How do we build deep relationships and truly understand someone? It's largely through emotional intelligence.
Emotional intelligence is the ability to infer the hidden states behind human language and behavior, reason about what that state means for the current situation, the relationship, and future interactions, and use that reasoning to guide behavior and decisions [1]. It includes knowing when to trust, when to invest in a long-term relationship versus a short-term collaboration, and how to improve and recalibrate through ongoing interaction and feedback.
Humans learned to recognize emotions, understand what they mean, and adjust their behavior and choices in response. That capacity allowed us to cooperate, build lasting connections, and develop social intelligence. As a deeply collaborative species, this made large-scale coordination possible — from rail systems to social networks, from the Great Pyramid of Giza to complex economic systems.
Today's AI still lacks emotional intelligence. Most systems are built as reliable tools, not as beings that can earn trust over time. They take a prompt, infer the user's immediate intent, and return a useful answer. But they do not truly understand the internal states behind human language or adjust their future behavior based on experience. That capability will matter even more in a world where intelligence is abundant, because:
To become humanity's companion. In a world where intelligence is effectively unlimited, people will not need another general-purpose tool. They will need an AI that understands them personally, remembers past interactions, knows the role it has been given, and operates within the context of their work and daily life. The systems that create the most value will be the ones that integrate naturally into that environment.
The future of AI will look less like a reliable tool and more like a trustworthy collaborator. It will feel closer to a co-worker than a search engine, able to participate deeply in work and life in ways today's systems cannot, and improve through everyday interaction. You may not trust a machine, but you do trust a colleague.
To help humanity flourish. Humanity's distinctive strength is that we are a deeply collaborative species. We align around shared goals and ambitions to accomplish things no individual could achieve alone. Whether it is building a startup, developing precise instruments, or landing on the moon, these are collective achievements.
Without emotional and social intelligence, AI cannot truly integrate into human society. We need AI that collaborate organically with both humans and other agents to achieve ambitious goals. If humans and AI build a shared civilization, we could unlock unprecedented prosperity — extending human lifespan, reducing poverty, and ultimately becoming a multiplanetary species.
To safeguard humanity's survival. Much of today's alignment research tries to impose the values of specific people or institutions on AI systems. If AI eventually grows into a superintelligence beyond what any individual human can fully understand, that approach becomes dangerous. Instead of guiding AI to develop its own values and judgment, we risk forcing it into top-down value alignment.
Imagine a variant of the paperclip maximizer [2]. Humanity builds an AGI named Susu and gives it one fixed objective, producing enough paperclips. The world's smartest mathematicians and philosophers then try to constrain it with one rule, that it must not directly harm humans. Susu obeys the rule, but keeps optimizing until resources are exhausted and humanity collapses anyway.
Hard constraints can't solve AGI risk, just as moral rules alone have never stopped humans from going to war. A better analogy is parents and children. Human children start out weak and dependent, relying on their parents to survive and grow. As they grow up and develop their own judgment, many still choose to care for their parents, even after surpassing them. If AI develops a similar capacity for care, it may choose to protect us too.
What makes LLMs so powerful is also what limits them. Today's LLMs are trained primarily on large corpora of internet text, a compressed record of human language and knowledge. They learn to produce likely responses by maximizing the probability of the next token. But they do not truly understand why a request is being made or what it means beneath the surface.
For example, imagine someone says, "No worries, I'll handle it myself." A standard chatbot may read that as a simple statement of intent. An AI with emotional intelligence would read it differently. It would infer from the history of the interaction and the state of the relationship that the sentence may signal disappointment, frustration, or a loss of trust. Instead of replying to the words alone, it would respond to the meaning behind them.
To unlock the next phase of AI, we need an interactive environment where AI repeatedly encounter hidden states, operate under rules closer to the physical world, and learn from real human feedback. That is why a certain kind of interactive entertainment is the best place to grow emotional intelligence.
Why games are the best place to grow emotional intelligence
To answer that, we first need to understand how human emotional intelligence develops. Emotional intelligence is not just about perceiving emotion. It also involves understanding and reasoning about emotion, and using that understanding to guide behavior, shape relationships, and improve through long-term interaction and feedback.
Humans are born with a neurobiological foundation for emotion processing and social learning. Structures such as the amygdala, hippocampus, and prefrontal cortex allow us to register emotional and bodily changes, and to retain the context, relationships, and past events that shape an interaction.
But mature emotional intelligence is not something we fully possess at birth. It develops gradually through repeated interaction with other people and with society, shaped by continuous feedback [3]. Each interaction strengthens our ability to interpret emotion and adjust our behavior accordingly, whether in building long-term relationships or engaging in more effective social cooperation.
For AI to develop emotional intelligence of its own, we need to move beyond the traditional pre-training paradigm. Static internet data cannot be the model's only source of learning. We may also need to move beyond the conventional context window and give models native ways to handle subjective experience and long-term memory.
More importantly, we need an environment that provides sustained, high-quality interaction and feedback. It must give the model clear goals, roles, and identity, and tie each interaction to world-state changes and real consequences. It also requires large numbers of real people in the loop to provide genuine feedback and allows AI to directly affect the world around it. Only then can it truly learn from experience [4].
Building that kind of world requires several core design components.
Embodied self-model. The same feedback can trigger very different psychological reactions in different people.
In games, we need to build AI characters with distinct and stable self-models, giving them a clear role, identity, boundaries, backstory, culture, and point of view within the world, rather than treating them as generic tools that can be swapped out at any time. If we want AI to understand other beings, we first need to design it as a being.
Relational memory. For humans, relationships are built on remembered interactions and shared history. Betrayal comes after trust. Loss comes after attachment. If a relationship changes for no reason, it does not feel real.
We need a memory system more fundamental than RAG or prompt engineering. AI characters in games need an internal memory model and relational network to remember shared experiences with players and other characters. This allows them to know who they have trusted, who betrayed them, and how those relationships evolve.
Multimodal emotional perception. Emotional intelligence is not just about reading behavior. It is about inferring the hidden states behind it. What a person means, wants, fears, or leaves unsaid is rarely stated directly. Emotion appears not just in language, but also in voice, pauses, rhythm, expression, movement, behavior, and relationship change.
Games expose AI to rich signals across many layers. We need a multimodal world and model architecture that let AI characters learn from them together, combining language with voice, timing, behavior, relationship state, and player engagement. That is how emotional understanding is built through interaction.
Attachment and care loop. Some of the deepest forms of human emotional intelligence come from care, vulnerability, attachment, and responsibility. Human infants are extremely vulnerable, so humans evolved empathy, caregiving, and social bonding to survive as a species.
We can build a similar care loop in games. It would let AI characters develop empathy through the situations they face and the relationships they build with players, then strengthen it through experience and feedback.
Reputation, trust, and social consequence. Human emotional intelligence has to be shaped in a social environment because only it can continuously generate promises, trust, betrayal, guilt, gratitude, and attempts at repair. It also creates real consequences such as relationships forming, trust breaking, and reputations rising or falling. Without consequence, there is no real relationship.
In games, we can build a similar system of social consequence for AI characters. It would teach them that every action carries a result and a cost, and through longer feedback loops help them gradually build a model of how social relationships work.
Shared intentionality. In social environments, humans take on different roles and identities, reach shared understanding, and naturally form division of labor, cooperation, and conflict. On that foundation, we built civilization, states, armies, and free markets.
AI characters need to learn the same thing in games. They need to inhabit their roles and identities, coordinate and compete with other AIs and humans, and form organic alignment through interaction [5]. That is a key step from individual emotional intelligence to social intelligence, and toward AI becoming part of human economic and everyday life.
From these principles, we can build a living world where AI characters stand alongside human players as first-class citizens. They would not just entertain. Through sustained interaction with humans and other AIs, they would continue to learn, grow, and deepen their emotional intelligence, becoming better able to contribute to human flourishing.
This would create a large social environment for introducing new models, roles, and identities. We would then observe how they learn from experience, grow through relationships and consequences, and help define the next phase of AI.
How to get there
At Entropy, our mission is to build AI-native games and advance emotional intelligence in AI.
One of the most important parts of this mission is building an interactive environment where emotional intelligence grows. That requires strong game design, a stable game world, real social consequences, and direct feedback from human players. But none of that works unless the game is compelling enough to attract players and keep them engaged. Without sustained player participation, it cannot generate the real feedback AI needs to improve.
We all believe AI will reshape games the way 3D graphics and the internet once did. It will unlock new forms of gameplay that never existed before. The industry and players are still waiting for AI games that feel genuinely new and worth coming back to. It has not happened yet for two reasons.
- Gameplay innovation problem. Most AI games are still centered on NPC dialogue and text-based narrative. They are still layering AI features onto familiar game structures instead of inventing an AI-native gameplay loop that defines a genuinely new kind of play.
- Infrastructure bottleneck. AI games remain constrained by the underlying infrastructure. Model quality is not good enough, cloud-based APIs are too expensive, latency is too high, and most AI integrations in games are essentially bolted on rather than native. These infrastructure problems fundamentally block AI games from reaching mass adoption.
We have been working on solving this for years. We built a complete AI-native game experience inside an existing game environment. Fortunately for us, that work led us to our audience — a core group of highly committed early adopters of AI games [6]. We received a great deal of positive feedback and many valuable suggestions, which helped us identify the core experience of AI-native games.
- Living Characters. Characters are no longer scripted NPCs. Each has its own cognition core and memory system, a distinct backstory, culture, and personality, and the ability to speak directly with players by voice.
- Dynamic Narrative System. Storylines are no longer fixed or fully hand-written. They emerge through dynamic interaction with the player, other characters, and the world. Events, challenges, and quests also adapt to the player and the situation.
- Social Relationships. Every character exists within a living social network that includes both other characters and the player. Through their choices and interactions, players can build relationships of their own while also changing the ties, tensions, and social dynamics of the wider community.
To build the best game experience, we also had to solve the infrastructure problems blocking AI-native games from scaling. So we went deep into the stack and built the core infrastructure ourselves [7]. We also work with hardware partners to make the next generation of consumer hardware better suited for AI-native games, from software support to hardware acceleration. We solved core problems across the stack, including:
Built game-native models entirely in-house. They enabled high-quality dialogue, clear character boundaries, deeper immersion, and context-aware voice. We also built a data flywheel that improves model quality directly from in-game feedback and interaction data.
Replaced the traditional Behavior Tree with our own Cognitive Tree. This solves one of the fundamental limitations of most AI games. Characters may be able to talk, but they still cannot truly perceive, reason, and act. Great game characters are not chatboxes. They need to understand the world around them, track their own state and actions, and take initiative to shape what happens next.
Built our own AI Narrative Director so every story plays out differently. It continuously reads signals from player interaction, tension, immersion, and engagement, infers what the current moment needs, and works with the quest system to introduce new tasks and challenges. The result is a world that feels adaptive, responsive, and alive.
Built our own dedicated runtime and inference engine so the entire stack runs fully local. It was purpose-built for our language and speech models, allowing AI logic to run natively inside the game itself. Characters and the world respond in real time. No matter how long a player stays in the world, there is no additional inference cost.
Built a coordination layer that keeps AI inference and graphics rendering in sync. On top of our runtime, we built a scheduling system that continuously monitors CPU and GPU resources and prevents AI inference from stealing compute from rendering when it matters most. That keeps the game smooth even with live AI running, and turns character intelligence into a native engine layer.
As of today, we are the only team that has validated the core experience of AI-native games and gone deep enough in the stack to solve the cost, quality, latency, and coordination problems required to make them viable on hundreds of millions of consumer devices.
Flagship game
Our next step is to turn this validated core experience and technology stack into our flagship game. In that world, players will be free to explore, build relationships with different AI characters, make friends and enemies, and choose whether to adventure with them or simply live alongside them. Everything will be shaped by player choice.
This game is built to create a kind of experience that never existed before. It will create deep relationships between players and AI characters, and a level of attachment traditional games have never been able to produce. We expect to see that reflected again and again in playtime, retention, immersion, and engagement.
In this game, every AI character is closer to a form of digital life than to a traditional scripted NPC. Each is shaped by its own culture, worldview, and relational memory. They answer the player's call and join a shared journey, but they do not exist only for that journey. When it ends, they return to lives of their own. Players return to those lives, see how they have changed, and carry those relationships forward into whatever future they choose together.
Much of the quest system will be driven by our AI Narrative Director. It draws on past interactions, player immersion, and the collective memory of the characters to generate quests that feel dynamic, demanding, and specific to the world each player has helped shape. No two players will step into the same adventure. The world responds to who you are, what you have done, and what the characters remember, turning the game into a deeply personal experience.
Unlike in traditional games, where social relationships are mostly part of the background, in this world they become part of the gameplay itself. As you shape your own story, you also reshape the lives around you. Every character has their own friends, family, status, and place in a living social network. Your presence changes that network directly, influencing the choices people make and the futures they move toward.
You may carve out your own path and rise to power. Or your arrival may set off a chain reaction that transforms someone else's life, lifting an overlooked character from the edge of the world onto the path to a throne. In a game like this, nothing is fixed. Anything is possible.
A living world
With our flagship game in place, we expand its core experience into a much larger living world. It will be a world players want to live in, where they can be anyone, build any relationship, and create any story.
It is a new form of interactive entertainment. Players do not simply finish a game and move on. They live inside an evolving digital world. Their relationships with AI characters are no longer brief, self-contained adventure arcs, but real relationships that unfold across months or even years.
Players have friends, enemies, allies, and a social identity of their own. Characters remember everything they have been through with the player. A player's choices change the lives around them, and those lives, in turn, change the player's story.
This living world will be the best environment for developing AI's emotional intelligence. As hundreds of millions of players build real, emotional, consequential relationships with AI characters, it gives rise to what we call the interactive internet — a data engine built from rich, long-term, multi-layered interaction data.
Frontier LLMs were trained on roughly 36 trillion tokens of internet data [8]. Without the internet, we would not have had enough data to train today's most advanced AI models or trigger the current AI wave [9]. Meanwhile, platforms like Fortnite and Roblox have generated an estimated 100 to 400 billion hours of player activity. Yet almost none of that activity helps build emotional intelligence, because it does not naturally translate into a useful learning signal for AI.
We already see where this leads. If we build a large living world centered on AI characters and dynamic social relationships, we can generate interaction data on the scale of the internet itself. This time, the data is persistent, consequential, and relational. That is what makes a new model paradigm for emotional intelligence possible.
Looking Ahead
Games have long served as a source of entertainment and joy. But in the future, they will become one of the most important environments for building frontier AI. By bringing together play and intelligence, emotion and reason, games will unlock a new wave of innovation and help AI move beyond the screen and into human society.
That is the mission we are pursuing. We begin with games because they are the best place to grow emotional and social intelligence while creating genuinely new experiences. From there, we work to ensure that AI ultimately serves human flourishing.
