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Safety findings from the phase 1/2 MOSAIC study of miransertib for patients with PIK3CA-related overgrowth spectrum or Proteus syndrome
CONCLUSION: Miransertib was safe and tolerable in participants with a confirmed diagnosis of PROS or Proteus syndrome. Future investigations are needed to determine whether patients receive measurable clinical benefit from miransertib. →
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The VIP trial: a randomised controlled trial of the clinical effectiveness of a Victim Improvement Package (VIP) for the reduction of continued symptoms of depression or anxiety in older victims of community crime in an English city
CONCLUSIONS: Community crime had long-lasting impacts. The police are ideally placed to screen for distress, present in 35% of victims, but only 58% of participants were recruited and the cognitive-behavioural therapy was not delivered competently. Further research on victim care and improving the delivery and quality of therapy is required. →
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The U.S. White House Releases AI Playbook: A Bold Strategy to Lead the Global AI Race
«`html The U.S. White House Releases AI Playbook: A Bold Strategy to Lead the Global AI Race The White House has released the U.S. AI Playbook—formally titled “America’s AI Action Plan”—which outlines a comprehensive federal strategy emphasizing the United States’ commitment to artificial intelligence. This initiative aims to accelerate AI development across various sectors, from… →
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Building a Context-Aware Multi-Agent AI System Using Nomic Embeddings and Gemini LLM
«`html Understanding the Target Audience The target audience for building a context-aware multi-agent AI system using Nomic embeddings and Gemini LLM primarily consists of: AI researchers and developers looking to implement advanced AI solutions. Business professionals interested in leveraging AI for improved decision-making and operational efficiency. Data scientists and machine learning engineers aiming to enhance… →
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VLM2Vec-V2: A Unified Computer Vision Framework for Multimodal Embedding Learning Across Images, Videos, and Visual Documents
VLM2Vec-V2: A Unified Computer Vision Framework for Multimodal Embedding Learning Across Images, Videos, and Visual Documents Understanding the Target Audience The target audience for VLM2Vec-V2 primarily includes researchers, data scientists, and business professionals in the fields of artificial intelligence and computer vision. These individuals are typically engaged in developing or implementing AI solutions that require… →
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Key Factors That Drive Successful MCP Implementation and Adoption
«`html Key Factors That Drive Successful MCP Implementation and Adoption The Model Context Protocol (MCP) is transforming the interaction between intelligent agents and backend services, applications, and data. A successful MCP implementation project requires more than just protocol-compliant code; it necessitates a systematic approach to adoption that encompasses architecture, security, user experience, and operational rigor.… →
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NVIDIA AI Dev Team Releases Llama Nemotron Super v1.5: Setting New Standards in Reasoning and Agentic AI
«`html Understanding the Target Audience for Llama Nemotron Super v1.5 The target audience for NVIDIA’s Llama Nemotron Super v1.5 primarily includes AI developers, data scientists, and business leaders in technology-driven enterprises. These individuals are typically looking to enhance their AI capabilities for complex reasoning tasks and agentic applications. Pain Points Difficulty in achieving high accuracy… →
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Building a Multi-Node Graph-Based AI Agent Framework for Complex Task Automation
«`html Building a Multi-Node Graph-Based AI Agent Framework for Complex Task Automation In this tutorial, we guide you through the development of an advanced Graph Agent framework, powered by the Google Gemini API. Our goal is to build intelligent, multi-step agents that execute tasks through a well-defined graph structure of interconnected nodes. Each node represents… →
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Why Context Matters: Transforming AI Model Evaluation with Contextualized Queries
Why Context Matters: Transforming AI Model Evaluation with Contextualized Queries The target audience for this content primarily includes AI researchers, data scientists, software developers, and business managers who are interested in enhancing AI model performance and evaluation methods. Their pain points often involve the challenges of ambiguous user queries, leading to inaccuracies in AI responses… →
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GenSeg: Generative AI Transforms Medical Image Segmentation in Ultra Low-Data Regimes
«`html GenSeg: Generative AI Transforms Medical Image Segmentation in Ultra Low-Data Regimes Medical image segmentation is crucial in modern healthcare AI, enabling tasks such as disease detection, progression monitoring, and personalized treatment planning. In fields like dermatology, radiology, and cardiology, the need for precise segmentation—assigning a class to every pixel in a medical image—is critical.… →