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AtScale Open-Sourced Semantic Modeling Language (SML): Transforming Analytics with Industry-Standard Framework for Interoperability, Reusability, and Multidimensional Data Modeling Across Platforms Asif Razzaq Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” AtScale has made a significant move by announcing the open-source release of its Semantic Modeling Language (SML). This initiative aims to provide an industry-standard semantic modeling language that can be adopted across various platforms, fostering greater collaboration and interoperability in the analytics community. The… Read More »AtScale Open-Sourced Semantic Modeling Language (SML): Transforming Analytics with Industry-Standard Framework for Interoperability, Reusability, and Multidimensional Data Modeling Across Platforms Asif Razzaq Artificial Intelligence Category – MarkTechPost

NVIDIA Researchers Introduce Order-Preserving Retrieval-Augmented Generation (OP-RAG) for Enhanced Long-Context Question Answering with Large Language Models (LLMs) Nikhil Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” Retrieval-augmented generation (RAG), a technique that enhances the efficiency of large language models (LLMs) in handling extensive amounts of text, is critical in natural language processing, particularly in applications such as question-answering, where maintaining the context of information is crucial for generating accurate responses.… Read More »NVIDIA Researchers Introduce Order-Preserving Retrieval-Augmented Generation (OP-RAG) for Enhanced Long-Context Question Answering with Large Language Models (LLMs) Nikhil Artificial Intelligence Category – MarkTechPost

µFormer: A Deep Learning Framework for Efficient Protein Fitness Prediction and Optimization Sana Hassan Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” Protein engineering is essential for designing proteins with specific functions, but navigating the complex fitness landscape of protein mutations poses a significant challenge, making it hard to find optimal sequences. Zero-shot approaches, which predict mutational effects without relying on homologs or multiple sequence alignments… Read More »µFormer: A Deep Learning Framework for Efficient Protein Fitness Prediction and Optimization Sana Hassan Artificial Intelligence Category – MarkTechPost

Chai-1 Released by Chai Discovery Team: A Groundbreaking Multi-Modal Foundation Model Set to Transform Drug Discovery and Biological Engineering with Revolutionary Molecular Structure Prediction Asif Razzaq Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” The Chai Discovery team announced the launch of Chai-1, a groundbreaking multi-modal foundation model designed to predict molecular structures with unprecedented accuracy. This release marks a major advancement in molecular biology and drug discovery, with the model boasting state-of-the-art capabilities across a diverse range… Read More »Chai-1 Released by Chai Discovery Team: A Groundbreaking Multi-Modal Foundation Model Set to Transform Drug Discovery and Biological Engineering with Revolutionary Molecular Structure Prediction Asif Razzaq Artificial Intelligence Category – MarkTechPost

PISA: A Psychology-Informed Approach to Sequential Music Recommendation with Repeat Listening Awareness Nikhil Artificial Intelligence Category – MarkTechPost

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​[[{“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

Exploring the Dual Nature of RAG Noise: Enhancing Large Language Models Through Beneficial Noise and Mitigating Harmful Effects Shoaib Nazir Artificial Intelligence Category – MarkTechPost

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​[[{“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

Diffusion Models Redefined: Mastering Low-Dimensional Distributions with Subspace Clustering Aswin Ak Artificial Intelligence Category – MarkTechPost

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​[[{“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