Обзор
Просматривайте все технологии графа по типу и категории.
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- Алгоритмы 30
- Модели 16
- Модели эмбеддингов 8
- Методы 35
- Промптинг 10
- Фреймворки 12
- Фреймворки LLM 6
- Базы данных 3
- Векторные базы данных 8
- Поисковые движки 4
- Инфраструктура 15
- MLOps 4
- Оценка 6
- Оборудование 11
- Безопасность и выравнивание 6
- Приложения 7
- Мультимодальные 5
- ИИ-агенты 4
- Бенчмарки 11
- Наборы данных 7
10 technologies shown
- Function Calling technique Letting a model request a tool by name with structured arguments.
- In-Context Learning concept A model performing a task from examples in the prompt, with no weight update.
- Zero-Shot concept Performing a task with no examples and no training for it.
- Prompt Engineering technique Shaping a model's instructions and context to get the output you actually want.
- Context Engineering technique Deciding what goes into the context window, not just how it is worded.
- Few-Shot Learning technique Putting examples in the prompt instead of training on them.
- Self-Consistency technique Sampling several reasoning paths and taking the majority answer.
- Structured Output technique Constraining a model to emit valid JSON or a schema-conforming object.
- Chain of Thought technique Prompting a model to reason step by step before answering.
- Tree of Thoughts technique Searching over intermediate reasoning states instead of one linear chain.