An anomaly detection framework anyone can use

An anomaly detection framework anyone can use

Sarah Alnegheimish’s research interests reside at the intersection of machine learning and systems engineering. Her objective: to make machine learning systems more accessible, transparent, and trustworthy. Alnegheimish is a PhD student in Principal Research Scientist Kalyan Veeramachaneni’s Data-to-AI group in MIT’s Laboratory for Information and Decision Systems (LIDS). Here, she commits most of her energy…

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LlamaFirewall: Open-source framework to detect and mitigate AI centric security risks – Help Net Security

LlamaFirewall: Open-source framework to detect and mitigate AI centric security risks – Help Net Security

LlamaFirewall is a system-level security framework for LLM-powered applications, built with a modular design to support layered, adaptive defense. It is designed to mitigate a wide spectrum of AI agent security risks including jailbreaking and indirect prompt injection, goal hijacking, and insecure code outputs. Why Meta created LlamaFirewall LLMs are moving far beyond simple chatbot…

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Building A Practical UX Strategy Framework — Smashing Magazine

Building A Practical UX Strategy Framework — Smashing Magazine

Learn how to create and implement a UX strategy framework that shapes work and drives real business value. In my experience, most UX teams find themselves primarily implementing other people’s ideas rather than leading the conversation about user experience. This happens because stakeholders and decision-makers often lack a deep understanding of UX’s capabilities and potential….

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Ming-Lite-Uni: An Open-Source AI Framework Designed to Unify Text and Vision through an Autoregressive Multimodal Structure

Ming-Lite-Uni: An Open-Source AI Framework Designed to Unify Text and Vision through an Autoregressive Multimodal Structure

Multimodal AI rapidly evolves to create systems that can understand, generate, and respond using multiple data types within a single conversation or task, such as text, images, and even video or audio. These systems are expected to function across diverse interaction formats, enabling more seamless human-AI communication. With users increasingly engaging AI for tasks like…

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Web Components Vs. Framework Components: What’s The Difference? — Smashing Magazine

Web Components Vs. Framework Components: What’s The Difference? — Smashing Magazine

Some critics question the agnostic nature of Web Components, with some even arguing that they are not real components. Gabriel Shoyomboa explores this topic in-depth, comparing Web Components and framework components, highlighting their strengths and trade-offs, and evaluating their performance. It might surprise you that a distinction exists regarding the word “component,” especially in front-end…

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Meet PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC

Meet PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities across various domains, propelling their evolution into multi-modal agents for human assistance. GUI automation agents for PCs face particularly daunting challenges compared to smartphone counterparts. PC environments present significantly more complex interactive elements with dense, diverse icons and widgets often lacking textual labels, leading to perception…

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Tufa Labs Introduced LADDER: A Recursive Learning Framework Enabling Large Language Models to Self-Improve without Human Intervention

Tufa Labs Introduced LADDER: A Recursive Learning Framework Enabling Large Language Models to Self-Improve without Human Intervention

Large Language Models (LLMs) benefit significantly from reinforcement learning techniques, which enable iterative improvements by learning from rewards. However, training these models efficiently remains challenging, as they often require extensive datasets and human supervision to enhance their capabilities. Developing methods that allow LLMs to self-improve autonomously without additional human input or large-scale architectural modifications has…

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