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​[[{“value”:” JSON Prompting is a technique for structuring instructions to AI models using the JavaScript Object Notation (JSON) format, making prompts clear, explicit, and machine-readable. Unlike traditional text-based prompts, which can leave room for ambiguity and misinterpretation, JSON prompts organize requirements as key-value pairs, arrays,… Read More »JSON Prompting for LLMs: A Practical Guide with Python Coding Examples Arham Islam Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Differential privacy (DP) stands as the gold standard for protecting user information in large-scale machine learning and data analytics. A critical task within DP is partition selection—the process of safely extracting the largest possible set of unique items from massive user-contributed datasets (such as… Read More »Google AI Proposes Novel Machine Learning Algorithms for Differentially Private Partition Selection Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Retrieval-Augmented Generation (RAG) has emerged as a cornerstone technique for enhancing Large Language Models (LLMs) with real-time, domain-specific knowledge. But the landscape is rapidly shifting—today, the most common implementations are “Native RAG” pipelines, and a new paradigm called “Agentic RAG” is redefining what’s possible… Read More »Native RAG vs. Agentic RAG: Which Approach Advances Enterprise AI Decision-Making? Michal Sutter Artificial Intelligence Category – MarkTechPost

​[[{“value”:” As data becomes more abundant and information systems grow in complexity, stakeholders need solutions that reveal quality insights. Applying emerging technologies to the geospatial domain offers a unique opportunity to create transformative user experiences and intuitive workstreams for users and organizations to deliver on… Read More »Enhance Geospatial Analysis and GIS Workflows with Amazon Bedrock Capabilities Dave Horne Artificial Intelligence

​[[{“value”:” Most organizations evaluating foundation models limit their analysis to three primary dimensions: accuracy, latency, and cost. While these metrics provide a useful starting point, they represent an oversimplification of the complex interplay of factors that determine real-world model performance. Foundation models have revolutionized how… Read More »Beyond the basics: A comprehensive foundation model selection framework for generative AI Sandeep Singh Artificial Intelligence

​[[{“value”:” Every day, organizations process millions of documents, including invoices, contracts, insurance claims, medical records, and financial statements. Despite the critical role these documents play, an estimated 80–90% of the data they contain is unstructured and largely untapped, hiding valuable insights that could transform business… Read More »Accelerate intelligent document processing with generative AI on AWS Bob Strahan Artificial Intelligence

​[[{“value”:” Amazon SageMaker HyperPod is a purpose-built infrastructure for optimizing foundation model (FM) training and inference at scale. SageMaker HyperPod removes the undifferentiated heavy lifting involved in building and optimizing machine learning (ML) infrastructure for training FMs, reducing training time by up to 40%. SageMaker… Read More »Amazon SageMaker HyperPod enhances ML infrastructure with scalability and customizability Mark Vinciguerra Artificial Intelligence

​[[{“value”:” In the rapidly evolving landscape of AI-driven automation, Zhipu AI has introduced ComputerRL, a groundbreaking framework designed to empower agents with the ability to navigate and manipulate complex digital workspaces. This innovation addresses a core challenge in AI agent development: the disconnect between computer… Read More »Zhipu AI Unveils ComputerRL: An AI Framework Scaling End-to-End Reinforcement Learning for Computer Use Agents Asif Razzaq Artificial Intelligence Category – MarkTechPost