorly on new, unseen data.

パラメータ

The internal variables of a neural network that are adjusted during training. More parameters generally means a more capable model.

予測分析

Using AI and statistical models to analyze historical data and forecast future outcomes or trends.

プロンプト

The text instruction or question you give to an AI model to get a response.

プロンプトチェーニング

Breaking a complex task into a sequence of simpler prompts, where each prompt's output feeds into the next one.

プロンプトエンジニアリング

The practice of designing and refining prompts to get the best possible results from AI models.

プロンプトインジェクション

A security attack where malicious instructions are hidden in input to trick an AI model into ignoring its original instructions.

量子化

A technique that reduces AI model size and speeds up inference by using lower-precision numbers, with minimal quality loss.

人間のフィードバックによる強化学習

Reinforcement Learning from Human Feedback — a training technique where human preferences guide the model to produce better, safer outputs.

レコメンドシステム

An AI system that suggests items, content, or actions to users based on their behavior, preferences, and similarity to other users.

再帰型ニューラルネットワーク

A neural network designed for sequential data that maintains a memory of previous inputs, useful for time series and text.

強化学習

A machine learning approach where an agent learns to make decisions by receiving rewards or penalties for its actions in an environment.

責任あるAI

A framework for developing and deploying AI that is fair, transparent, accountable, and respects privacy and human rights.

検索拡張生成

A technique that enhances AI responses by first retrieving relevant information from external sources, then using that context to generate more accurate answers.

ロボティック・プロセス・オートメーション

Software robots that automate repetitive digital tasks like data entry, form filling, and file transfers by mimicking human actions.

セマンティック検索

Search technology that understands the meaning behind queries rather than just matching keywords.

感情分析

An NLP technique that identifies the emotional tone of text — whether it's positive, negative, or neutral.

音声テキスト変換

AI technology that converts spoken audio into written text, also known as automatic speech recognition.

ステーブル・ディフュージョン

An open-source text-to-image AI model that generates images from text descriptions, runnable on consumer hardware.

教師あり学習

A machine learning approach where the model learns from labeled examples — input-output pairs where the correct answer is provided.

合成データ

Artificially generated data that mimics real-world data, used when real data is scarce, expensive, or privacy-sensitive.

テキストから画像生成

AI models that generate images from text descriptions, translating written prompts into visual content.

テキスト音声合成

AI technology that converts written text into natural-sounding spoken audio.

トークン

A small unit of text (a word, part of a word, or punctuation) that AI models process. Models read and generate text as sequences of tokens.

トークン化

The process of breaking text into smaller units (tokens) that an AI model can process, like splitting words into subwords.

AIのトークノミクス

The pricing and economics of AI API usage, typically based on the number of input and output tokens processed.

学習データ

The dataset used to teach a machine learning model patterns and relationships. The model learns by finding patterns in this data.

転移学習

Reusing a model trained on one task as the starting point for a different but related task, saving time and data.

トランスフォーマー

A neural network architecture that processes all parts of input data simultaneously using attention mechanisms, enabling faster and more effective learning.

教師なし学習

A machine learning approach where the model finds hidden patterns in data without labeled examples or predefined answers.

ベクトルデータベース

A specialized database designed to store and efficiently search through embeddings (vectors), enabling fast similarity searches across millions of items.

説明可能AI

AI systems designed to provide clear, understandable explanations for how they reach their decisions or predictions.

ゼロショット学習

An AI model's ability to perform a task it was never explicitly trained on, using only its general knowledge.