How can generative agents empower urban computing? This paper proposes a computational framework based on continuous cognitive processes.
doi.org/10.59717/j.x...
#generativeagents #LargeLanguageModels #EmbodiedAI

Generative Agents' AI Training Program Featured in Education Journal Generative Agents has been highlighted in an education magazine for its innovative AI Agent training program aimed at addressing the IT skills gap.

Generative Agents' AI Training Program Featured in Education Journal #Japan #AI #Tokyo #LLM #GenerativeAgents

2/12 Meet "Isabella"—the AI therapist that interviewed me.

Friendly female voice, 1990s video game avatar, distinctly mechanical cadence.

For nearly 2 hours she collected my thoughts on life, then fed them to a large language model to create my "digital clone."

#GenerativeAgents

#ai #generativeagents #innovation #behavioralscience #socialimpact… | Antonio Vieira Santos Revolutionizing Behavioral Simulations with Generative Agents. What if we could accurately simulate human attitudes and behaviors to design better policies, test societal interventions, or solve complex social challenges—without relying on stereotypes or outdated assumptions? A recent study, "Generative Agent Simulations of 1,000 People," takes an exciting leap in this direction. It introduces interview-based generative agents powered by advanced large language models (LLMs). These agents are trained on detailed, narrative-rich qualitative interviews, enabling them to reflect the complexity of human behavior in ways traditional models simply cannot. 🔑 Highlights from the Research - Unmatched Accuracy: These agents achieved 85% normalized accuracy on social survey predictions, approaching human-level consistency. - Reduced Bias: By grounding agents in personal stories, the study significantly reduces racial, gender, and political bias compared to demographic-based methods. - Game-Changing Applications: These agents could transform fields like public policy, behavioral research, and AI by enabling simulations that are both realistic and ethical. 🤔 But There’s More to Consider... While this innovation is groundbreaking, it’s also a solution looking for a problem. The study demonstrates the potential of generative agents but raises critical questions: - How do we ensure these models stay relevant in a world where societal attitudes and behaviors constantly shift? - Can this resource-intensive methodology scale to broader populations or global contexts? - And most importantly, how can we translate this impressive research into real-world applications that drive meaningful change? 💡 The Road Ahead To unlock the full potential of this research, we need to: 1️⃣ Identify specific, high-impact challenges (e.g., public health campaigns or policy design) where these agents can shine. 2️⃣ Develop real-world case studies to showcase tangible benefits. 3️⃣ Collaborate across disciplines—policymakers, social scientists, and AI experts—to align this technology with pressing societal needs. What do you think about the potential of generative agents to shape the future of behavioral modeling and decision-making? How can we ensure this technology is ethical, scalable, and impactful? Let’s discuss and explore how innovations like this are changing the game in AI and social sciences. #AI #GenerativeAgents #Innovation #BehavioralScience #SocialImpact #MachineLearning #FutureOfWork #Sociology #AIWithPurpose

What if we could accurately simulate human attitudes and behaviors to design better policies, test societal interventions, or solve complex social challenges—without relying on stereotypes or outdated assumptions?

#AI #GenerativeAgents #Innovation
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