Tagged articles

Algorithm Evolution

4 articles · Page 1 of 1

Jun 15, 2026 · Artificial Intelligence

Evolution of Recommendation System Architecture: From Hand‑Crafted Rules to the Large‑Model Era

This article traces the five‑generation evolution of recommendation algorithms—from manual rules, through LR and GBDT, to deep learning and large models—explaining each stage’s suitable scenarios, engineering upgrades, trade‑offs, and why practical architecture choices should prioritize business needs over chasing the newest technology.

Algorithm EvolutionGBDTdeep learning

0 likes · 32 min read

Evolution of Recommendation System Architecture: From Hand‑Crafted Rules to the Large‑Model Era

Model Perspective

Dec 20, 2024 · Artificial Intelligence

From Monte Carlo to Deep Learning: How Algorithms Evolved to Power AI

This article traces the evolution of algorithms—from the random‑sampling Monte Carlo method through classic machine‑learning models to modern deep‑learning architectures—highlighting how data, computing power, and scientific demand have driven each breakthrough and hinting at future trends like interpretability, AGI, and quantum algorithms.

Algorithm EvolutionArtificial IntelligenceMonte Carlo

0 likes · 8 min read

From Monte Carlo to Deep Learning: How Algorithms Evolved to Power AI

Baobao Algorithm Notes

Jul 8, 2024 · Industry Insights

Why Large‑Model Deployment Stalls: Robots, Scaling Laws, and Multimodal Frontiers

The article analyzes current challenges in deploying large AI models, covering robot automation, scaling‑law limits, vertical‑domain use cases, multimodal breakthroughs, algorithmic evolution, and the hardware‑software trade‑offs of training and inference infrastructures, while questioning ROI and practical feasibility.

Algorithm EvolutionMultimodalTraining Infrastructure

0 likes · 21 min read

Why Large‑Model Deployment Stalls: Robots, Scaling Laws, and Multimodal Frontiers

Meitu Technology

Mar 11, 2016 · Artificial Intelligence

Meipai Personalized Recommendation Technology Journey

As Meipai’s user base exploded, the platform shifted from manual curation to sophisticated personalized recommendation algorithms—leveraging machine‑learning and data‑mining techniques, iterating through multiple generations, overcoming scalability and relevance challenges, and delivering rapid solutions that inspire future recommendation system designs.

Algorithm EvolutionMeipaiPersonalized Recommendation

0 likes · 1 min read

Meipai Personalized Recommendation Technology Journey