A chatbot is a software application designed to simulate human conversation. It interacts with users through messaging platforms, websites, or mobile apps, using pre-set scripts or artificial intelligence technologies to understand queries and provide responses. Chatbots are often used for customer service, information retrieval, or as virtual assistants.
In a Nature Machine Intelligence paper, researchers unveiled ChemCrow, an advanced LLM chemistry agent that autonomously tackles complex tasks in organic synthesis and materials design. By integrating GPT-4 with 18 expert tools, ChemCrow excels in chemical reasoning, planning syntheses, and guiding drug discovery, outperforming traditional LLMs and showcasing its potential to transform scientific research.
Researchers advocate for a user-centric evaluation framework for healthcare chatbots, emphasizing trust-building, empathy, and language processing. Their proposed metrics aim to enhance patient care by assessing chatbots' performance comprehensively, addressing challenges and promoting reliability in healthcare AI systems.
In Nature Computational Science, researchers highlight the transformative potential of digital twins for climate action, emphasizing the need for innovative computing solutions to enable effective human interaction.
A groundbreaking study in Scientific Reports delves into the emotional responses of AI chatbots, revealing their capacity to mimic human-like behavior in prosocial and risk-related decision-making. ChatGPT-4 emerges as a frontrunner, showcasing heightened sensitivity to emotional cues compared to its predecessors, marking a significant stride in AI's emotional intelligence journey.
In a groundbreaking study, researchers detailed how ChatGPT-4 chatbots exhibited remarkably human-like behavioral and personality traits in Turing test scenarios and classic behavioral games. Through interactive sessions and comprehensive analyses, the study unveiled ChatGPT-4's tendencies towards altruism, fairness, trust, cooperation, and risk aversion, offering profound insights into the adaptability and responsiveness of AI in diverse scenarios.
This paper outlines ten principles for designing elementary English lessons using AI chatbots, addressing crucial aspects like media selection, motivation, feedback, and collaboration. Through a rigorous methodology involving expert validation and usability evaluation, the study offers practical guidelines to bridge the gap between theoretical insights and effective implementation, paving the way for enhanced language instruction and educational adaptability in diverse contexts.
A study analyzing ChatGPT's responses on ecological restoration reveals biases towards Western academia and forest-centric approaches, neglecting indigenous knowledge and non-forest ecosystems. Urgent measures are proposed to ensure ethical AI practices, including transparency, decolonial formulations, and consideration of gender, race, and ethnicity in knowledge systems. Addressing data access and ownership issues is crucial for promoting inclusivity and transparency in embracing environmental justice perspectives.
This study from Stanford University delves into the use of intelligent social agents (ISAs), such as the chatbot Replika powered by advanced language models, by students dealing with loneliness and suicidal thoughts. The research, combining quantitative and qualitative data, uncovers positive outcomes, including reduced anxiety and increased well-being, shedding light on the potential benefits and challenges of employing ISAs for mental health support among students facing high levels of stress and loneliness.
This study explores the acceptance of chatbots among insurance policyholders. Using the Technology Acceptance Model (TAM), the research emphasizes the crucial role of trust in shaping attitudes and behavioral intentions toward chatbots, providing valuable insights for the insurance industry to enhance customer acceptance and effective implementation of conversational agents.
The article emphasizes the pivotal role of Human Factors and Ergonomics (HFE) in addressing challenges and debates surrounding trust in automation, ethical considerations, user interface design, human-AI collaboration, and the psychological and behavioral aspects of human-robot interaction. Understanding knowledge gaps and ongoing debates is crucial for shaping the future development of HFE in the context of emerging technologies.
The paper addresses concerns about the accuracy of AI-driven chatbots, focusing on large language models (LLMs) like ChatGPT, in providing clinical advice. The researchers propose the Chatbot Assessment Reporting Tool (CHART) as a collaborative effort to establish structured reporting standards, involving a diverse group of stakeholders, from statisticians to patient partners.
Researchers propose viewing large language models (LLMs) in conversational AI through the lens of roleplay and simulation. This metaphorical framework helps avoid anthropomorphic misattributions, enabling nuanced interpretations of LLM behavior and fostering responsible development within ethical constraints.
This article explores the challenges and approaches to imparting human values and ethical decision-making in AI systems, with a focus on large language models like ChatGPT. It discusses techniques such as supervised fine-tuning, auxiliary models, and reinforcement learning from human feedback to imbue AI systems with desired moral stances, emphasizing the need for interdisciplinary perspectives from fields like cognitive science to align AI with human ethics.
MarineGPT, a groundbreaking vision-language model designed specifically for the marine domain, has been developed to identify marine objects from visual inputs and provide comprehensive, scientific, and sensitive responses. This model leverages the Marine-5M dataset and offers improved marine vision and language alignment, contributing to increased public awareness of marine biodiversity while addressing some limitations.
Researchers explored the influence of stingy bots in improving human welfare within experimental sharing networks. They conducted online experiments involving artificial agents with varying allocation behaviors, finding that stingy bots, when strategically placed, could enhance collective welfare by enabling reciprocal exchanges between individuals.
Researchers introduced an interactive robot framework that leverages Large Language Models (LLMs) to excel in long-term task planning, adapting to new goals and tasks during execution. The system seamlessly integrates high-level planning and low-level execution using language, demonstrating robustness and adaptability across tasks.
This article discusses the electricity consumption of artificial intelligence (AI) technologies, focusing on the training and inference phases of AI models. With AI's rapid growth and increasing demand for AI chips, the study examines the potential impact of AI on global data center energy use and the need for a balanced approach to address environmental concerns while harnessing AI's potential.
This study delves into the ongoing debate about whether Generative Artificial Intelligence (GAI) chatbots can rival human creativity. The findings indicate that GAI chatbots can generate original ideas comparable to humans, emphasizing the potential for synergy between humans and AI in the creative process, with chatbots serving as valuable creative assistants.
A study comparing the creativity of AI chatbots and human participants in the Alternate Uses Task (AUT) reveals that chatbots consistently produce creative responses, often surpassing humans. However, the study underscores the unique complexity of human creativity, highlighting that while AI can excel, it still struggles to fully replicate or surpass the best human ideas.
Researchers explore how AI chatbots can improve supply chain sustainability in small and medium manufacturing enterprises (SMEs) in India. The research shows that chatbots enhance supply chain visibility and innovation capability, leading to improved sustainability performance, and offers practical recommendations for SMEs to leverage this technology for sustainable practices.
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