​[[{“value”:” Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI, allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. This process involves updating the model’s weights to improve its performance on targeted applications. By fine-tuning, the LLM can… Read More »Best practices and lessons for fine-tuning Anthropic’s Claude 3 Haiku on Amazon Bedrock Yanyan Zhang AWS Machine Learning Blog

​[[{“value”:” As enterprises increasingly embrace generative AI , they face challenges in managing the associated costs. With demand for generative AI applications surging across projects and multiple lines of business, accurately allocating and tracking spend becomes more complex. Organizations need to prioritize their generative AI… Read More »Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock Kyle Blocksom AWS Machine Learning Blog

​[[{“value”:” Traditionally, clinical trials not only place a significant burden on patients and participants due to the costs associated with transportation, lodging, meals, and dependent care, but also have an environmental impact. With the advancement of available technologies, decentralized clinical trials have become a widely… Read More »Advance environmental sustainability in clinical trials using AWS Sidharth Rampally AWS Machine Learning Blog

​[[{“value”:” Amazon Q Business is a generative AI-powered assistant designed to enhance enterprise operations. It’s a fully managed service that helps provide accurate answers to users’ questions while adhering to the security and access restrictions of the content. You can tailor Amazon Q Business to… Read More »Use Amazon Q to find answers on Google Drive in an enterprise Glen Ireland AWS Machine Learning Blog

​[[{“value”:” This post is co-written with David Gildea and Tom Nijs from Druva. Druva enables cyber, data, and operational resilience for thousands of enterprises, and is trusted by 60 of the Fortune 500. Customers use Druva Data Resiliency Cloud to simplify data protection, streamline data… Read More »How Druva used Amazon Bedrock to address foundation model complexity when building Dru, Druva’s backup AI copilot David Gildea AWS Machine Learning Blog

​[[{“value”:” The world of software development has seen an explosion in the use of AI agents over the last few years, promising to enhance productivity, automate complex tasks, and make the lives of developers easier. However, one problem that remains prevalent is the significant gap… Read More »All Hands AI Open Sources OpenHands CodeAct 2.1: A New Software Development Agent to Solve Over 50% of Real Github Issues in SWE-Bench Asif Razzaq Artificial Intelligence Category – MarkTechPost

​In recent years, the finance industry has been experiencing significant changes, with artificial intelligence and machine learning (ML) playing an increasingly important role. In recent years, the finance industry has been experiencing significant changes, with artificial intelligence and machine learning (ML) playing an increasingly important role.  Read… Read More »Industries in Focus: Machine Learning in Finance Vinod Chugani MachineLearningMastery.com

​[[{“value”:” Large Language Models (LLMs) are widely used in natural language tasks, from question-answering to conversational AI. However, a persistent issue with LLMs is “hallucination,” where the model generates responses that are factually incorrect or ungrounded in reality. These hallucinations can diminish the reliability of… Read More »WACK: Advancing Hallucination Detection by Identifying Knowledge-Based Errors in Language Models Through Model-Specific, High-Precision Datasets and Prompting Techniques Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Quality of Service (QoS) is a very important metric used to evaluate the performance of network services in mobile edge environments where mobile devices frequently request services from edge servers. It includes dimensions like bandwidth, latency, jitter, and data packet loss rate. However, most… Read More »CHESTNUT: A QoS Dataset for Mobile Edge Environments Nazmi Syed Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) are increasingly utilized for complex reasoning tasks, requiring them to provide accurate responses across various challenging scenarios. These tasks include logical reasoning, complex mathematics, and intricate planning applications, which demand the ability to perform multi-step reasoning and solve problems in… Read More »AUTO-CEI: A Curriculum and Expert Iteration Approach to Elevate LLMs’ Response Precision and Control Refusal Rates Across Diverse Reasoning Domains Mohammad Asjad Artificial Intelligence Category – MarkTechPost