Exponential Moving Averages at Scale: Building Smart Time-Decay SystemsExponential Moving Averages are vital for real-time analytics in modern applications, particularly in managing the decay of relevance over time.
Boaz Shor: The Engineer Behind $80M in AI Revenue and the Future of Robotics | HackerNoonBoaz Shor's AI innovations have added $80 million to Taboola's revenue and are reshaping business growth globally.
How an AI Recommendation System Can Increase Sales (2025) - ShopifyAI recommendation systems can significantly enhance e-commerce experiences by delivering personalized product suggestions based on user data.
QCon SF: Large Scale Search and Ranking Systems at NetflixNetflix developed a Unified Contextual Recommender to combine search and recommendation, enhancing user experience across millions of items.
Efficient Incremental Processing with Netflix Maestro and Apache IcebergNetflix utilizes extensive data insights for personalized user experiences and business decisions.The company faces challenges in data management including accuracy, freshness, and cost efficiency.
Countering Mainstream Bias via End-to-End Adaptive Local Learning: Debiasing Experiments and Setup | HackerNoonThe method significantly improves debiasing performance for diverse user groups while enhancing overall model utility.
Boaz Shor: The Engineer Behind $80M in AI Revenue and the Future of Robotics | HackerNoonBoaz Shor's AI innovations have added $80 million to Taboola's revenue and are reshaping business growth globally.
How an AI Recommendation System Can Increase Sales (2025) - ShopifyAI recommendation systems can significantly enhance e-commerce experiences by delivering personalized product suggestions based on user data.
QCon SF: Large Scale Search and Ranking Systems at NetflixNetflix developed a Unified Contextual Recommender to combine search and recommendation, enhancing user experience across millions of items.
Efficient Incremental Processing with Netflix Maestro and Apache IcebergNetflix utilizes extensive data insights for personalized user experiences and business decisions.The company faces challenges in data management including accuracy, freshness, and cost efficiency.
Countering Mainstream Bias via End-to-End Adaptive Local Learning: Debiasing Experiments and Setup | HackerNoonThe method significantly improves debiasing performance for diverse user groups while enhancing overall model utility.
Making AI Recommendations Smarter with Visual, Text, and Audio Data | HackerNoonDucho facilitates multimodal extraction for applications like fashion recommendation, utilizing both visual and textual data for enhanced user insights.
Ducho: A Unified Framework for Multimodal Feature Extraction in AI-Powered Recommendations | HackerNoonDucho is designed to enhance multimodal-aware recommendation systems by providing a customizable feature extraction framework.
Making AI Recommendations Smarter with Visual, Text, and Audio Data | HackerNoonDucho facilitates multimodal extraction for applications like fashion recommendation, utilizing both visual and textual data for enhanced user insights.
Ducho: A Unified Framework for Multimodal Feature Extraction in AI-Powered Recommendations | HackerNoonDucho is designed to enhance multimodal-aware recommendation systems by providing a customizable feature extraction framework.
How Different Personalities Interact With Artificial IntelligenceAI systems enhance decision-making in high-stakes fields.User preferences and personality traits are vital for effective human-AI collaboration.
The EU wants to know just how X's recommendation algorithm worksThe European Commission is investigating X's recommendation systems for compliance with the Digital Services Act.Regulators are concerned about transparency and deceptive design practices related to content moderation.
Meta chief lays out long-term AI plan | Computer WeeklyMeta's first-quarter revenue hit $36.5bn, emphasizing long-term AI and AR investments for profitability.