​[[{“value”:” Many organizations are building generative AI applications powered by large language models (LLMs) to boost productivity and build differentiated experiences. These LLMs are large and complex and deploying them requires powerful computing resources and results in high inference costs. For businesses and researchers with… Read More »Brilliant words, brilliant writing: Using AWS AI chips to quickly deploy Meta LLama 3-powered applications Zheng Zhang AWS Machine Learning Blog

​[[{“value”:” In Part 1 of this series, we explored best practices for creating accurate and reliable agents using Amazon Bedrock Agents. Amazon Bedrock Agents help you accelerate generative AI application development by orchestrating multistep tasks. Agents use the reasoning capability of foundation models (FMs) to… Read More »Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 2 Maira Ladeira Tanke AWS Machine Learning Blog

​[[{“value”:” Artificial intelligence is advancing rapidly, but enterprises face many obstacles when trying to leverage AI effectively. Organizations require models that are adaptable, secure, and capable of understanding domain-specific contexts while also maintaining compliance and privacy standards. Traditional AI models often struggle with delivering such… Read More »IBM Releases Granite 3.0 2B and 8B AI Models for AI Enterprises Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Model Predictive Control (MPC), or receding horizon control, aims to maximize an objective function over a planning horizon by leveraging a dynamics model and a planner to select actions. The flexibility of MPC allows it to adapt to novel reward functions at test time,… Read More »Google DeepMind Introduces Diffusion Model Predictive Control (D-MPC): Combining Multi-Step Action Proposals and Dynamics Models Using Diffusion Models for Online MPC Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Home Table of Contents Predictive Maintenance Using Isolation Forest What Is Predictive Maintenance? And Why Anomaly Detection? Predictive Maintenance Predictive Maintenance as Anomaly Detection The Isolation Forest Algorithm Isolation Trees Anomaly Score Building the Forest Implementing Predictive Maintenance Using Isolation Forest Setup and Data… Read More »Predictive Maintenance Using Isolation Forest Puneet Mangla PyImageSearch

​[[{“value”:” Large language models (LLMs) have revolutionized various domains, including code completion, where artificial intelligence predicts and suggests code based on a developer’s previous inputs. This technology significantly enhances productivity, enabling developers to write code faster and with fewer errors. Despite the promise of LLMs,… Read More »aiXcoder-7B: A Lightweight and Efficient Large Language Model Offering High Accuracy in Code Completion Across Multiple Languages and Benchmarks Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have revolutionized the field of artificial intelligence by performing a wide range of tasks across different domains. These models are expected to work seamlessly in multiple languages, solving complex problems while ensuring safety. However, the challenge lies in maintaining safety… Read More »This AI Research from Cohere for AI Compares Merging vs Data Mixing as a Recipe for Building High-Performant Aligned LLMs Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Vision-Language-Action Models (VLA) for robotics are trained by combining large language models with vision encoders and then fine-tuning them on various robot datasets; this allows generalization to new instructions, unseen objects, and distribution shifts. However, various real-world robot datasets mostly require human control, which… Read More »Latent Action Pretraining for General Action models (LAPA): An Unsupervised Method for Pretraining Vision-Language-Action (VLA) Models without Ground-Truth Robot Action Labels Nazmi Syed Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A primary feature of sophisticated language models is In-Context Learning (ICL), which allows the model to produce answers based on input instances without being specifically instructed on how to complete the task. In ICL, a few examples that show the intended behavior or pattern… Read More »This Machine Learning Research Discusses How Task Diversity Shortens the In-Context Learning (ICL) Plateau Tanya Malhotra Artificial Intelligence Category – MarkTechPost