E.N.D. ada | OptimAI | $XAGE

We’ve been quietly building something new for the Action Model ecosystem. Most automation tools start by asking you to build the automation. We thought that was a little backwards. With Actionist, you show it how you do something once. The tabs you open. The tools you use. The order you do things. The decisions you make along the way. Then turn that process into something AI can repeat for you. Less tab chaos. Less repetitive clicking. More time for the work that actually needs you. And the best part? The value doesn't just flow back to a billionaire-owned AI company. Actionist is part of the Action Model ecosystem, built with the help of our 500K+ community, with a model designed to give that community a stake in the value they help create. We're getting closer. If you're not following @Actionist_ai yet, now would be a good time 👀

100 WINNERS. $5,000 IN REWARDS. The @NeoSoulAI x ActionFi lottery has officially been drawn. 100 people just won $50 worth of NeoSoul tokens each. That’s another $5,000 in rewards going directly to the Action Model community. Took part? CHECK YOUR EMAIL. Didn't get picked? Keep taking action. The $100k SIXR campaign is only 3 weeks into its 2-month run, and new ActionFi campaigns are coming soon. ⚠️ Winners are ONLY contacted via [email protected]. We will never DM you about winnings or ask for sensitive information. Congrats to all 100 winners. This is just the start.

"The world is right to be afraid of AI.” When the CEO of OpenAI says this, we should probably pay attention. Sam Altman just acknowledged one of the biggest risks of AI: Too much power concentrated in the hands of a few AI companies. Altman warned that AI companies could gain enough power to exert undue influence over the economy and push their worldview onto society. Think about that. Even the people building the world's most powerful AI are warning about what happens when too few companies control too much of it. AI will become one of the most powerful technologies humanity has ever created. So why should its future belong to a handful of corporations and billionaires? At Action Model, we believe there's another path: AI built with the people. AI owned by the people. AI where the people creating the value have the opportunity to share in it. AI is inevitable. Concentrated ownership doesn't have to be. Join our community-owned AI ecosystem and let's build a different future.

Tristan Harris, former Google design ethicist and co-founder of the Center for Humane Technology, has spent years warning about what happens when AI is controlled by a small number of companies. His warning about AI is simple: If AI replaces all of human work, who owns the value it creates? Right now, a handful of Big Tech companies are spending billions to build AI capable of doing more and more of the work humans do. If they succeed, they own the models. They own the automation. They capture the upside. Everyone else gets disrupted. At Action Model, we believe the people whose data, behavior and contributions help train AI should have a stake in the value it creates. That’s why we’re building a community-owned AI ecosystem where contributors can participate in the upside of the technology they help build. AI replacing more human work may be inevitable. A handful of companies owning the entire AI economy isn’t.

No one can create the Matrix. Well, actually… they just did. Harvard and MIT researchers just built an AI simulation containing 8.3 billion virtual people, roughly the entire population of Earth. They call it MatrAIx. It’s a population-scale simulation infrastructure powered by Big Tech models like GPT and Claude. At its core is an insanely detailed dataset called Persona 8B. It contains 8.3 billion digital profiles, with each persona represented across 1,290 categorical dimensions. Background. Psychology. Spending habits. Behavioral traits. Technical literacy. Lifestyle. But they didn’t just build a giant database of statistics. They brought the personas to life. Researchers placed these persona agents into four different digital environments: • Surveys • AI chat interfaces • Live web browsing • Native apps Then they tested how this simulated population reacted to products, software and changes in user experience. The system could capture things like hesitation after a price increase, willingness to continue after an AI assistant failed, and tolerance for latency. And when researchers tested whether the agents actually behaved according to their assigned personas, they reported 91.5% adherence across 400 controlled trials. This sounds incredible for testing. But there’s a massive question hiding underneath it. Humans don't always behave according to their profile. We’re erratic. A rational buyer sometimes makes an irrational purchase. Someone who hates waiting might randomly tolerate a terrible experience. Someone who should abandon a checkout might continue anyway. And sometimes there is no obvious reason why. So if we're going to simulate humanity, we also need to simulate human unpredictability. It isn't enough for an AI persona to behave consistently with its demographics, psychology and historical preferences. There needs to be some probability that it does something completely unexpected. And that's incredibly difficult to model because you don't actually know the probability of a human being erratic in any given situation. That may ultimately become one of the biggest challenges with simulated populations. Because the closer these systems get to modelling billions of people, the more powerful they could become for testing products, pricing and user experiences before releasing them into the real world. Imagine testing a product against millions of simulated customers overnight instead of waiting weeks for traditional market research. But there’s an important distinction: Simulating 8.3 billion personas isn't the same thing as predicting 8.3 billion humans. The final ingredient might be the hardest one to reproduce. Chaos. And interestingly, this is exactly why real human behavioral data becomes increasingly valuable. Simulations can model what humans should do. Real interaction data reveals what humans actually do, including the pauses, mistakes, strange decisions and unexpected paths that models may never think to generate themselves. That distinction is highly relevant to Action Model's approach of learning from real human-computer interactions.

People often ask us: "Why should I join Action Model?" The answer is simple. Action Model is building a community-owned AI ecosystem where people can earn ownership based on the value they help create. Whether that's: • Training the model • Completing ActionFi tasks • Inviting friends • Contributing to the community • Building automations with Actionist Every action helps strengthen the ecosystem. And if AI is going to reshape the world, we want that future to be owned by more than just a handful of billionaires. If you believe this to, then join our movement.

Everyone’s racing to build bigger AI models. Almost no one is asking where the training data comes from or who benefits from it. Scraped. Unlicensed. Collected without meaningful consent. The next battle in AI won’t just be about copyright. It will be about who owns the data, who gets rewarded, and whether the people training AI ever had a choice. That’s why Action Model is building AI differently: Trained by the community. Rewarding contributors. Owned by the people who help build it.

An OpenAI insider just revealed why the AI race is moving so fast. Daniel Kokotajlo, a former OpenAI researcher, says the race isn't just about building better AI. It's about economic power. Whoever builds the leading AI systems could shape the next global economy. He also believes AI has the potential to dramatically improve humanity. But if that power ends up concentrated in the hands of just a few companies, the consequences could be enormous. That's why we built Action Model. A community-owned AI model where the people helping train, grow, and build the ecosystem can earn a fractional stake in the value they help create. AI is inevitable. An AI future owned by only a handful of companies isn't.