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​[[{“value”:” Understanding Subgroup Fairness in Machine Learning ML Evaluating fairness in machine learning often involves examining how models perform across different subgroups defined by attributes such as race, gender, or socioeconomic background. This evaluation is essential in contexts such as healthcare, where unequal model performance… Read More »This AI Paper from Google Introduces a Causal Framework to Interpret Subgroup Fairness in Machine Learning Evaluations More Reliably Nikhil Artificial Intelligence Category – MarkTechPost

​This post is divided into three parts; they are: • Why Attention is Needed • The Attention Operation • Multi-Head Attention (MHA) • Grouped-Query Attention (GQA) and Multi-Query Attention (MQA) Traditional neural networks struggle with long-range dependencies in sequences. This post is divided into three parts;… Read More »A Gentle Introduction to Multi-Head Attention and Grouped-Query Attention Adrian Tam MachineLearningMastery.com

​[[{“value”:” In recent years, the rapid advancement of artificial intelligence and machine learning (AI/ML) technologies has revolutionized various aspects of digital content creation. One particularly exciting development is the emergence of video generation capabilities, which offer unprecedented opportunities for companies across diverse industries. This technology… Read More »Build a scalable AI video generator using Amazon SageMaker AI and CogVideoX Nick Biso Artificial Intelligence

​[[{“value”:” The AWS DeepRacer Student Portal will no longer be available starting September 15, 2025. This change comes as part of the broader transition of AWS DeepRacer from a service to an AWS Solution, representing an evolution in how we deliver AI & ML education.… Read More »Update on the AWS DeepRacer Student Portal Jayadev Kalla Artificial Intelligence

​[[{“value”:” Modern generative AI model providers require unprecedented computational scale, with pre-training often involving thousands of accelerators running continuously for days, and sometimes months. Foundation Models (FMs) demand distributed training clusters — coordinated groups of accelerated compute instances, using frameworks like PyTorch — to parallelize… Read More »Accelerate foundation model training and inference with Amazon SageMaker HyperPod and Amazon SageMaker Studio Bruno Pistone Artificial Intelligence

​[[{“value”:” The Challenge of Long-Context Reasoning in AI Models Large reasoning models are not only designed to understand language but are also structured to think through multi-step processes that require prolonged attention spans and contextual comprehension. As the expectations from AI grow, especially in real-world… Read More »MiniMax AI Releases MiniMax-M1: A 456B Parameter Hybrid Model for Long-Context and Reinforcement Learning RL Tasks Nikhil Artificial Intelligence Category – MarkTechPost

​MLOps, or machine learning operations, is all about managing the end-to-end process of building, training, deploying, and maintaining machine learning models. MLOps, or machine learning operations, is all about managing the end-to-end process of building, training, deploying, and maintaining machine learning models.  Read More  

​[[{“value”:” The Challenge of Multimodal Reasoning Recent breakthroughs in text-based language models, such as DeepSeek-R1, have demonstrated that RL can aid in developing strong reasoning skills. Motivated by this, researchers have attempted to apply the same RL techniques to MLLMs to enhance their ability to… Read More »ReVisual-R1: An Open-Source 7B Multimodal Large Language Model (MLLMs) that Achieves Long, Accurate and Thoughtful Reasoning Sana Hassan Artificial Intelligence Category – MarkTechPost