🚨 911 NIGHTMARE: Dad Calls for Help – Cops Handcuff the Victim Instead 😡 #BodyCam #HillCounty
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TIME names ‘Architects of AI’ its Person of the Year
TIME Magazine has named the ‘Architects of AI’ its Person of the Year, who include Jensen Huang, Elon Musk, Sam Altman, Mark Zuckerberg, Lisa Su, Dario Amodei, Demis Hassabis, and Fei-Fei Li
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The 5 AI Tensions Leaders Need to Navigate
Based on insights from more than 100 builders, executives, investors, advisors, and researchers from across the globe.
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7 Steps to Mastering Agentic AI
As AI systems begin handling more complex, multi-stage tasks, understanding agentic design is becoming essential. This article outlines seven practical steps to build reliable, effective AI agents.
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New method improves the reliability of statistical estimations
Let’s say an environmental scientist is studying whether exposure to air pollution is associated with lower birth weights in a particular county. They might train a machine-learning model to estimate the magnitude of this association, since machine-learning methods are especially good at learning complex relationships. Standard machine-learning methods excel at making predictions and sometimes provide uncertainties, like confidence intervals, for these predictions. However, they generally don’t provide estimates or confidence intervals when determining whether two variables are related. […]
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Stop building RAG pipelines like it’s 2023
Author(s): AI Rabbit Originally published on Towards AI. Agentic Era If your architecture still looks like “User Query Vector DB LLM,” you aren’t building an AI application; you’re building a hallucination engine. The “naive” RAG era where we just dumped PDFs into Pinecone and prayed for the best is officially over. Here is the technical reality of RAG in 2025.The article discusses the evolution of Retrieval-Augmented Generation (RAG) pipelines, emphasizing the transition from outdated linear architectures to more […]
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Supervisor SHUTS DOWN The Post Office Instead Of Following The Law!
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How to design LLMs that don’t need prompt engineering
Standard LLMs rely on prompt engineering to fix problems (hallucinations, poor response, missing information) that come from issues in the backend architecture. If the backend (corpus processing) is properly built from the ground up, it is possible to offer a full, comprehensive answer to a meaningful prompt, without the need for multiple prompts, rewording your query, having to go through a chat session, or prompt engineering. In this article, I explain how to do it, focusing on enterprise […]
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Charting the future of AI, from safer answers to faster thinking
Adoption of new tools and technologies occurs when users largely perceive them as reliable, accessible, and an improvement over the available methods and workflows for the cost. Five PhD students from the inaugural class of the MIT-IBM Watson AI Lab Summer Program are utilizing state-of-the-art resources, alleviating AI pain points, and creating new features and capabilities to promote AI usefulness and deployment — from learning when to trust a model that predicts another’s accuracy to more effectively reasoning […]
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