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SFR-GNN: A Novel Graph Neural Networks (GNN) Model that Employs an ‘Attribute Pre-Training and Structure Fine-Tuning’ Strategy to Achieve Robustness Against Structural Attacks Mohammad Asjad Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” Graph Neural Networks (GNNs) have emerged as the leading approach for graph learning tasks across various domains, including recommender systems, social networks, and bioinformatics. However, GNNs have shown vulnerability to adversarial attacks, particularly structural attacks that modify graph edges. These attacks pose significant challenges… Read More »SFR-GNN: A Novel Graph Neural Networks (GNN) Model that Employs an ‘Attribute Pre-Training and Structure Fine-Tuning’ Strategy to Achieve Robustness Against Structural Attacks Mohammad Asjad Artificial Intelligence Category – MarkTechPost

MemLong: Revolutionizing Long-Context Language Modeling with Memory-Augmented Retrieval Shreya Maji Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” The paper “MemLong: Memory-Augmented Retrieval for Long Text Modeling” addresses a critical limitation regarding the ability to process long contexts in the field of Large Language Models (LLMs). While LLMs have shown remarkable success in various applications, they struggle with long-sequence tasks due to… Read More »MemLong: Revolutionizing Long-Context Language Modeling with Memory-Augmented Retrieval Shreya Maji Artificial Intelligence Category – MarkTechPost

Scalable Multi-Agent Reinforcement Learning Framework for Efficient Decision-Making in Large-Scale Systems Sana Hassan Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” The primary challenge in scaling large-scale AI systems is achieving efficient decision-making while maintaining performance. Distributed AI, particularly multi-agent reinforcement learning (MARL), offers potential by decomposing complex tasks and distributing them across collaborative nodes. However, real-world applications face limitations due to high communication and… Read More »Scalable Multi-Agent Reinforcement Learning Framework for Efficient Decision-Making in Large-Scale Systems Sana Hassan Artificial Intelligence Category – MarkTechPost

Reflection 70B: A Ground Breaking Open-Source LLM, Trained with a New Technique called Reflection-Tuning that Teaches a LLM to Detect Mistakes in Its Reasoning and Correct Course Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” Hallucination is a phenomenon where large language models (LLMs) produce responses that are not grounded in reality or do not align with the provided context, generating incorrect, misleading, or nonsensical information. These errors can have serious consequences, particularly in applications that require high precision,… Read More »Reflection 70B: A Ground Breaking Open-Source LLM, Trained with a New Technique called Reflection-Tuning that Teaches a LLM to Detect Mistakes in Its Reasoning and Correct Course Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

DeepSeek-V2.5 Released by DeepSeek-AI: A Cutting-Edge 238B Parameter Model Featuring Mixture of Experts (MoE) with 160 Experts, Advanced Chat, Coding, and 128k Context Length Capabilities Asif Razzaq Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” DeepSeek-AI has released DeepSeek-V2.5, a powerful Mixture of Experts (MOE) model with 238 billion parameters, featuring 160 experts and 16 billion active parameters for optimized performance. The model excels in chat and coding tasks, with cutting-edge capabilities such as function calls, JSON output generation,… Read More »DeepSeek-V2.5 Released by DeepSeek-AI: A Cutting-Edge 238B Parameter Model Featuring Mixture of Experts (MoE) with 160 Experts, Advanced Chat, Coding, and 128k Context Length Capabilities Asif Razzaq Artificial Intelligence Category – MarkTechPost

Detecting and Overcoming Perfect Multicollinearity in Large Datasets Vinod Chugani MachineLearningMastery.com

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​[[{“value”:” One of the significant challenges statisticians and data scientists face is multicollinearity, particularly its most severe form, perfect multicollinearity. This issue often lurks undetected in large datasets with many features, potentially disguising itself and skewing the results of statistical models. In this post, we… Read More »Detecting and Overcoming Perfect Multicollinearity in Large Datasets Vinod Chugani MachineLearningMastery.com

How Vidmob is using generative AI to transform its creative data landscape Mickey Alon AWS Machine Learning Blog

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​[[{“value”:” This post was co-written with Mickey Alon from Vidmob. Generative artificial intelligence (AI) can be vital for marketing because it enables the creation of personalized content and optimizes ad targeting with predictive analytics. Specifically, such data analysis can result in predicting trends and public… Read More »How Vidmob is using generative AI to transform its creative data landscape Mickey Alon AWS Machine Learning Blog

Fine-tune Llama 3 for text generation on Amazon SageMaker JumpStart Ben Friebe AWS Machine Learning Blog

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​[[{“value”:” Generative artificial intelligence (AI) models have become increasingly popular and powerful, enabling a wide range of applications such as text generation, summarization, question answering, and code generation. However, despite their impressive capabilities, these models often struggle with domain-specific tasks or use cases due to… Read More »Fine-tune Llama 3 for text generation on Amazon SageMaker JumpStart Ben Friebe AWS Machine Learning Blog

Ground truth curation and metric interpretation best practices for evaluating generative AI question answering using FMEval Samantha Stuart AWS Machine Learning Blog

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​[[{“value”:” Generative artificial intelligence (AI) applications powered by large language models (LLMs) are rapidly gaining traction for question answering use cases. From internal knowledge bases for customer support to external conversational AI assistants, these applications use LLMs to provide human-like responses to natural language queries.… Read More »Ground truth curation and metric interpretation best practices for evaluating generative AI question answering using FMEval Samantha Stuart AWS Machine Learning Blog