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Model Perspective
Model Perspective
Jan 14, 2025 · Artificial Intelligence

Quantifying AI Effectiveness: A Formulaic Model for Skills, Prompts, and Platforms

This article proposes a quantitative model that breaks AI usage effectiveness into three multiplicative factors—professional ability, prompt engineering skills, and AI platform capabilities—detailing each component, offering a prompt framework (BROKE), and providing tailored recommendations for beginners, competitors, and applied learners.

AI effectivenessAI platformsPrompt Engineering
0 likes · 7 min read
Quantifying AI Effectiveness: A Formulaic Model for Skills, Prompts, and Platforms
JD Retail Technology
JD Retail Technology
Apr 19, 2024 · Product Management

My Journey as an AI Product Manager at JD.com: Career Decisions, Project Experiences, and Growth Framework

This article chronicles the author's three‑year journey as an AI product manager at JD.com, detailing the decision to enter the AI field, key project experiences such as platform integration and edge‑intelligence, a three‑stage growth roadmap, essential capabilities across four quadrants, and a forward‑looking view of AI's industry impact.

AI platformsAI product managementJD.com
0 likes · 12 min read
My Journey as an AI Product Manager at JD.com: Career Decisions, Project Experiences, and Growth Framework
DataFunSummit
DataFunSummit
Nov 20, 2021 · Artificial Intelligence

Design Dimensions of Next‑Generation AI Platforms: Programming Languages, Runtime Environments, and Model Deployment

The article examines three key design dimensions of modern AI platforms—choice of programming language, runtime environment isolation, and model deployment—highlighting how Python’s dominance, container‑based resource management, and efficient data sharing shape platform architecture and performance.

AI platformsApache ArrowModel Deployment
0 likes · 13 min read
Design Dimensions of Next‑Generation AI Platforms: Programming Languages, Runtime Environments, and Model Deployment
High Availability Architecture
High Availability Architecture
May 28, 2018 · Artificial Intelligence

Interview with GIAC AI Forum Lecturer Long Mingkang on Building AI Platforms, Speech Recognition Challenges, and Future AI Trends

In this interview, Long Mingkang, Vice President of iFlytek's Cloud Computing Institute, shares his experience building large‑scale speech cloud services, discusses the technical hurdles of speech recognition and AI platform development, compares TensorFlow and MXNet, and offers insights on AutoML, industry trends, and how engineers can master AI.

AI platformsAutoMLCloud AI
0 likes · 13 min read
Interview with GIAC AI Forum Lecturer Long Mingkang on Building AI Platforms, Speech Recognition Challenges, and Future AI Trends