Tag: human-in-the-loop
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Are AI Agents Ready for the Workplace? A New Benchmark Raises Doubts
Introduction: The Promise vs. The Reality Two years into the AI revolution, the question isn’t whether AI agents exist, but whether they belong in the typical workplace. High-profile predictions—such as those from tech leaders suggesting AI could shoulder much of knowledge work—have raised expectations about faster decision-making, cost savings, and new forms of collaboration. Yet…
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Are AI Agents Ready for the Workplace? A Benchmark Sparks Doubt
Introduction: A Rising Expectation Meets a Harsh Benchmark The AI productivity hype has reached a fever pitch. Since early promises that AI agents could replace knowledge workers, many organizations have watched the tech evolve from clever assistants to more autonomous systems. Yet a fresh benchmark looking at AI agents in practical, workplace-like tasks is casting…
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AgiBot: The AI-Powered Home Robot That Clears Tables and Loads the Dishwasher
Overview: A New Kind of Domestic Robot In households worldwide, robots designed to tidy up and manage chores have long been a promise. A new wave of AI-powered service robots is turning that promise into practice. At the forefront is AgiBot, a Chinese startup pushing the boundaries of practical home robotics. The company is showcasing…
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AgiBot: AI-Powered Home Robot Transforms Domestic Tasks
Reinventing Domestic Labor with AI-powered Robots In homes and light manufacturing alike, a new breed of home robots promises to take on repetitive, messy, and precision-driven tasks. AgiBot, a Chinese startup, is at the forefront of this shift by deploying AI-powered robots that can clear tables and load dishwashers, among other everyday chores. What makes…
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Meet the Chinese Startup Using AI—and a Small Army of Workers—to Train Robots
In the World of Industrial Robotics, a New Model Emerges Across China’s sprawling tech hubs, a discreet blue-collar workforce collaborates with cutting-edge artificial intelligence to teach robots how to perform complex tasks. A rising Chinese startup is redefining industrial automation by combining AI-driven training with a lean, hands-on workforce. The model is simple in concept…
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A Human-LLM Collaborative Annotation Approach for Screening Precision Oncology RCT Articles
Introduction Systematic reviews in precision oncology rely on identifying randomized controlled trials (RCTs) to compare therapies and guide clinical decisions. However, screening thousands of articles to find eligible RCTs is labor-intensive and prone to human error. While supervised learning can accelerate this process, it often demands large labeled datasets and careful tuning, especially for nuanced…
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A human-LLM collaborative annotation approach for screening articles on precision oncology randomized controlled trials
Why a human-LLM collaborative approach matters Systematic reviews in precision oncology require screening thousands of articles to identify randomized controlled trials (RCTs) that illuminate biomarker-driven therapies and targeted interventions. Manual screening, while thorough, is time-consuming and resource-intensive. Large language models (LLMs) can accelerate triage by quickly categorizing relevance and extracting key trial details, but their…