​[[{“value”:” The convergence of artificial intelligence with physical systems marks a pivotal moment in technological evolution. Physical AI, where algorithms transcend digital boundaries to perceive, understand, and manipulate the tangible world, will fundamentally transform how enterprises operate across industries. These intelligent systems bridge the gap… Read More »Transforming the physical world with AI: the next frontier in intelligent automation  Sri Elaprolu, Alla Simoneau, Paul Amadeo, and Randi Larson Artificial Intelligence

​[[{“value”:” Evaluating LLM applications, particularly those using RAG (Retrieval-Augmented Generation), is crucial but often neglected. Without proper evaluation, it’s almost impossible to confirm if your system’s retriever is effective, if the LLM’s answers are grounded in the sources (or hallucinating), and if the context size… Read More »How to Evaluate Your RAG Pipeline with Synthetic Data? Arham Islam Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In healthcare, the ability to quickly analyze and interpret medical reports is crucial for both healthcare providers and patients. While medical reports contain valuable information, they often remain underutilized due to their complex nature and the time-intensive process of analysis. This complexity manifests in… Read More »Medical reports analysis dashboard using Amazon Bedrock, LangChain, and Streamlit Aditya Ranjan Artificial Intelligence

​[[{“value”:” This post was written with Ajay Nyamati from Kitsa. The clinical trial industry conducts medical research studies to evaluate the safety, efficacy, and effectiveness of new drugs, treatments, or medical devices before they reach the market. The industry is a cornerstone of medical innovation,… Read More »Kitsa transforms clinical trial site selection with Amazon Quick Automate Chethan Shriyan Artificial Intelligence

​[[{“value”:” Organizations need solutions for people and AI agents to securely collaborate through a single interface to the organization’s data and take actions across enterprise applications to improve productivity. The ability of an AI agent to securely and seamlessly connect with organizational knowledge bases, enterprise… Read More »Connect Amazon Quick Suite to enterprise apps and agents with MCP Abhinav Jawadekar Artificial Intelligence

​[[{“value”:” Get agents out of prototype purgatory and into production with security, scalability, and reliability When we launched AWS in 2006, we believed that cloud computing would transform how organizations build and scale technology. We’re now at a similar inflection point with AI agents. We… Read More »Make agents a reality with Amazon Bedrock AgentCore: Now generally available Swami Sivasubramanian Artificial Intelligence

​[[{“value”:” Home Table of Contents KV Cache Optimization via Multi-Head Latent Attention Recap of KV Cache The Need for KV Cache Optimization Multi-Head Latent Attention (MLA) Low-Rank KV Projection Up-Projection Decoupled Rotary Position Embeddings (RoPE) RoPE in Standard MHA Challenges in MLA: The Need for… Read More »KV Cache Optimization via Multi-Head Latent Attention Puneet Mangla PyImageSearch

​[[{“value”:” The agentic AI landscape is exploding. Every new framework, demo, and announcement promises to let your AI assistant book flights, query databases, and manage calendars. This rapid advancement of capabilities is thrilling for users, but for the architects and engineers building these systems, it… Read More »The Architect’s Dilemma Heiko Hotz AI & ML – Radar

​Large dataset handling in Python is not exempt from challenges like memory constraints and slow processing workflows. Large dataset handling in Python is not exempt from challenges like memory constraints and slow processing workflows.  Read More