From RNNs to Multimodal Agents: A Decade of Transformer Evolution

This article traces the evolution of sequence models from early RNN/LSTM designs through the breakthrough Transformer, its major branches, dense scaling, efficiency‑focused variants, next‑generation linear‑complexity SSMs, and finally multimodal agent architectures, highlighting each stage's strengths, weaknesses, and typical use cases.

AI ArchitectureLLMMultimodal

0 likes · 12 min read

From RNNs to Multimodal Agents: A Decade of Transformer Evolution

ShiZhen AI

Mar 2, 2026 · Artificial Intelligence

What We Learned After a Year of Building Claude Code: Thinking Like an Agent

The article shares Claude Code core developer Thariq's design philosophy for AI agent tools, explaining how tool selection must match model capabilities, the iterative failures that shaped the AskUserQuestion tool, and why progressive disclosure and continual tool evolution are essential as models improve.

AI agentsAskUserQuestionClaude Code

0 likes · 10 min read

What We Learned After a Year of Building Claude Code: Thinking Like an Agent

DataFunSummit

Aug 28, 2021 · Artificial Intelligence

Evolution of Alibaba’s Advertising Prediction Models: From Linear Regression to Deep Interest Evolution Networks

This article reviews the characteristics of e‑commerce personalized prediction, traces Alibaba’s advertising CTR model evolution from large‑scale logistic regression through deep learning architectures such as DIN and CrossMedia, and discusses future research directions like representation learning and white‑box modeling.

CTR predictionDeep LearningE‑commerce

0 likes · 13 min read

Evolution of Alibaba’s Advertising Prediction Models: From Linear Regression to Deep Interest Evolution Networks

DataFunTalk

Oct 30, 2020 · Artificial Intelligence

Evolution of Display Advertising Effect Optimization at 360: System Architecture, Smart Bidding, and Model Advances

This article details the end‑to‑end evolution of 360's display advertising optimization, covering business flow, common ad formats, system architecture, CPC settings, traffic layering, smart bidding, creative combination, model progression from simple to deep learning, multi‑task learning, and latency reduction techniques.

Ad TechOCPCdisplay advertising

0 likes · 13 min read

Evolution of Display Advertising Effect Optimization at 360: System Architecture, Smart Bidding, and Model Advances

DataFunTalk

Jun 21, 2019 · Artificial Intelligence

Applying Deep Learning to Airbnb Search: Model Evolution, Feature Engineering, and System Insights

This article reviews the Airbnb search ranking paper, detailing offline and online performance gains, the progression from SimpleNN to LambdaRankNN, GBDT/FM NN, and Deep NN models, failed embedding attempts, extensive feature engineering practices, and the production system architecture that enabled large‑scale deep learning deployment.

AirbnbNDCGmodel evolution

0 likes · 10 min read

Applying Deep Learning to Airbnb Search: Model Evolution, Feature Engineering, and System Insights

DataFunTalk

May 20, 2019 · Artificial Intelligence

Evolution of Alibaba's Advertising CTR Prediction Models: From Linear Methods to Deep Interest Evolution Networks

The article reviews the characteristics of e‑commerce personalized prediction, outlines Alibaba's model iteration from large‑scale linear regression to deep learning architectures such as DIN, CrossMedia, and Deep Interest Evolution, and discusses future directions like disentangled representation and white‑box modeling.

Attention MechanismCTR predictionRecommendation Systems

0 likes · 11 min read

Evolution of Alibaba's Advertising CTR Prediction Models: From Linear Methods to Deep Interest Evolution Networks