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Alimama Tech

Sep 17, 2025 · Artificial Intelligence

How Federated Learning Balances Privacy and Collaboration in AI

Federated Learning enables multiple parties to collaboratively train a global AI model without sharing raw data, using techniques like local training, encrypted parameter exchange, and secure aggregation, while addressing privacy, communication efficiency, heterogeneity, and incentive challenges across horizontal, vertical, and transfer learning scenarios.

Federated LearningHorizontal FLSecure Aggregation

0 likes · 24 min read

How Federated Learning Balances Privacy and Collaboration in AI

Alimama Tech

Sep 3, 2025 · Artificial Intelligence

Privacy-Preserving Machine Learning: Balancing Data Utility and Confidentiality

Privacy-Preserving Machine Learning (PPML) integrates cryptographic techniques such as federated learning, differential privacy, homomorphic encryption, and secure multi-party computation to enable model training and inference on encrypted or distributed data, thereby breaking data silos while safeguarding privacy across sectors like healthcare, finance, and advertising.

Federated LearningHomomorphic Encryptionmachine learning

0 likes · 18 min read

Privacy-Preserving Machine Learning: Balancing Data Utility and Confidentiality

Alimama Tech

Aug 27, 2025 · Artificial Intelligence

How Multi-Attribution Learning Boosts Conversion Rate Prediction in Display Ads

This article introduces Multi-Attribution Learning (MAL), a novel paradigm that jointly models multiple attribution labels to overcome the single-attribution bottleneck in conversion rate (CVR) prediction, detailing its architecture, auxiliary tasks, extensive offline and online experiments, and significant business gains.

advertising systemsconversion rate predictionmulti-attribution learning

0 likes · 24 min read

How Multi-Attribution Learning Boosts Conversion Rate Prediction in Display Ads

Alimama Tech

Aug 20, 2025 · Information Security

How Private Information Retrieval Secures Data Queries in Modern Applications

Private Information Retrieval (PIR) is a core privacy-preserving technique that enables users to query databases without revealing their query content or access patterns, and its evolution—from early theoretical models to efficient, real‑world deployments across blockchain, cloud, and advertising—makes it essential for secure data collaboration.

Data PrivacyPrivate Information Retrievalsecure multi-party computation

0 likes · 18 min read

How Private Information Retrieval Secures Data Queries in Modern Applications

Alimama Tech

Aug 13, 2025 · Information Security

How Private Set Operations Secure Data Collaboration in the Big Data Era

Private Set Operations (PSO) enable multiple parties to perform set intersections, unions, and related computations on encrypted data, preserving privacy through cryptographic techniques such as public‑key encryption, oblivious transfer, and garbled circuits, and are applied across advertising, finance, healthcare, and government for secure data collaboration.

AdvertisingPrivacy Computingcryptography

0 likes · 20 min read

How Private Set Operations Secure Data Collaboration in the Big Data Era

Alimama Tech

Aug 6, 2025 · Information Security

How Privacy-Enhancing Technologies Are Revolutionizing Data Use in Digital Advertising

This article reviews the background, core techniques, and typical applications of privacy‑enhancing technologies—including secure multi‑party computation, privacy‑preserving machine learning, differential privacy, and trusted execution environments—highlighting their role in unlocking multi‑party data value while ensuring compliance and privacy protection.

Federated LearningPrivacy Computingdifferential privacy

0 likes · 20 min read

How Privacy-Enhancing Technologies Are Revolutionizing Data Use in Digital Advertising

Alimama Tech

Aug 6, 2025 · Artificial Intelligence

How ComRecycle Cuts CPU/GPU Use by 23% in Taobao Ads: An Intelligent Computation Recycling Framework

This paper introduces ComRecycle, an intelligent computation recycling framework for Taobao's display advertising system that caches and reuses ad candidates across recall, coarse‑ranking, and fine‑ranking stages, achieving up to 23% CPU and 22% GPU savings while maintaining recommendation quality.

Resource OptimizationUplift Modelingcomputation recycling

0 likes · 17 min read

How ComRecycle Cuts CPU/GPU Use by 23% in Taobao Ads: An Intelligent Computation Recycling Framework

Alimama Tech

Jul 23, 2025 · Artificial Intelligence

How Differentiable Solver Search Accelerates Diffusion Model Sampling

This article presents a differentiable solver search method that quickly finds high‑quality sampling paths for diffusion models, demonstrating significant FID improvements across Rectified‑Flow, DDPM/VP, and text‑to‑image models while requiring no model parameter changes.

AIDiffusion Modelsdifferentiable solver

0 likes · 20 min read

How Differentiable Solver Search Accelerates Diffusion Model Sampling

Alimama Tech

Jul 17, 2025 · Artificial Intelligence

How to Build a High‑Scoring AI Werewolf Agent: Strategies, Prompt Engineering, and Code

This article details the author's experience designing a top‑performing AI Werewolf agent for the Taotian Group's AI Werewolf Challenge, covering game rules, core challenges, prompt engineering, caching, concurrent requests, model selection, reinforcement‑learning‑style tuning, and tactical strategies for each role, with code examples.

AI AgentGame AILLM

0 likes · 25 min read

How to Build a High‑Scoring AI Werewolf Agent: Strategies, Prompt Engineering, and Code

Alimama Tech

Jul 11, 2025 · Artificial Intelligence

Inside Alibaba’s Taotian AI Team: From Werewolf Games to RecGPT

This article explores Alibaba’s Taotian technology team, revealing how its young engineers blend cutting‑edge AI research with playful projects like AI‑driven Werewolf games, develop large‑scale recommendation models such as RecGPT, and foster a culture of curiosity, rapid experimentation, and flat, tech‑first management.

AIGCArtificial IntelligenceR&D Management

0 likes · 24 min read

Inside Alibaba’s Taotian AI Team: From Werewolf Games to RecGPT