Artificial Intelligence (AI) has been making significant advances with an exponentially growing trajectory, incorporating vast amounts of data and building more complex Large Language Models (LLMs). Training these LLMs requires more computational power and resources for memory allocation, power usage, and hardware. Optimizing memory utilization for different types and configurations of GPUs is complex. Deciding… →
Epistaxis greatly affects patients with hereditary hemorrhagic telangiectasia (HHT). Although few systemic treatment exist, nintedanib, is a good candidate thanks to its anti-angiogenic activity. Our main objective was to evaluate the efficacy of oral nintedanib on epistaxis duration in HHT patients with moderate to severe epistaxis. This multicenter phase 2 randomized, placebo-controlled, double-blind trial was… →
CONCLUSION: Long-term supplementation with 5.7 g of the egg-protein hydrolysate NWT-03 for 36 weeks improved vascular endothelial function in older adults with overweight/obesity experiencing elevated SCF, which may benefit cardiovascular disease risk. No overall changes in other vascular function markers, retinal microvascular calibers or cardiometabolic risk markers were observed. →
Graphical User Interfaces (GUIs) play a fundamental role in human-computer interaction, providing the medium through which users accomplish tasks across web, desktop, and mobile platforms. Automation in this field is transformative, potentially drastically improving productivity and enabling seamless task execution without requiring manual intervention. Autonomous agents capable of understanding and interacting with GUIs could revolutionize… →
Multi-agent systems (MAS) are pivotal in artificial intelligence, enabling multiple agents to work collaboratively to solve intricate tasks. These systems are designed to function in dynamic and unpredictable environments, addressing data analysis, process automation, and decision-making tasks. By incorporating advanced frameworks and leveraging large language models (LLMs), MAS has increased efficiency and adaptability for various… →
Current datasets used to train and evaluate AI-based mathematical assistants, particularly LLMs, are limited in scope and design. They often focus on undergraduate-level mathematics and rely on binary rating protocols, making them unsuitable for evaluating complex proof-based reasoning comprehensively. These datasets lack representation of critical aspects of mathematical workflows, such as intermediate steps and problem-solving… →
The business landscape is undergoing a profound transformation, driven by artificial intelligence technologies that are reshaping how companies approach sales and customer relationships. As we navigate through 2024, AI has evolved from a futuristic concept to an indispensable business tool, offering unprecedented capabilities in lead generation, customer engagement, and sales optimization. This technological revolution is… →
CONCLUSIONS AND RELEVANCE: OBC may be more efficacious in helping families to improve health management routines after a child’s diagnosis with T1D than usual endocrinology care alone. Most child health outcomes were in target range at the start of the study; therefore, it was not expected to see significant improvements. Plain-Language Summary: Occupational therapy is… →
The feasibility of conducting a fully remote, interventional, phase II decentralized clinical trial (DCT) was investigated in major depressive disorder (MDD). Key learnings were collated to improve future DCTs. A double-blind, placebo-controlled, parallel-group, DCT enrolled adult MDD patients with inadequate response to first-line antidepressant monotherapy (ongoing ≥8 weeks) and a Montgomery-Åsberg Depression Rating Scale total… →
Large Language Models (LLMs) have demonstrated impressive proficiency in numerous tasks, but their ability to perform multi-step reasoning remains a significant challenge. This limitation becomes particularly evident in complex scenarios such as mathematical problem-solving, embodied agent control, and web navigation. Traditional Reinforcement Learning (RL) methods, like Proximal Policy Optimization (PPO), have been applied to address… →