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better policies, test societal interventions, or solve complex social challenges—without relying on stereotypes or outdated assumptions?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
https://www.linkedin.com/posts/antoniovieirasantos_ai-generativeagents-innovation-activity-7329512656027971586-E-Gw

#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better policies, test societal interventions, or solve complex social challenges—without relying on stereotypes or outdated assumptions?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

#shownotes for @gamesatwork_biz #podcast e428 are done, and publication set for tomorrow on https://www.gamesatwork.biz and all your favorite podcast feeds! Topics this week include #AI, #GenerativeAudio, #GenerativeBooks, Jane Friedman’s author experiences, #GenerativeAgents, #NPCs #GenerativeBucketLists from @soka Benji Smith’s #prosecraft and much more! Be sure to subscribe so you don’t miss an episode!
Games At Work dot Biz e545 – Cyberpunk pot holes

A weekly podcast and blog where we focus on metaverse & gaming technology in business, gamification and the business of games.

Games At Work dot Biz | Play games with us!
on the #shownotes #grind for @gamesatwork_biz in preparation for tomorrow's posting of e428 — stories & toots about #AI @soka #GeneratedAudio #GeneratedBooks #GenerativeAgents and a whole lot more! Check out the earlier episodes, chock full of #AI #metaverse #AR #VR #gamification and so much more on https://www.gamesatwork.biz

More in the thread of exploring the aesthetic of early #generativeai via #chatGPT4 and #nijijourney5

Like abstract expressionism moving away from pictorial representation, this series attempts to bring the process of diffusion itself to the surface.

Boost/Follow/Reply 🙏 ✨

#aiart #painting #chatgpt #autogpt #generativeart #generativeagents #ai #ml

I'm still not quite sure how to properly use threads on this site. Maybe I need an actual blog to link to 🤔

So, forgive the bird-site link but I took some time to deep-dive into my process for my #pixelart portrait, and I figured it's worth a share.

If you'd like to help me reach a wider audience, as always, I really appreciate the boosts as I try and establish here!! ✨

https://twitter.com/dreamwieber/status/1646174361542615040?s=20

#aiart #ai #generativeagents

Gregory Wieber on Twitter

“Actually, this pixel art version of me is an interesting case-study in how sometimes it's actually hard to narrow in on what you want with #generative #ai tools like #midjourney. A quick thread on some of the fails, and how I got what I wanted.”

Twitter

Wow, this was fast: 25 Agents simulating human behaviour. Including memory and planning. Worth a read.

#generativeagents

https://arxiv.org/abs/2304.03442

Generative Agents: Interactive Simulacra of Human Behavior

Believable proxies of human behavior can empower interactive applications ranging from immersive environments to rehearsal spaces for interpersonal communication to prototyping tools. In this paper, we introduce generative agents--computational software agents that simulate believable human behavior. Generative agents wake up, cook breakfast, and head to work; artists paint, while authors write; they form opinions, notice each other, and initiate conversations; they remember and reflect on days past as they plan the next day. To enable generative agents, we describe an architecture that extends a large language model to store a complete record of the agent's experiences using natural language, synthesize those memories over time into higher-level reflections, and retrieve them dynamically to plan behavior. We instantiate generative agents to populate an interactive sandbox environment inspired by The Sims, where end users can interact with a small town of twenty five agents using natural language. In an evaluation, these generative agents produce believable individual and emergent social behaviors: for example, starting with only a single user-specified notion that one agent wants to throw a Valentine's Day party, the agents autonomously spread invitations to the party over the next two days, make new acquaintances, ask each other out on dates to the party, and coordinate to show up for the party together at the right time. We demonstrate through ablation that the components of our agent architecture--observation, planning, and reflection--each contribute critically to the believability of agent behavior. By fusing large language models with computational, interactive agents, this work introduces architectural and interaction patterns for enabling believable simulations of human behavior.

arXiv.org

Just me and the dogs talking a walk in the garden to observe, plan, and reflect.

#generativeagents #stanford #ai #farmlife

Generative Agents might be one of the most fascinating papers you'll read on #ai this year.

Or this week, space moves fast.

#ai #stanford #generativeagents #smallville #sims #llm #chatGPT

https://arxiv.org/abs/2304.03442

Generative Agents: Interactive Simulacra of Human Behavior

Believable proxies of human behavior can empower interactive applications ranging from immersive environments to rehearsal spaces for interpersonal communication to prototyping tools. In this paper, we introduce generative agents--computational software agents that simulate believable human behavior. Generative agents wake up, cook breakfast, and head to work; artists paint, while authors write; they form opinions, notice each other, and initiate conversations; they remember and reflect on days past as they plan the next day. To enable generative agents, we describe an architecture that extends a large language model to store a complete record of the agent's experiences using natural language, synthesize those memories over time into higher-level reflections, and retrieve them dynamically to plan behavior. We instantiate generative agents to populate an interactive sandbox environment inspired by The Sims, where end users can interact with a small town of twenty five agents using natural language. In an evaluation, these generative agents produce believable individual and emergent social behaviors: for example, starting with only a single user-specified notion that one agent wants to throw a Valentine's Day party, the agents autonomously spread invitations to the party over the next two days, make new acquaintances, ask each other out on dates to the party, and coordinate to show up for the party together at the right time. We demonstrate through ablation that the components of our agent architecture--observation, planning, and reflection--each contribute critically to the believability of agent behavior. By fusing large language models with computational, interactive agents, this work introduces architectural and interaction patterns for enabling believable simulations of human behavior.

arXiv.org
Smallville: KI-Agenten simulieren in eigener Stadt menschliches Verhalten

Forscher schufen für 25 KI-Agenten die virtuelle Stadt Smallville und beobachten sie nun bei der Gestaltung ihres Alltags.

Tarnkappe.info