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Embeddings

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Full-Stack Internet Architecture
Full-Stack Internet Architecture
Jun 4, 2025 · Artificial Intelligence

Key AI Concepts for Spring AI: Models, Prompts, Embeddings, Tokens, Structured Output, and RAG

This article introduces essential AI concepts—including models, prompts and prompt templates, embeddings, tokens, structured output, and Retrieval‑Augmented Generation—explaining their meanings and relevance for effectively using Spring AI in real‑world applications.

AIEmbeddingsRAG
0 likes · 7 min read
Key AI Concepts for Spring AI: Models, Prompts, Embeddings, Tokens, Structured Output, and RAG
Bitu Technology
Bitu Technology
Jan 17, 2024 · Artificial Intelligence

Rosetta Stone: Scalable ID Mapping System for Tubi's Content Library Using LLMs and Embeddings

This article describes how Tubi built the Rosetta Stone system—a flexible ID mapping workflow that leverages large language models, embedding similarity ranking, and K‑nearest‑neighbors to unify and enrich metadata across a 200,000‑title library, improve content recommendation, and streamline operations.

Big DataEmbeddingsLLM
0 likes · 10 min read
Rosetta Stone: Scalable ID Mapping System for Tubi's Content Library Using LLMs and Embeddings
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jan 12, 2024 · Artificial Intelligence

Understanding Vector Databases, ANN Algorithms, and Their Integration with Large Language Models

This article explains the fundamentals of vector databases, how high‑dimensional vector data is generated and stored, reviews common ANN search algorithms such as Flat, k‑means and LSH, discusses benchmarking and product selection, and demonstrates practical integration of vector stores with LLMs using LangChain and Python code.

ANNEmbeddingsLLM integration
0 likes · 17 min read
Understanding Vector Databases, ANN Algorithms, and Their Integration with Large Language Models
Architect
Architect
May 29, 2023 · Artificial Intelligence

Understanding Embeddings and Vector Databases for LLM Applications

This article explains what embeddings and vector databases are, how they are generated with models like OpenAI's Ada, why they enable semantic search and help overcome large language model token limits, and demonstrates a practical workflow for retrieving relevant document chunks using cosine similarity.

EmbeddingsLLMSemantic Search
0 likes · 7 min read
Understanding Embeddings and Vector Databases for LLM Applications
Top Architect
Top Architect
Mar 1, 2023 · Artificial Intelligence

Understanding the Internals of ChatGPT: Neural Networks, Embeddings, and Training Techniques

This article provides a comprehensive overview of how ChatGPT works, covering its probabilistic text generation, transformer architecture, embedding representations, neural network training processes, and the underlying principles that enable large language models to produce coherent and meaningful human-like language.

AIChatGPTEmbeddings
0 likes · 80 min read
Understanding the Internals of ChatGPT: Neural Networks, Embeddings, and Training Techniques
Bitu Technology
Bitu Technology
Jul 8, 2022 · Artificial Intelligence

Applying NLP and Machine Learning to Classify Tubi User Feedback

This article explains how Tubi leverages natural‑language processing, sentence embeddings (USE and BERT), and LightGBM models to automatically categorize large volumes of Net Promoter Score comments and customer‑support tickets, enabling data‑driven product decisions and workflow automation.

EmbeddingsLightGBMNLP
0 likes · 11 min read
Applying NLP and Machine Learning to Classify Tubi User Feedback