​[[{“value”:” Large Language Models (LLMs) have transformed natural language processing, offering user modeling and personalization opportunities. However, effectively integrating user interaction data is challenging. Such data, encompassing various digital engagements, provides valuable insights but is often complex and noisy. Directly fine-tuning LLMs with interaction histories… Read More »Google AI Proposes USER-LLM: A Novel Artificial Intelligence Framework that Leverages User Embeddings to Contextualize LLMs Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Amazon Bedrock provides a broad range of models from Amazon and third-party providers, including Anthropic, AI21, Meta, Cohere, and Stability AI, and covers a wide range of use cases, including text and image generation, embedding, chat, high-level agents with reasoning and orchestration, and more.… Read More »Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock Mark Roy AWS Machine Learning Blog

​[[{“value”:” OpenSearch is a scalable, flexible, and extensible open source software suite for search, analytics, security monitoring, and observability applications, licensed under the Apache 2.0 license. Amazon OpenSearch Service is a fully managed service that makes it straightforward to deploy, scale, and operate OpenSearch in… Read More »Unlock personalized experiences powered by AI using Amazon Personalize and Amazon OpenSearch Service Reagan Rosario AWS Machine Learning Blog

​[[{“value”:” Creating scalable and efficient machine learning (ML) pipelines is crucial for streamlining the development, deployment, and management of ML models. In this post, we present a framework for automating the creation of a directed acyclic graph (DAG) for Amazon SageMaker Pipelines based on simple… Read More »Automate Amazon SageMaker Pipelines DAG creation Luis Felipe Yepez Barrios AWS Machine Learning Blog

​[[{“value”:” This guest post is written by Vihan Lakshman, Tharun Medini, and Anshumali Shrivastava from ThirdAI. Large-scale deep learning has recently produced revolutionary advances in a vast array of fields. Although this stunning progress in artificial intelligence remains remarkable, the financial costs and energy consumption… Read More »Accelerating large-scale neural network training on CPUs with ThirdAI and AWS Graviton Vihan Lakshman AWS Machine Learning Blog

​[[{“value”:” In pandas, any() function is used to check if any element in a Series satisfies the condition. It returns True if at least one element in a Series is True based on specified conditions; otherwise, it returns False. In this article, I will explain… Read More »Pandas Series any() Function Malli Spark By {Examples}

​[[{“value”:” AI’s growing influence in large organizations brings crucial challenges in managing AI platforms. These include developing a scalable and operationally efficient platform that adheres to organizational compliance and security standards. Amazon SageMaker Studio offers a comprehensive set of capabilities for machine learning (ML) practitioners… Read More »Supercharge your AI team with Amazon SageMaker Studio: A comprehensive view of Deutsche Bahn’s AI platform transformation Prasanna Tuladhar AWS Machine Learning Blog

​[[{“value”:” In deep learning, the quest for efficiency has led to a paradigm shift in how we finetune large-scale models. The research spearheaded by Soufiane Hayou, Nikhil Ghosh, and Bin Yu from the University of California, Berkeley, introduces a significant enhancement to the Low-Rank Adaptation… Read More »UC Berkeley Researchers Unveil LoRA+: A Breakthrough in Machine Learning Model Finetuning with Optimized Learning Rates for Superior Efficiency and Performance Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The rapidly developing field of Artificial Intelligence (AI) has seen a major advancement in technologies, including generative AI, deep neural networks, and Large Language Models (LLMs). AI has a wide range of effects on society, including effects on production, health, finance, and education. Proper… Read More »Balancing Power and Policy: Navigating the Future of Compute Governance in Artificial Intelligence Development Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A significant challenge confronting the deployment of LLMs is their susceptibility to adversarial attacks. These are sophisticated techniques designed to exploit vulnerabilities in the models, potentially leading to the extraction of sensitive data, misdirection, model control, denial of service, or even the propagation of… Read More »Are Your AI Conversations Safe? Exploring the Depths of Adversarial Attacks on Machine Learning Models Nikhil Artificial Intelligence Category – MarkTechPost