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Architect
Architect
Jul 13, 2024 · Artificial Intelligence

Practical Guide to Building LLM Products: Prompt Engineering, RAG, Evaluation, and Operations

This article provides a comprehensive, step‑by‑step guide for developing large‑language‑model (LLM) applications, covering prompt design techniques, n‑shot and chain‑of‑thought strategies, retrieval‑augmented generation, structured I/O, workflow optimization, evaluation pipelines, operational best practices, and team organization to create reliable, scalable AI products.

AI operationsLLMProduct Development
0 likes · 54 min read
Practical Guide to Building LLM Products: Prompt Engineering, RAG, Evaluation, and Operations
DataFunSummit
DataFunSummit
May 10, 2024 · Artificial Intelligence

LLMOps: Definition, Fine‑tuning Techniques, Application Architecture, Challenges and Solutions

This article introduces LLMOps by defining large language model operations, explains the three stages of LLM development, details modern fine‑tuning methods such as PEFT, Adapter, Prefix, Prompt and LoRA, outlines the architecture for building LLM applications, discusses the main difficulties of agent‑based deployments, and presents practical solutions including Prompt IDE, low‑code deployment, monitoring and cost control.

AI operationsFine-tuningLLMOps
0 likes · 14 min read
LLMOps: Definition, Fine‑tuning Techniques, Application Architecture, Challenges and Solutions
Efficient Ops
Efficient Ops
Nov 7, 2022 · Artificial Intelligence

Unlocking AI Project Success with the New MLOps Maturity Assessment

This article outlines the background, standards, evaluation items, process, and registration details of a newly launched MLOps development management maturity assessment designed to accelerate AI model delivery and improve operational efficiency across teams.

AI EngineeringAI operationsMaturity Assessment
0 likes · 6 min read
Unlocking AI Project Success with the New MLOps Maturity Assessment
Didi Tech
Didi Tech
Apr 26, 2021 · Artificial Intelligence

Model Quality Assurance Practices at DiDi: Challenges, Solutions, and Evaluation

DiDi’s shift to machine‑learning‑driven ride‑hailing services revealed major QA challenges—data and feature quality, model verification, and API stability—prompting a four‑pillar framework and a unified “Strategy‑Center 1.0” platform to systematically monitor, evaluate, and improve model effectiveness, bias paths, and feature discovery.

AI operationsFeature EvaluationModel Quality Assurance
0 likes · 8 min read
Model Quality Assurance Practices at DiDi: Challenges, Solutions, and Evaluation
Efficient Ops
Efficient Ops
Nov 22, 2018 · Artificial Intelligence

How AI Transforms Log Management: Building an Intelligent Log Center for AIOps

This article explores how AI-driven AIOps can turn massive operational log data into actionable insights, detailing the five‑level AI capability model, real‑world implementation scenarios, and industry case studies that demonstrate the value of an intelligent log center.

AI operationsAIOpsIT Operations
0 likes · 10 min read
How AI Transforms Log Management: Building an Intelligent Log Center for AIOps