​[[{“value”:”This paper was accepted at the NeurIPS Datasets and Benchmarks Workshop at NeurIPS 2024 We introduce DataComp for Language Models (DCLM), a testbed for controlled dataset experiments with the goal of improving language models. As part of DCLM, we provide a standardized corpus of 240T… Read More »DataComp-LM: In Search of the Next Generation of Training Sets for Language Models Apple Machine Learning Research

​[[{“value”:” Today, we are excited to announce a new capability in Amazon SageMaker inference that can help you reduce the time it takes for your generative artificial intelligence (AI) models to scale automatically. You can now use sub-minute metrics and significantly reduce overall scaling latency… Read More »Amazon SageMaker inference launches faster auto scaling for generative AI models James Park AWS Machine Learning Blog

​[[{“value”:” Amazon Q Business is a fully managed, generative artificial intelligence (AI)-powered assistant that helps enterprises unlock the value of their data and knowledge. With Amazon Q, you can quickly find answers to questions, generate summaries and content, and complete tasks by using the information… Read More »Find answers accurately and quickly using Amazon Q Business with the SharePoint Online connector Vijai Gandikota AWS Machine Learning Blog

​[[{“value”:” As conversational artificial intelligence (AI) agents gain traction across industries, providing reliability and consistency is crucial for delivering seamless and trustworthy user experiences. However, the dynamic and conversational nature of these interactions makes traditional testing and evaluation methods challenging. Conversational AI agents also encompass… Read More »Evaluate conversational AI agents with Amazon Bedrock Sharon Li AWS Machine Learning Blog

​[[{“value”:” Implementing hardware resiliency in your training infrastructure is crucial to mitigating risks and enabling uninterrupted model training. By implementing features such as proactive health monitoring and automated recovery mechanisms, organizations can create a fault-tolerant environment capable of handling hardware failures or other issues without… Read More »Node problem detection and recovery for AWS Neuron nodes within Amazon EKS clusters Darren Lin AWS Machine Learning Blog

​Breakthrough models AlphaProof and AlphaGeometry 2 solve advanced reasoning problems in mathematics Breakthrough models AlphaProof and AlphaGeometry 2 solve advanced reasoning problems in mathematics  Read More  

​[[{“value”:” Theorem proving in mathematics faces growing challenges due to increasing proof complexity. Formalized systems like Lean, Isabelle, and Coq offer computer-verifiable proofs, but creating these demands substantial human effort. Large language models (LLMs) show promise in solving high-school-level math problems using proof assistants, yet… Read More »LEAN-GitHub: A Large-Scale Dataset for Advancing Automated Theorem Proving Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Question answering (QA) is a crucial area in natural language processing (NLP), focusing on developing systems that can accurately retrieve and generate responses to user queries from extensive data sources. Retrieval-augmented generation (RAG)  enhances the quality and relevance of answers by combining information retrieval… Read More »This AI Paper Introduces Long-form RobustQA Dataset and RAG-QA Arena for Cross-Domain Evaluation of Retrieval-Augmented Generation Systems Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” AutoML is a tool designed for both technical and non-technical experts. It simplifies the process of training machine learning models. All you have to do is provide it with the dataset, and in return, it will provide you with the best-performing model for your… Read More »Introduction to AutoML: Automating Machine Learning Workflows Matthew Mayo MachineLearningMastery.com

​[[{“value”:” Video large language models (LLMs) have emerged as powerful tools for processing video inputs and generating contextually relevant responses to user commands. However, these models face significant challenges in their current methodologies. The primary issue lies in the high computational and labeling costs associated… Read More »SF-LLaVA: A Training-Free Video LLM that is Built Upon LLaVA-NeXT and Requires No Additional Fine-Tuning to Work Effectively for Various Video Tasks Mohammad Asjad Artificial Intelligence Category – MarkTechPost