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Population-Based Digital Health Interventions to Deliver at-Home COVID-19 Testing: SCALE-UP II Randomized Clinical Trial
CONCLUSIONS: Simple bidirectional text messaging was more effective than an interactive web-based chatbot on the delivery of COVID-19 testing. Although messaging every 10 days was more effective than every 30 days, it also led to a larger opt-out rate. Digital health interventions based on automated bidirectional SMS text messaging are a simple, scalable, and low-cost… →
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Too Much Thinking Can Break LLMs: Inverse Scaling in Test-Time Compute
«`html Too Much Thinking Can Break LLMs: Inverse Scaling in Test-Time Compute Recent advances in large language models (LLMs) have encouraged the idea that allowing models to “think longer” during inference typically improves their accuracy and robustness. Techniques such as chain-of-thought prompting, step-by-step explanations, and increasing “test-time compute” have become standard in the field. However,… →
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A Coding Guide to Build a Scalable Multi-Agent System with Google ADK
«`html Understanding the Target Audience for A Coding Guide to Build a Scalable Multi-Agent System with Google ADK The target audience for this tutorial primarily includes software developers, data scientists, and business analysts looking to leverage AI technologies for building scalable systems. These professionals typically work in enterprise settings and are interested in optimizing workflows… →
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Apple Researchers Introduce FastVLM: Achieving State-of-the-Art Resolution-Latency-Accuracy Trade-off in Vision Language Models
Understanding the Target Audience for FastVLM The target audience for the introduction of FastVLM comprises primarily AI researchers, machine learning practitioners, and business leaders interested in the implementation and optimization of Vision Language Models (VLMs) in enterprise applications. This audience typically has a strong technical background and is engaged in fields such as AI development,… →
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Is Vibe Coding Safe for Startups? A Technical Risk Audit Based on Real-World Use Cases
«`html Is Vibe Coding Safe for Startups? A Technical Risk Audit Based on Real-World Use Cases Introduction: Why Startups Are Looking at Vibe Coding Startups are under pressure to build, iterate, and deploy faster than ever. With limited engineering resources, many are exploring AI-driven development environments—collectively referred to as “Vibe Coding”—as a shortcut to launch… →
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MiroMind-M1: Advancing Open-Source Mathematical Reasoning via Context-Aware Multi-Stage Reinforcement Learning
«`html Understanding the Target Audience for MiroMind-M1 The MiroMind-M1 initiative targets a range of professionals involved in mathematics, AI, and machine learning. This includes researchers, data scientists, and AI developers who are seeking robust and transparent tools for mathematical reasoning. Their pain points often include a lack of transparency and reproducibility in proprietary models, as… →
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Rubrics as Rewards (RaR): A Reinforcement Learning Framework for Training Language Models with Structured, Multi-Criteria Evaluation Signals
«`html Rubrics as Rewards (RaR): A Reinforcement Learning Framework for Training Language Models with Structured, Multi-Criteria Evaluation Signals Researchers have proposed the Rubrics as Rewards (RaR) framework, which utilizes checklist-style rubrics to enhance reinforcement learning in training language models (LLMs). This method focuses on guiding multi-criteria tasks, producing prompt-specific rubrics based on structured principles. Each… →
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When Good Cultures Go Bad: Stanford’s Charles O’Reilly
Stanford University’s Charles O’Reilly has spent over 50 years studying organizational behavior. In his research on why companies fail, he’s observed something troubling: The same strong cultures that drive success often become the very thing that kills companies when markets shift. Adaption is key. In a conversation with MIT Sloan’s Donald Sull, O’Reilly breaks down… →
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GTM 156: Revenue Marketing Unpacked: GTM Lessons, AI, and What’s Really Broken in Attribution | John Fernandez
The GTM Podcast is available on any major directory, including: Apple Podcasts Spotify YouTube John Fernandez is SVP at Datasite, with a track record as GTM leader at Glia, ContentWise, and Diligent, having scaled teams through IPOs, acquisitions, and $1.4B in equity events. At Glia, John pioneered revenue marketing’s impact, driving 71% of pipeline and… →
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Impact of point-of-care maternal viral load testing at delivery on vertical HIV transmission risk assessment and neonatal prophylaxis: a cluster randomized trial
CONCLUSIONS: PoC maternal VL testing at delivery significantly increased the proportion of infants identified to be at high risk. Infants at high risk whose mothers received PoC VL at delivery were more often initiated on ePNP. However, the linkage of infants at high risk to appropriate prophylaxis remains suboptimal, warranting consideration of universal ePNP. →
