​[[{“value”:” Music recommendation systems have become essential to streaming services, helping users discover new songs and re-listen to their favorites. These systems use algorithms that analyze users’ listening patterns, making personalized song recommendations. One key type of algorithm used in these services is sequential recommendation… Read More »PISA: A Psychology-Informed Approach to Sequential Music Recommendation with Repeat Listening Awareness Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Previous research on Retrieval-Augmented Generation (RAG) in large language models (LLMs) concentrated on enhancing retrieval models to improve document selection for generation tasks. Initial studies established the benefits of integrating external information into LLMs, but recent extensions to noisy environments often focused on a… Read More »Exploring the Dual Nature of RAG Noise: Enhancing Large Language Models Through Beneficial Noise and Mitigating Harmful Effects Shoaib Nazir Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A recent article in Computerworld argued that the output from generative AI systems, like GPT and Gemini, isn’t as good as it used to be. It isn’t the first time I’ve heard this complaint, though I don’t know how widely held that opinion is.… Read More »The AI Blues Mike Loukides AI & ML – Radar

​[[{“value”:” A significant challenge in the field of artificial intelligence, particularly in generative modeling, is understanding how diffusion models can effectively learn and generate high-dimensional data distributions. Despite their empirical success, the theoretical mechanisms that enable diffusion models to avoid the curse of dimensionality—where the… Read More »Diffusion Models Redefined: Mastering Low-Dimensional Distributions with Subspace Clustering Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The intersection of computational physics and machine learning has brought significant progress in understanding complex systems, particularly through neural networks. Graph neural networks (GNNs) have emerged as powerful tools for modeling interactions within physical systems, capitalizing on their ability to manage data-rich environments. Recently,… Read More »Researchers from Brown University Introduce Symplectic Graph Neural Networks (SympGNNs) to Revolutionize High-Dimensional Hamiltonian Systems Modeling and Overcome Challenges in Energy Conservation and Node Classification Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Speculative decoding is emerging as a vital strategy to enhance high-throughput long-context inference, especially as the need for inference with large language models (LLMs) continues to grow across numerous applications. Together AI’s research on speculative decoding tackles the problem of improving inference throughput for… Read More »Together AI Optimizing High-Throughput Long-Context Inference with Speculative Decoding: Enhancing Model Performance through MagicDec and Adaptive Sequoia Trees Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In computer vision, backbone architectures are critical in image recognition, object detection, and semantic segmentation tasks. These backbones extract local and global features from images, enabling machines to understand complex patterns. Traditionally, convolutional layers have been the primary component in these models, but recent… Read More »LowFormer: A Highly Efficient Vision Backbone Model That Optimizes Throughput and Latency for Mobile and Edge Devices Without Sacrificing Accuracy Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Building on LG AI Research’s remarkable achievements in AI language models, especially with the launch of EXAONE 3.0, the development of EXAONEPath represents another significant milestone. This new chapter in EXAONE’s journey focuses on transforming digital histopathology, a critical area in medical diagnostics, by… Read More »LG AI Research Open-Sources EXAONEPath: Transforming Histopathology Image Analysis with a 285M Patch-level Pre-Trained Model for Variety of Medical Prediction, Reducing Genetic Testing Time and Costs Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Medical LLMs like ClinicalCamel 70B and Llama3-OpenBioLLM 70B have shown strong performance in various medical NLP tasks, but no model specifically tailored to the cancer domain currently exists. Additionally, these models, with billions of parameters, are computationally demanding for many healthcare systems. A cancer-focused… Read More »CancerLLM: A Large Language Model in Cancer Domain Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This post will demonstrate the usage of Lasso, Ridge, and ElasticNet models using the Ames housing dataset. These models are particularly valuable when dealing with data that may suffer from multicollinearity. We leverage these advanced regression techniques to show how feature scaling and hyperparameter… Read More »Scaling to Success: Implementing and Optimizing Penalized Models Vinod Chugani MachineLearningMastery.com