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Unveiling the complexity: predicting long-term CPAP adherence among patients with moderate to severe OSA undergoing ‘Interval’ CPAP Titration study. A prospective randomised study
CONCLUSION: A trial of CPAP before a titration study could improve acceptability, lower the CPAP pressures and improve long-term adherence in patients with moderate to severe OSA. →
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Code2Video: A Code-Centric Paradigm for Educational Video Generation
Code2Video introduces a revolutionary framework for generating professional educational videos directly from executable Python code. Unlike pixel-based diffusion or text-to-video models, Code2Video treats code as the core generative medium, enabling precise visual control, transparency, and interpretability in long-form educational content. Developed by Show Lab (National University of Singapore), the system coordinates three collaborative agents, namely:… →
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SwiReasoning: Entropy-Driven Alternation of Latent and Explicit Chain-of-Thought for Reasoning LLMs
SwiReasoning: Entropy-Driven Alternation of Latent and Explicit Chain-of-Thought for Reasoning LLMs Understanding the Target Audience The target audience for SwiReasoning primarily includes AI researchers, data scientists, and business managers interested in enhancing the efficiency and accuracy of reasoning in large language models (LLMs). Their pain points often revolve around the limitations of current reasoning methods,… →
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Google Introduces Speech-to-Retrieval (S2R) Approach that Maps a Spoken Query Directly to an Embedding and Retrieves Information without First Converting Speech to Text
Google Introduces Speech-to-Retrieval (S2R) Approach Understanding the Target Audience The target audience for Google’s Speech-to-Retrieval (S2R) approach primarily includes: Business Executives: Interested in enhancing customer experience through improved voice search capabilities. AI Researchers: Focused on advancements in natural language processing and machine learning methodologies. Developers: Seeking to integrate voice search functionalities into applications and services.… →
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A Coding Implementation of Secure AI Agent with Self-Auditing Guardrails, PII Redaction, and Safe Tool Access in Python
«`html Understanding the Target Audience The target audience for this tutorial on implementing a secure AI agent with self-auditing guardrails, PII redaction, and safe tool access in Python primarily consists of software developers, data scientists, and AI ethics professionals. These individuals are often engaged in AI development within enterprise environments, focusing on deploying responsible and… →
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5 Most Popular Agentic AI Design Patterns Every AI Engineer Should Know
«`html 5 Most Popular Agentic AI Design Patterns Every AI Engineer Should Know As AI agents evolve beyond simple chatbots, new design patterns have emerged to make them more capable, adaptable, and intelligent. These agentic design patterns define how agents think, act, and collaborate to solve complex problems in real-world settings. Whether it’s reasoning through… →
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Sentient AI Releases ROMA: An Open-Source and AGI Focused Meta-Agent Framework for Building AI Agents with Hierarchical Task Execution
«`html Sentient AI Releases ROMA: An Open-Source and AGI Focused Meta-Agent Framework for Building AI Agents with Hierarchical Task Execution Understanding the Target Audience The target audience for ROMA includes AI developers, data scientists, and business managers interested in building advanced AI systems. Their pain points often revolve around the complexity of managing multi-agent systems,… →
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The Great GTM Rebuild: From Systems of Record to Systems of Execution
Hello and welcome to The GTMnow Newsletter – the media brand of VC firm, GTMfund. Build, scale and invest with the best minds in tech. For decades, technology was the defining edge that set great companies apart. Not anymore. Tech moats have been on the decline and now are almost gone. Today, the real differentiator… →
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A Coding Guide to Master Self-Supervised Learning with Lightly AI for Efficient Data Curation and Active Learning
«`html Understanding Self-Supervised Learning with Lightly AI The evolution of machine learning has led to the incorporation of self-supervised learning techniques, enabling models to learn from data without the need for labeled examples. In this guide, we would explore the process of building a SimCLR model using the Lightly AI framework, focusing on its application… →