​[[{“value”:” Researchers from Microsoft attempt to solve the challenge faced in predicting molecular properties and simulating molecular dynamics by presenting a method, ViSNet, that results in more accurate predictions. Predicting molecular properties is crucial for understanding structure-activity relationships (SAR) in drug discovery, biotechnology, and materials… Read More »Microsoft Researchers Propose ViSNet: An Equivariant Geometry-Enhanced Graph Neural Network for Predicting Molecular Properties and Simulating Molecular Dynamics  Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” From producing writing that resembles that of a human being to comprehending subtleties of language, Large Language Models (LLMs) have played a key role in attaining state-of-the-art performance in various Natural Language Processing (NLP) applications. However, their efficacy wanes when processing texts exceeding their… Read More »Efficiently Processing Extended Contexts in Large Language Models: Dual Chunk Attention for Training-Free Long-Context Support Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The recent success of large language models relies heavily on extensive text datasets for pre-training. However, indiscriminate use of all available data may not be optimal due to varying quality. Data selection methods are crucial for optimizing training datasets and reducing costs and carbon… Read More »Maximizing Efficiency in AI Training: A Deep Dive into Data Selection Practices and Future Directions Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This post is co-written with Sherwin Chu from Alida. Alida helps the world’s biggest brands create highly engaged research communities to gather feedback that fuels better customer experiences and product innovation. Alida’s customers receive tens of thousands of engaged responses for a single survey,… Read More »Alida gains deeper understanding of customer feedback with Amazon Bedrock Kinman Lam AWS Machine Learning Blog

​[[{“value”:” Artificial intelligence (AI) is rapidly evolving, with researchers tirelessly working to enhance its capabilities and applications. At the forefront of this innovation are generative models pushing the boundaries of what machines can understand and create. With each passing day, the improvements in state-of-the-art models… Read More »Revolutionizing AI: Introducing the Claude 3 Model Family for Enhanced Cognitive Performance Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In an era of ubiquitous digital interfaces, the quest to refine the interaction between humans and computers has led to significant technological strides. A pivotal area of focus is automating the mundane and repetitive tasks that require unyielding human supervision, aiming for a future… Read More »This AI Paper from CMU Introduce OmniACT: The First-of-a-Kind Dataset and Benchmark for Assessing an Agent’s Capability to Generate Executable Programs to Accomplish Computer Tasks Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Image Quality Assessment (IQA) is a method that standardizes the evaluation criteria for analyzing different aspects of images, including structural information, visual content, etc. To improve this method, various subjective studies have adopted comparative settings. In recent studies, researchers have explored large multimodal models… Read More »Revolutionizing Image Quality Assessment: The Introduction of Co-Instruct and MICBench for Enhanced Visual Comparisons Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Efficiency of Large Language Models (LLMs) is a focal point for researchers in AI. A groundbreaking study by Qualcomm AI Research introduces a method known as GPTVQ, which leverages vector quantization (VQ) to enhance the size-accuracy trade-off in neural network quantization significantly. This approach… Read More »Qualcomm AI Research Proposes the GPTVQ Method: A Fast Machine Learning Method for Post-Training Quantization of Large Networks Using Vector Quantization (VQ) Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Developing large language models (LLMs) in artificial intelligence represents a significant leap forward. These models underpin many of today’s advanced natural language processing tasks and have become indispensable tools for understanding and generating human language. However, these models’ computational and memory demands, especially during… Read More »This Machine Learning Paper from Microsoft Proposes ChunkAttention: A Novel Self-Attention Module to Efficiently Manage KV Cache and Accelerate the Self-Attention Kernel for LLMs Inference Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:”Posted by Kate Weber and Shannon Leon, Google Research, Quantum AI Team Today the 2024 March Meeting of the American Physical Society (APS) kicks off in Minneapolis, MN. A premier conference on topics ranging across physics and related fields, APS 2024 brings together researchers, students,… Read More »Google at APS 2024 Google AI Google AI Blog