​[[{“value”:” In today’s fast-paced business environment, organizations are constantly seeking innovative ways to enhance employee experience and productivity. There are many challenges that can impact employee productivity, such as cumbersome search experiences or finding specific information across an organization’s vast knowledge bases. Additionally, with the… Read More »Build a generative AI assistant to enhance employee experience using Amazon Q Business Puneeth Komaragiri AWS Machine Learning Blog

​[[{“value”:” Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra helps you aggregate content from a variety of content repositories into a centralized index that lets you quickly search all your enterprise data and find the most accurate answer. Amazon Kendra… Read More »Introducing document-level sync reports: Enhanced data sync visibility in Amazon Kendra Aneesh Mohan AWS Machine Learning Blog

​[[{“value”:” Categorical variables are pivotal as they often carry essential information that influences the outcome of predictive models. However, their non-numeric nature presents unique challenges in model processing, necessitating specific strategies for encoding. This post will begin by discussing the different types of categorical data… Read More »Decision Trees and Ordinal Encoding: A Practical Guide Vinod Chugani MachineLearningMastery.com

​[[{“value”:” The University of Washington and the Allen Institute for AI (Ai2) have recently made a significant contribution to the AI research community by releasing their cutting-edge language models: MagpieLM-4B-Chat-v0.1 and MagpieLM-8B-Chat-v0.1. Part of the larger MagpieLM project, these models are specifically designed to address… Read More »MagpieLM-4B-Chat-v0.1 and MagpieLM-8B-Chat-v0.1 Released: Groundbreaking Open-Source Small Language Models for AI Alignment and Research Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Every industry uses data to make smarter decisions. But raw data can be messy and hard to understand. EDA allows you to explore and understand your data better. In this article, we’ll walk you through the basics of EDA with simple steps and examples… Read More »From Data to Insights: A Beginner’s Journey in Exploratory Data Analysis Jayita Gulati MachineLearningMastery.com

​[[{“value”:” A committee of experts from top U.S. medical centers and research institutes is harnessing NVIDIA-powered federated learning to evaluate the impact of federated learning and AI-assisted annotation to train AI models for tumor segmentation. Federated learning is a technique for developing more accurate, generalizable… Read More »Medical Centers Tap AI, Federated Learning for Better Cancer Detection Isha Salian – Archives Page 1 | NVIDIA Blog

​[[{“value”:” Multimodal large language models (MLLMs) focus on creating artificial intelligence (AI) systems that can interpret textual and visual data seamlessly. These models aim to bridge the gap between natural language understanding and visual comprehension, allowing machines to cohesively process various forms of input, from… Read More »This AI Paper by NVIDIA Introduces NVLM 1.0: A Family of Multimodal Large Language Models with Improved Text and Image Processing Capabilities Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Generative AI has emerged as a pivotal field with the rise of large language models (LLMs). These models are capable of producing complex outputs based on a variety of prompts. One notable area within this domain is Retrieval Augmented Generation (RAG), which integrates external… Read More »Salesforce AI Research Unveiled SFR-RAG: A 9-Billion Parameter Model Revolutionizing Contextual Accuracy and Efficiency in Retrieval Augmented Generation Frameworks Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Efficient optimization of large-scale deep learning models remains a significant challenge as the cost of training large language models (LLMs) continues to escalate. As models grow larger, the computational burden and time required for training increase substantially, creating a demand for more efficient optimizers… Read More »Can We Optimize Large Language Models Faster Than Adam? This AI Paper from Harvard Unveils SOAP to Improve and Stabilize Shampoo in Deep Learning Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Predicting the long-term behavior of chaotic systems, such as those used in climate modeling, is essential but requires significant computational resources due to the need for high-resolution spatiotemporal grids. One alternative to fully-resolved simulations (FRS) is to use coarse grids, with closure models correcting… Read More »Efficient Long-Term Prediction of Chaotic Systems Using Physics-Informed Neural Operators: Overcoming Limitations of Traditional Closure Models Sana Hassan Artificial Intelligence Category – MarkTechPost