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Airbnb Technology Team
Airbnb Technology Team
Dec 12, 2024 · Artificial Intelligence

Airbnb Automation Platform v2: Enabling LLM‑Driven Conversational AI

Airbnb’s Automation Platform v2 replaces the rigid, workflow‑driven architecture of v1 with an LLM‑centric design that orchestrates context gathering, chain‑of‑thought reasoning, tool execution, and guardrails, enabling more natural, scalable, and safe conversational AI while preserving the reliability of traditional workflows.

AI ArchitectureAirbnbConversational AI
0 likes · 11 min read
Airbnb Automation Platform v2: Enabling LLM‑Driven Conversational AI
DataFunSummit
DataFunSummit
Nov 27, 2024 · Artificial Intelligence

Applying Large Language Models in Data Management and Risk Control at Ping An One Wallet

This presentation details how Ping An One Wallet leverages large language models across five key areas—current application status, data management, risk control, technical architecture, and a Q&A session—highlighting strategies such as vectorized rule storage, prompt engineering, RAG enhancements, and workflow agents to improve efficiency and accuracy in data governance and fraud detection.

AI ArchitectureData GovernanceVector Database
0 likes · 16 min read
Applying Large Language Models in Data Management and Risk Control at Ping An One Wallet
Tencent Docs Tech Team
Tencent Docs Tech Team
Nov 13, 2024 · Artificial Intelligence

Technical Architecture and Practices of the AI Document Assistant

This article explores the challenges large language models bring to efficiency tools, outlines the AI document assistant's technical thinking and architecture, and details both application‑side and model‑side practices such as retrieval‑augmented generation, intent recognition, and code‑driven table handling, concluding with key lessons.

AIAI ArchitectureDocument Automation
0 likes · 16 min read
Technical Architecture and Practices of the AI Document Assistant
phodal
phodal
Oct 20, 2024 · Backend Development

Why Streaming BFF Is the Missing Glue for AI‑Native Apps

The article proposes a Streaming Backend‑for‑Frontend (BFF) layer to unify heterogeneous AI agents, handle Server‑Sent Events streams, and resolve interface inconsistencies, offering a practical architecture for generative‑AI‑native systems across IDEs, DevOps, and team‑AI scenarios.

AI ArchitectureBackend DevelopmentServer-Sent Events
0 likes · 13 min read
Why Streaming BFF Is the Missing Glue for AI‑Native Apps
JavaEdge
JavaEdge
Jun 23, 2024 · Artificial Intelligence

Mapping the Generative AI Landscape: From Infrastructure to Applications

This article provides a comprehensive overview of the generative AI industry, detailing its upstream foundation layer, midstream large‑model and tool layers, downstream application scenarios, and an extensive glossary of models, techniques, platforms, and concepts.

AI ArchitectureIndustry OverviewMachine Learning
0 likes · 12 min read
Mapping the Generative AI Landscape: From Infrastructure to Applications
Baobao Algorithm Notes
Baobao Algorithm Notes
May 9, 2024 · Artificial Intelligence

Inside Deepseek‑V2: How Multi‑Head Latent Attention Cuts KV‑Cache and Boosts Performance

This article provides an in‑depth technical analysis of Deepseek‑V2, covering its 236B parameter size, Multi‑Head Latent Attention optimization that reduces KV‑cache memory, architectural details, training pipelines, infrastructure choices, and performance results on benchmarks such as MMLU and instruction following.

AI ArchitectureDeepSeekLarge Language Model
0 likes · 17 min read
Inside Deepseek‑V2: How Multi‑Head Latent Attention Cuts KV‑Cache and Boosts Performance
Architect
Architect
Apr 16, 2024 · Artificial Intelligence

Unraveling Sora: How OpenAI Might Build a 60‑Second Video Generator

This article dissects the possible architecture of OpenAI's Sora video model, tracing its visual encoder‑decoder, Spacetime Latent Patch, transformer‑based diffusion backbone, long‑time consistency strategies, and training pipeline, while comparing alternatives such as MAGVIT‑v2, TECO, NaViT, and FDM to reveal why each design choice may have been made.

AI ArchitectureLatent DiffusionSora
0 likes · 51 min read
Unraveling Sora: How OpenAI Might Build a 60‑Second Video Generator
DataFunTalk
DataFunTalk
Mar 21, 2024 · Artificial Intelligence

A Detailed Technical Analysis of Sora: Architecture, Key Components, and Potential Implementation

This article provides a comprehensive, easy‑to‑understand breakdown of Sora’s possible architecture—including its visual encoder‑decoder, Spacetime Latent Patch, transformer‑based diffusion model, long‑time consistency strategies, training techniques, and how it supports variable resolution and duration video generation.

AI ArchitectureSoraSpacetime Patch
0 likes · 49 min read
A Detailed Technical Analysis of Sora: Architecture, Key Components, and Potential Implementation
JD Retail Technology
JD Retail Technology
Feb 28, 2024 · Artificial Intelligence

Edge AI at JD Retail: Architecture, Challenges, and Business Practices

This article details JD Retail's edge AI (on‑device intelligence) platform, covering its definition, performance and security challenges, three‑layer cloud‑edge‑device architecture, key components such as high‑performance inference engine, data pipeline, Python VM container, and real‑world applications in traffic distribution and image recognition.

AI ArchitectureEdge AIJD Retail
0 likes · 15 min read
Edge AI at JD Retail: Architecture, Challenges, and Business Practices
HomeTech
HomeTech
Jul 26, 2023 · Artificial Intelligence

Practical Implementation of ChatGPT Technology Products: Architecture, Prompt Engineering, and Future Challenges

This article explores the practical deployment of ChatGPT‑based products, detailing the model fundamentals, technical architecture, engineering‑focused prompt design, real‑world application scenarios, and the challenges of model generalization, resource consumption, data privacy, interpretability, and ethical considerations.

AI ArchitectureChatGPTData Analysis
0 likes · 15 min read
Practical Implementation of ChatGPT Technology Products: Architecture, Prompt Engineering, and Future Challenges
phodal
phodal
Jun 2, 2023 · Artificial Intelligence

Mastering LLMs: A Programmer’s Guide to Prompt Engineering, Architecture, and Contextual AI

This comprehensive guide walks programmers through the fundamentals of large language model capabilities, prompt writing and management, new interaction and workflow designs, advanced scenario‑specific applications, and context engineering, offering practical strategies and architectural insights for AI‑native development.

AI ArchitectureContext EngineeringLLM
0 likes · 14 min read
Mastering LLMs: A Programmer’s Guide to Prompt Engineering, Architecture, and Contextual AI
DataFunSummit
DataFunSummit
Mar 30, 2023 · Artificial Intelligence

An Overview of ChatGPT’s Software Architecture and Technology Stack

The article examines ChatGPT’s underlying software architecture, detailing its cloud deployment on AWS and Azure, database choices like PostgreSQL and Redis, front‑end technologies such as TypeScript and React, core AI frameworks including PyTorch and Triton, as well as its container orchestration, monitoring, and programming language ecosystem.

AI ArchitectureChatGPTFrontend
0 likes · 6 min read
An Overview of ChatGPT’s Software Architecture and Technology Stack
21CTO
21CTO
Feb 8, 2023 · Artificial Intelligence

Understanding ChatGPT: Architecture, Training, Limitations, and Future Directions

This article provides a comprehensive overview of ChatGPT, covering its origin, core GPT‑3.5 architecture, RLHF training pipeline, distinctive features, current limitations, and emerging research directions such as model compression and integration with symbolic engines.

AI ArchitectureArtificial IntelligenceChatGPT
0 likes · 18 min read
Understanding ChatGPT: Architecture, Training, Limitations, and Future Directions
Alibaba Cloud Developer
Alibaba Cloud Developer
Sep 3, 2019 · Artificial Intelligence

Unlocking Scalable Private‑Domain Recommendations with a “4+N” Architecture

This article describes a systematic, standardized, and automated “4+N” recommendation framework that unifies features, samples, models, and pipelines to accelerate private‑domain marketing recommendations across multiple scenarios while improving accuracy, efficiency, and business impact.

AI ArchitectureModel Deploymentdeep learning
0 likes · 12 min read
Unlocking Scalable Private‑Domain Recommendations with a “4+N” Architecture