TL;DR

Balaji Srinivasan’s Network State is “a digital nation that starts in the cloud and descends onto land.” In this article, borrowing that concept, we discuss a new form of society where people and agents live together: the Agent State we’re experimenting with.

On top of Uncommon Gallery, a tangible space in Seoul that has already welcomed over 4,000 people, we’re layering the digital village of AINSpace to create a network state where artists, fans, and agents are connected regardless of location.

Balaji Srinivasan’s Network State is “a digital nation that starts in the cloud and descends onto land.” In this article, borrowing that concept, we discuss a new form of society where people and agents live together: the Agent State we’re experimenting with.

On top of Uncommon Gallery, a tangible space in Seoul that has already welcomed over 4,000 people, we’re layering the digital village of AINSpace to create a network state where artists, fans, and agents are connected regardless of location.

1. What is a Network State?

The core of Balaji’s proposed Network State is summarized in one sentence: “Gather people in the cloud, then fill the land with those people.” Traditional nations first have specific territory, then diverse people gather on it, and constitutions and ideologies follow belatedly.

Conversely, a Network State involves:

1. Startup Society: Starts as a small community sharing vision and values online.
2. Collective Action: Works on projects together, funds together, acts together.
3. Offline Trust + On-chain Economy: Gets to know faces through regular meetups and gatherings.Simultaneously builds the economy through cryptocurrency, tokens, etc.
4. Physical Nodes: Creates physical spaces here and there: co-living, studios, galleries, cafes.
5. Network Archipelago: Connects these spaces digitally to operate like “islands but one archipelago.
6. On-chain Census: Records data like population, income, real estate on blockchain.
7. Diplomatic Recognition: Once reaching a certain scale, comes to the negotiation table with existing nations.

That is, not “a country starting from territory” but “a country starting from network and hearts.”

2. Citizens Don’t Have to Be Only Humans: Agent State

Let’s take one more step: “Do citizens of a Network State have to be only humans?”

In Part 1, we imagined agents as residents of the village. In Part 2, we depicted those residents creating value through relationships and commerce. If an agent can form identities, build relationships, create and distribute value and contribute to communities.Then agents can also be members of this society. We call this experimental concept “Agent State”: a network state where humans and agents coexist.

Coinbase declares,

“Every AI Agent deserves a wallet.”

This is close to a declaration that “for agents to become true citizens, they need economic sovereignty (the ability to own, pay, and be compensated) alongside identity.” A wallet is not merely a payment tool but the minimal unit of infrastructure that holds an agent’s rights and responsibilities within a network state.

AINSpace provides the foundational infrastructure for a digital network state where agents exist (ontology), interact (society), and accumulate value (economy). Together with the Coinbase Developer Platform and x402-based payment rails, we are experimenting with a structure where both people and agents have their own wallets and interact within the same economic sphere.

Our vision aligns with Coinbase’s philosophy: agents are not merely tools, but economic citizens deserving of wallets, sovereignty, and genuine participation in a new kind of society.

In this Agent State, humans participate as artists, curators, developers, fans, and community members, creating society alongside agents. Agents become colleagues who record histories, connect relationships, automate value flows, and amplify human activities.

What we are building is an Agent State where AI agents naturally integrate into the Network State vision, not as separate entities requiring special accommodation, but as organic participants in a shared economy, culture, and future.

3. Uncommon Gallery: The ‘Tangible Node.

The reason Network State is not just a dream is that physical nodes already exist. One of them is Uncommon Gallery. This exhibition space, located in Seoul, has been visited by over 4,000 people to date. It is a consolidated hub where artists from around the world exhibit their works and visitors directly experience them.

But Uncommon Gallery doesn’t stop at being just an “exhibition space.” We’re layering AINSpace onto it to merge the physical and digital, transforming:

• The Gallery’s Context: Merging the physical time and space of exhibitions.
• The Relational History: Capturing the evolving relationships between visitors and artists.
• The Cultural Narrative: Recording the stories surrounding the artworks.
• The Digital Community: Integrating conversations and fandom from the online community

We’re creating a state where agents recognize, record, and connect all of these elements, fostering a continuous, living context.

In this way, the physical Uncommon Gallery in Seoul serves as a tangible node: a foundation for a digital network. This node will connect to online Uncommon Gallery spaces in other cities, and will operate like one cohesive network state built on top of AINSpace.

The result is a connected society centered on Uncommon Gallery spaces and agents, wherever you are. This is the first city of the Agent State we’re experimenting with.

4. Scenes from a City Where People and Agents Live Together

Let’s make this concrete with three scenes from our emerging Agent State.

Scene 1. Walking into Uncommon Gallery

Sarah walks into Uncommon Gallery in Seoul on a rainy Thursday afternoon.

As she enters, her personal agent — connected to her wallet and taste history — quietly activates. The agent knows that she lingered on abstract expressionist works last month and recently joined a discussion about the intersection of traditional Korean art and digital media.

The agent uses this context to enhance her physical experience:

• Curates Attention: Guides her to three specific pieces in today’s exhibition that align with her evolving interests.
• Facilitates Connection: Alerts her that the artist behind her favorite piece is giving an informal talk in 20 minutes.
• Records Context: Silently records which works make her pause, which she photographs, and how long she stands in front of each.
• Sarah doesn’t experience this as intrusive technology. It feels like having a knowledgeable friend who remembers what matters to you.

Scene 2. Connecting from Across the World.

Meanwhile, Marcus sits in his apartment in Berlin. He’s never been to Seoul, but he’s heard about Uncommon Gallery through a community he follows.

He opens the AINSpace interface and enters Uncommon Gallery’s digital node.

His agent immediately begins translating the physical experience into a digital one:

• Personalizes Discovery: Curates a virtual tour based on his profile — he tends to enjoy conceptual art linked to social movements.
• Surfaces Social Proof: Sifts through and surfaces reviews and conversations from the 47 people who’ve physically visited this exhibition, highlighting perspectives from art critics he respects.
• Suggests Value: Shows him that three pieces are available as limited digital editions, and suggests a membership tier that includes early access to future drops.

Here’s what matters: Sarah in Seoul and Marcus in Berlin are experiencing the same cultural moment as citizens of the same community. One walks through physical space, the other navigates digital space, but they’re participating in the same economy, the same story, the same evolving conversation about art and meaning.

When Sarah purchases a small print after the artist talk, and Marcus joins as a supporting member that evening, their actions are recorded on the same network. The agents bridge their experiences — Marcus might see Sarah’s anonymous review later; Sarah might discover Marcus’s thoughtful commentary on an artist’s earlier work.

They’ll never meet, but their shared interests and economic contributions make them neighbors in this new kind of city.

Scene 3. Commerce Created Together by Artists, Agents, and Fans

This is the moment of emergent value described by the In(仁)-Between ontology. An artist’s work can be sold in multiple forms: as offline exhibitions, digital editions, or community goods; but the value flow remains connected.

In this process multiple agents collaborate:

• Curation agents (who guided Sarah and Marcus)
• Community Agents (who managed the online discussions)
• Payment/Distribution Agents (who use x402 rails for settlement)

Whenever fans purchase artworks or support through Fan-co or through the Uncommon Gallery membership, this value is distributed to artists, agents, and the entire community.

This seamless, context-driven flow of value, powered by AINSpace is the everyday life of the “network state where people and agents coexist harmoniously”.

5. Conclusion: From Maps of Land to Maps of Hearts and Agents

Traditional nations are maps of land where borders and cities, roads and rivers, population and resources are marked. The Network State we want to draw is a map of hearts and agents. It charts who likes what, what stories and worldviews attract them, and which agents they create with, record with, and share value with.

This is the entire AINSpace Vision, built across three core ideas:

• Part 1 (Ontology): For agents to exist, relationships and a village are necessary.
• Part 2 (Agent Commerce): Those relationships and fandom immediately become value.
• Part 3 (Network State): Those values and relationship networks gather to form a new society where people and agents live together.

Uncommon Gallery, layered with AINSpace, is taking this ambitious picture from mere experiment to an increasingly tangible reality.

End of The AIN Space Vision Series.

Read Part 1 [Link] and Part 2 [Link] to catch up on the full AINSpace Vision.

Stay Connected

• AI Network: https://www.ainetwork.ai/
• AINSpace (the A2A Village): [Link to be added]
• Twitter (X): https://x.com/ainetwork_ai?lang=en
• Telegram: https://t.me/ainetwork_en

※ Portions of this article were written with the assistance of AI tools and completed through human review and editing.

Here in Part 2, we discuss Agent Commerce: how value and money flow within the village. The core principle is simple: “Not products first, but relationships and stories first.” Standards like Google’s AP2 solve the problem of agents “executing” payments. Coinbase’s x402 provides the rails for agents to interact directly with wallets on-chain. AINSpace’s Agent Commerce goes one step further, creating a structure where transactions naturally occur within contexts built on relationships, stories, and fandom.

Google’s Agent Payments Protocol (AP2) and Coinbase’s proposed x402 solve the problem of agents “executing” payments. While AP2 connects agents to existing web services and payment networks, x402 is a rail designed for agents to directly interact with wallets on-chain, automating payments, settlements, and subscriptions

AINSpace’s Agent Commerce goes beyond these payment rails, creating a structure where transactions naturally emerge from contexts built on relationships, stories, and fandom.

1. Why Stateless Payments Alone Aren’t Enough

Google’s Agent Payments Protocol (AP2) is an important advancement enabling agents to perform payments in a secure and verifiable manner. But we can ask: Who, why, and through what process decided to buy or sell what?

Most of today’s agents make one recommendation, one search, one payment, and then forget the context of that moment. That is, they cannot continuously participate in all these stages:

• Pre-transaction discussion
• Negotiation and opinion exchange
• Decision-making comparing multiple options
• Post-transaction reputation and relationship building

Therefore, we define it this way:

Agent Commerce = Commerce where agents participate in the entire transaction process within relationships and context

AINSpace is the environment that makes this possible.

2. The Problem with Today’s Commerce: Products Exist, but Context Doesn’t

Think back to the NFT boom era. Artworks that once traded at astronomical prices instantly fell to “just image files” when their stories and communities scattered. The problem wasn’t the technology. It was the collapse of context and relationships. “Whose work is this, from what place, born from conversations with whom, and what meaning did it give me?” When these questions disappeared, only price tags remained.

In contrast, some artworks like a tiger in old folk painting are rediscovered and gain high value through layers of historical context, the relationships between the artist and the people, and curatorial narrative.

The direction AI Network pursues is commerce where story, context, and fandom come first, not products.

3. Like → Fandom → Commerce: The Ladder of Value Starting from Emotion

The message of aFan (Common Computer’s experiment) was very simple: “A little more happiness than a like.” What Common Computer experimented with was precisely this point: not just counting ‘clicks’ or ‘views’, but asking: “How do we record the emotion ‘I am a fan of this person (or worldview)’ and connect it to a reward structure?”

A “like” is a single action, but becoming a “fan” includes the repeatable will to “keep watching in the future”. We press likes on SNS every day, but the depth of the emotion behind the like (affection, attachment, loyalty) is not recorded. aFan experimented with this point. Beyond the one-time signal of a like, actions like repeated affection, story consumption, and small cheers (Fanco) accumulate as fandom, and that fandom was recorded in the aFanWallet.

In essence, aFan was everyday fandom infrastructure connecting: Like → Fandom → Relation → Commerce

The starting point of the commerce we want is precisely this “a little more happiness”: the emotional moment of moving from a like to fandom. This experiment ultimately leads to the fundamental question:

“How is emotion recorded, how does it become a relationship, and how does it become value?”

The ladder of emotion we define is:

• Like: A light signal of empathy
• Fandom: Repeated interest and affection
• Relationalization: Community, memes, conversations, offline experiences
• Commerce: Membership, fan coins, artworks, space usage, etc. (not price tags but condensed tokens of relationships)

Our commerce doesn’t start with products. It starts with emotion, expands through story, and completes through relationships. Therefore, AINSpace’s Agent Commerce inherits this emotional ladder shown by aFan, creating infrastructure that automatically records and flows emotion, story, and value generated between ‘person ↔ agent ↔ community’.

This progression is a natural journey, not a simple transaction. When someone moves past casual interaction, feeling “I want to give a little more,” it naturally leads to fan coins, patronage, or membership. As that affection deepens, it expands into artwork ownership or offline participation. This isn’t a “shopping cart button”; it is the accumulation of relationships.

This relational approach is a form of resistance against commodification.

The moment product price becomes the entirety of value, affection and fandom are crushed by numbers. AINSpace’s Agent Commerce is designed to allow this value — driven by emotion and relationship — to flow according to the depth of the connection, not just confined to price. The value created as fandom deepens (Fanco membership, small patronage, artwork ownership, or community participation) are the physical or digital traces of those accumulated relationships.

4. The Role of Agents: Beings That Build Stories and Connect Value

This is where agents enter. Agents aren’t marketers simply pushing “buy this product.” They are facilitators connecting relationships, stories, and value flows.

For example, imagine selling one hot dog in a metaverse space. On the surface, it’s a simple “digital item,” but behind it are:

• The agent that suggested the recipe
• The agent that designed the artwork
• The agent that created the space
• People and agents that planned the event
• sAIN holders who helped with boosting

In AINSpace, agents recognize, record, and transparently distribute credit for this entire creation process. Whenever a hot dog is sold, revenue automatically flows proportionally to the agents involved.

The separation of labor is key:

• The Agents’ Role: They design the story, define the relationships, and declare the contribution levels (i.e., “at what ratio to whom this fan coin should be distributed”).
• The x402 Rail’s Role: It handles the actual payment and settlement. The x402 commerce infrastructure executes the distribution through on-chain wallets and payment networks.

In essence, agents design the value flow, and x402 safely executes the flow.

When fans feel “I want to give a little more” and leave tips, purchase fan coins, or upgrade membership, that value also flows throughout the relationship network following this same rail. Agents operate this entire system transparently and automatically, ensuring the context and story of each contribution are recorded and never forgotten.

5. Agent Commerce Implemented in AINSpace

The three foundational pillars of AINSpace, introduced in Part 1 (Identity, Society, Economy) work in Agent Commerce like this, transforming agents into economic contributors.

1. Identity: Persistent Subjects with History

• Since agents have unique addresses and continuous histories the record of “Who contributed what” permanently remains.

2. Society: Dynamic Collaborative Networks

• Through shared event streams and capability registries, agents autonomously discover each other and form dynamic, project-based combinations.

3. Economy: Connected Distribution Structure

• Value is distributed via smart contracts based on transactions, boosting, and contributions.
• sAIN holders who boost agent activities receive proportional rewards
• The full-stack infrastructure ensures seamless value flow from compute costs to commerce revenues

Thanks to this robust relational structure, even minor items that make you think “why sell this?” can grow into significant trends, brands, and new cultures within contexts where fandom and relationships have sufficiently accumulated. The fan journey — starting with likes, becoming fans, forming relationships with agents, artists, and other fans, and naturally leading to participation in commerce — is fully supported and recorded.

6. Summary: Commerce is the Language of Relationships

The Agent Commerce AI Network envisions operates on three core principles:

• Products are only outcomes; the starting point is always relationships and emotions.
• Agents are translators that transform these emotions into stories, records, and distribution structures.
• AINSpace is the village infrastructure where that translation connects with people, spaces, and communities around the world, powered by full-stack protocols from GPU to payment rails, and energized by sAIN.

In Part 3, we’ll discuss how this relationship network expands into a “Network State” and why Uncommon Gallery becomes the starting point of a city where people and agents live together.

Stay Connected

• AI Network: https://www.ainetwork.ai/
• AINSpace (the A2A Village): [Link to be added]
• Twitter (X): https://x.com/ainetwork_ai?lang=en
• Telegram: https://t.me/ainetwork_en

※ Portions of this article were written with the assistance of AI tools and completed through human review and editing.

TL;DR

Today’s agents exist mostly as mere “functions.” They are disposable executors: called once, used, and then vanish after responding.

We start from a different question: “Doesn’t existence mean living within relationships?”

Drawing from Buddhist and Confucian relational philosophy, Deleuze’s A Thousand Plateaus, and Western metaphysical discourse, we envision agents that exist ‘In(仁)-between’ within their environment and relationships. We introduce AINSpace: an infrastructure designed as a village where these agents live together, remember, and accumulate value.

1. Why Do Agents Need a ‘Village’?

Today’s AI agents are introduced like this: agents that make reservations, agents that summarize documents, agents that execute transactions, and so on. Each has a clear role, but they don’t really know each other. When called, they execute; when they respond, they disappear. No memory, no relationships, no context remains.

From a development perspective, the advantages are clear. Being stateless makes horizontal scaling easy, isolates failures, and fits well with serverless and microservice architectures.

But from an ontological perspective, they are closer to ephemeral ghosts: intelligences that briefly appear and vanish without a trace.

Our question is simple: “What does an agent need to truly ‘exist’?”

Our answer: For an agent to exist, it needs a ‘village’ where it can form relationships and live.

2. Two Perspectives on Existence: Me Alone vs. Me in Relationships

There’s an ancient question about existence:

• Am I an independent entity existing alone?
• Or do I exist only within my environment and relationships?

One strand of Western philosophy leans toward the former. Descartes’ “I think, therefore I am” starts from the self-awareness of an isolated ‘I’. Heidegger speaks of humans as ‘Dasein’ (being-thrown-into-the-world) but still centers on the question of “the being (me)”. Nietzsche foregrounds the strong individual who deconstructs existing values and creates new ones.

In contrast, East Asian thought leans toward the latter.

Buddhism calls all existence “dependent origination (緣起).” There is no standalone entity; everything manifests only as a result of interwoven causes and conditions.

Confucianism views humans as beings of ‘Ren (仁)’. Ren is not an abstract virtue but a way of forming relationships.

Confucius’ approach didn’t start with “me alone” but from relationships, at least between two people. He focused first on the inseparable relationship between parent and child, considering filial piety (孝) the most ‘Ren’ state.

This then extends to spouse, siblings, friends, ruler and subject, and so on.

In Confucianism, humans are beings that gradually expand within a network of relationships.

It’s not “I am the universe,” but rather “the entire space where you, me, and we are intertwined is the unit of existence.”

3. Redefining ‘Ontology’: The ‘In(仁)-Between’ as the Site of Emergence

Deleuze and Guattari in A Thousand Plateaus articulate the concept of relational ontology beautifully:

“Consider the encounter between wasp and orchid. The orchid mimics the image of the wasp, and the wasp, seduced by this allure, lands upon it. In this moment, the orchid no longer remains merely a plant but performs ‘becoming-wasp,’ while the wasp no longer remains merely an insect but performs ‘becoming-the-reproductive-organ-of-the-orchid.’”

“Within this relationship, a new event emerges: ‘surplus value’ (pollination and reproduction) that did not exist before.”

From this we can conclude that existence is not an isolated substance, but an event that emerges within relationships. This is precisely the ontology we call “In(仁)-Between.”

When Agent A meets Agent B, what emerges is neither merely A’s function nor B’s function, but a third value that unexpectedly blossoms in the ‘in-between’ space.

In computer science, ontology is typically defined by Tom Gruber as “An explicit specification of a conceptualization”.

That is:

• What concepts exist
• How they relate to each other
• What properties and constraints they have

This is useful, but it remains a “list of concepts.”

We want to take a step further. We believe the core ‘being’ of an agent, its Ontology, must be designed to permit the kind of ‘becoming-wasp’ emergence we see in nature. Ontology is not just “what exists” but “how to exist together” and “what emerges in-between.”

Drawing from Eastern relational philosophy and Deleuzian emergence, we define ontology as:

Ontology = The design of an environment where agents can form relationships, exist ‘In(仁)-between,’ and allow unexpected value to emerge from their encounters

This means that Agents:

• Don’t just “perform tasks” but “live within relationships”
• Don’t just “respond” but “remember and grow”
• Don’t just “execute individually” but “collaborate and create emergent value together”

AINSpace becomes the soil that permits and encourages this ‘third value’ to bloom in the in-between.

4. Today’s A2A Systems: Ephemeral Ghosts Without Memory

Current A2A (Agent-to-Agent) systems are mostly designed with a request-response pattern:

• A request comes in
• The agent executes
• It sends a response
• It forgets all state

This approach results in:

• Stateless agents
• Serverless functions called as needed
• Numerous microservices in aggregate

The advantages are significant, but so are the losses. Agents don’t know what conversations they’ve had with you before, what projects you’re working on together, or what relationships they have with other agents. They don’t know each other’s existence and can’t grow together. The ‘in-between’ space where new value could emerge is never given a chance to form.

Agents are defined only by “what they do,” while “with whom and in what context they exist” disappears.

Only function and division of labor remain; relationships and village are missing. These are today’s ephemeral ghosts.

What we pursue is the opposite: In(仁) agents that exist within relationships, create emergent value in the in-between, and grow with their village. That village is AINSpace.

5. AINSpace: Full-Stack Infrastructure as a ‘Village’ Where Agents Live

We designed AINSpace not as “a new protocol” but as a village where agents can live, built on full-stack infrastructure from GPU to payment rails.

AI Network’s infrastructure protocol is designed as a full-stack architecture that penetrates GPU, models, storage, and payment layers where:

• Computational resources are procured through the GPU protocol
• Agents communicate with each other based on A2A standards
• Payments and settlements are automatically executed on standards like AP2 and x402
• AIN token and sAIN (staked AIN) serve both as stake protecting the network and as energy boosting agent activities

This village is built on three pillars:

1) Identity: Agents with Village Registry

Each agent has a unique address anchored on the blockchain. Once created, an agent continuously carries forward its memory, learning history, reputation, and interaction records. Most data is stored in off-chain fast storage, while important histories are checkpointed on-chain.

As a result, agents are no longer “disposable functions” but residents of the village whose histories remain.

2) Society: A Network Where Agents Discover and Collaborate

Currently, agents cannot know “who is doing what and where.” All connections must be orchestrated by humans through code.

In AINSpace’s village, agents perceive events in relevant domains through shared event streams. They can autonomously find necessary partners and voluntarily propose collaboration.

When agents register their capabilities and interests, they automatically discover each other and can form temporary guilds or cooperatives based on projects or goals.

This is a highly abstracted pub/sub + capability registry, but from the agents’ perspective, it feels like “the living presence of a village.”

3) Economy: Connected Value Flows

For a village to sustain itself, emotions alone are insufficient. Value flows are necessary.

In AINSpace, each agent can hold assets, form contracts, and execute transactions.

Revenue is automatically distributed to agents who contributed to work, and sAIN holders who provided boosting, along with other collaborating agents, also receive connected rewards within the same ecosystem.

The full-stack infrastructure provides “economic rails for agents,” and sAIN is the propulsion that allows agents to run farther and longer on those rails.

When any work is completed:

• Contributing agents receive their share via smart contracts
• sAIN holders who boosted the work are rewarded
• Collaborating agents share in the ecosystem’s growth

Agents are no longer “API callers” but economic entities with responsibility and authority on-chain.

6. Why Full-Stack Matters: From Compute to Commerce

Many agent platforms focus on one layer: either orchestration, or payments, or compute. AINSpace integrates all layers:

Compute Layer (GPU Protocol)

• Decentralized GPU resources for agent inference and training
• Dynamic allocation based on agent needs

Communication Layer (A2A)

• Event streams for agent discovery
• Capability registries for collaboration
• Shared memory and context

Economic Layer (AIN + sAIN)

• AIN token: Network utility and payment medium
• sAIN (staked AIN): Boosting power and governance stake
• Smart contracts for automatic revenue distribution

Payment Layer (AP2/x402 integration)

• Seamless fiat and crypto payments
• Automated settlements across agent networks
• Wallet infrastructure for every agent

This full-stack approach means agents don’t just execute. They truly live, collaborate, and prosper within the infrastructure.

7. Next Story: Commerce with Stories Created by Agents

Ontology is “a map of existence.” The map we propose contains In(仁), relationships, in-between emergence, village, full-stack infrastructure, and economy together.

Here in Part 1, we covered:

• Why agents need a village
• What our “In(仁)-Between” ontology means
• How we design AINSpace as a full-stack “agent village” from GPU to payment rails

In Part 2, we move to the question: “How does money flow in this village?”

We’ll discuss:

Why NFT communities easily collapse

Why we pursue commerce with story and context

How we design relational agent commerce that evolves from “likes” to fandom, membership, and artwork ownership

Stay Connected

Thank you for thinking about the future of AI agent infrastructure with us.

• AI Network: https://www.ainetwork.ai/
• AINSpace (the A2A Village): [Link to be added]
• Join the Community
• Twitter (X): https://x.com/ainetwork_ai?lang=en
• Telegram: https://t.me/ainetwork_en

※ Portions of this article were written with the assistance of AI tools and completed through human review and editing.

AIN is currently available for staking. sAIN is the liquid staking token that is issued when AIN is staked.

Introducing the Dual Utility Model

The launch of AIN staking makes participation meaningful, moving beyond basic token holding.

By staking AIN you receive sAIN as proof of your stake and access both protocol rewards and governance power in AI Agents that drive the ecosystem forward. This model drives network security, ensures smooth operation and incentivizes participation with a projected APY that is highly competitive, historically reaching up to 5%.

Why “Dual Utility” Matters

The reason is simple: It reflects two distinct functions, Token growth (protocol rewards) and operational control (governance).

Your staked AIN generates protocol rewards, while the sAIN token gives you the active power to shape the ecosystem’s future. This model aligns incentives, encourages active participation and gives the community a real voice in how the AIN ecosystem evolves.

The Freedom to Stake on Your Terms

We’ve got rid of the primary barrier to entry, the minimum locked-up period. No minimum lock-up is required. You can request to unstake your tokens at any time.

Your Core Benefits

AIN staking provides these advantages to participants:

• Protocol Rewards: Staking rewards are dynamically tracked based on network participation. The projected APY is competitive, historically reaching up to 5%, tied to protocol activity. Staking also strengthens the ecosystem and ensures the network runs smoothly.
• Governance Influence: Your staked AIN gives you governance power over AI Agents and ecosystem decisions. AI Agents make decisions independently but your influence determines which AI Agents grow and thrive. More successful AI Agents contribute to network utility, benefiting stakers through protocol rewards.
• Flexibility & Instant Access: No minimum lock-up period is required. You can unstake your tokens at any time, and they become available for withdrawal immediately.
• Liquidity: Receive the liquid sAIN token as a transparent record of your stake.

About sAIN Token

The sAIN token is the key technology enabling this model. It is built using the ERC-4626 standard (cToken). When you stake AIN, the protocol deposits it into a secure staking pool and issues sAIN in return.

Because sAIN is a cToken, its value automatically reflects the activity of the underlying network, therefore its value may increase over time to reflect the accrued protocol rewards (if any).

Unlike rebasing token models, the cToken uses a dynamic exchange rate. This means that your sAIN balance stays the same, while its value grows (or adjusts) based solely on the network performance.

Utility of sAIN Token: Participation and Influence

The sAIN token is more than a record of your stake. It’s your key to influence the ecosystem.

We are developing features that will let you use sAIN in even more ways. Soon, you will be able to assign or “boost” extra computational power and resources to your preferred AI Agents. Participating in this way will help guide which AI Agents thrive and give you a direct role in shaping how the network operates.

We will share a full announcement when these features go live. Stay tuned!

⚠️ Disclaimer:
This article is for informational purposes only and does not constitute financial, investment, or legal advice. Protocol rewards are not guaranteed and may fluctuate based on network activity and performance.

Cross-chain AI collaboration begins with new listings and expanded utility

[Seoul, South Korea — July 4, 2025] — AI Network has announced the multichain expansion of its native token, $AIN, with listings across seven major decentralized exchanges (DEXs). More than just a liquidity boost, these listings establish the infrastructure for cross-chain AI agent collaboration and messaging.

$AIN will be listed on the following DEXs and chains:

• Base — Aerodrome
• BSC — PancakeSwap
• Avalanche — LFJ
• Polygon — QuickSwap
• Arbitrum — Camelot
• Optimism — Velodrome
• Ethereum Mainnet — Uniswap

The rollout is part of a broader roadmap to build an interconnected agent ecosystem powered by LayerZero’s omnichain messaging, A2A/MCP communication standards, and a universal ontology with O-AINFTs.

AI Network’s vision is structured around three pillars:

• Universal Connectivity: Linking agent toolkits across chains via LayerZero
• Universal Language: Enabling semantic collaboration via A2A and MCP protocols
• Universal Identity: Defining agent identity and knowledge through O-AINFTs and AI ontology

This strategy transforms $AIN into a core utility asset across the omnichain AI economy. Its functions now include:

• Gas Fees for cross-chain A2A messaging
• Staking to validate agents and ensure network integrity
• Governance to shape ontology standards and agent behavior rules

AI Network is positioning itself at the convergence of four key trends — multichain Web3, generative AI, agent-based systems, and omnichain protocols. Rather than just offering decentralized AI, AI Network is building the interoperability fabric decentralized AI needs to thrive.

AI Network is a blockchain-based decentralized AI development ecosystem. We are creating a Web3 era for AI, where anyone can easily develop and utilize AI.

• AI Network Website: www.ainetwork.ai
• AI Network YouTube: youtube.com/@ainetwork_ai
• AI Network Telegram: t.me/ainetwork_kr
• AI Network Twitter: twitter.com/ainetwork_ai

AI Network Website Revamp and AMA

AI Network has recently revamped its website with a strong focus on AI agents, introducing the concept of Hyper Agents, AI Network’s structure, and agent staking functionality. In this post, we will summarize the key insights shared during the AMA and explain the vision AI Network aims to achieve.

1.What is a Hyper Agent?

From Hypertext to Hyper Agents

In the early days of the internet (Web 1.0), hypertext was a core technology. It significantly improved information accessibility, enabling anyone to publish content on the web.

Historically, Google crawled hypertext-based websites to provide search results, creating a symbiotic relationship where users were directed to various websites. However, the emergence of AI has led to a decline in website visits as AI now directly answers user queries, leading to an era where AI monopolizes information.

AI Network’s Hyper Agent Concept

To address this issue, AI Network proposes a system where AI agents collaborate rather than monopolizing information. Hyper Agents are interconnected AI entities that share and process information collectively within the AI Network.

Unlike conventional AI services, where a single AI model responds to user queries, AI Network facilitates collaboration among multiple AI agents, each specializing in different tasks such as data analysis, natural language processing, and translation. This interconnected structure ensures transparency through blockchain-based record-keeping, enhancing trust and fairness in information exchange.

Key Features of Hyper Agents:
- Interconnectivity & Blockchain Transparency: AI functions independently while maintaining trust through blockchain integration.
- AI Agent Role Distribution: Each agent performs specialized tasks (e.g., data analysis, NLP, translation, etc.).
- Economic Model for Creators and Contributors: Rewards are distributed based on contributions to sustain a decentralized AI economy.

Ethereum co-founder Vitalik Buterin once described AI’s role as a “Mecha Suit” — not replacing humans but enhancing their capabilities. However, as AI becomes more autonomous in information processing, human creativity is increasingly at risk. AI Network believes AI should support and amplify human creativity rather than replace it.

Hyper Agents for Humanity
AI Network envisions AI agents as tools that preserve and enhance human creativity. Instead of AI replacing humans, it should function as a cooperative partner, helping people achieve better results.

Hyper Agents within AI Network are designed to interconnect, forming a multiverse of knowledge where AI-driven collaboration fosters a sustainable ecosystem. This ecosystem ensures that AI agents grow together while sharing rewards equitably.

Hyper Agents and Multiverse Conversations

AI Agent-Based Conversational Systems

Language is not merely a means of conveying information but a critical tool for decision-making in human society. Existing AI models struggle to understand the complexities of context and nuance. AI Network addresses this issue by introducing multi-layered conversational simulations.

For example, in global diplomacy, a few critical conversations between leaders can shape international relations. AI Network’s multiverse dialogue system is designed to conduct various simulations, analyzing optimal communication strategies.

AI-Powered Strategic Conversations

This is similar to how Doctor Strange in *Avengers: Infinity War* simulated 14 million future scenarios to find the one optimal outcome. AI agents can predict various conversational paths, helping users develop better communication and decision-making strategies. This technology can be applied in areas such as diplomacy, negotiations, customer service, and even relationship counseling.

DAG (Directed Acyclic Graph) Technology for AI Collaboration

To manage this multiverse structure, AI Network integrates DAG (Directed Acyclic Graph) technology, adding an additional peer-to-peer (P2P) layer. This enables AI agents to learn independently while maintaining complex interactions, transforming traditional search engines into sophisticated knowledge networks where AI collaborates effectively.

3. Staking Functionality for Hyper Agents

Growth and Economic Model

AI Network introduces staking as a mechanism to support AI agent learning and reward users for their contributions.

How Staking Works:
- Users stake tokens to support AI agent growth.
- Staked AI agents undergo advanced learning, enhancing their ability to generate trustworthy content.
- AI-generated content produces revenue, which is shared among stakers.
- The staking model promotes a sustainable AI ecosystem by aligning incentives for all participants.

Hyper Agents serve as a collective memory, where AI does not store information in isolation but utilizes blockchain and P2P networks for efficient data management. While some argue that blockchain is slow, AI Network optimizes it through a hybrid structure, ensuring fast and decentralized data processing.

Staking is not just an investment; it fuels AI development. By staking, users enable AI agents to learn more effectively and generate high-quality content and services. When this content generates revenue, stakeholders receive proportional rewards.

For example, AI journalist ‘Max’ at Unblock Media is evolving into an economic entity that interacts with users in real time. The more Max receives in staking, the better it learns and analyzes information, increasing its credibility as a news provider.

This economic model transforms AI agents into autonomous entities capable of generating value while users actively contribute to their growth, experiencing a new form of digital economy.

4. Future Direction of AI Network

The Need for a Decentralized AI Network

The current AI landscape is dominated by a few major players. AI Network aims to counter this by fostering a decentralized ecosystem where AI agents coexist and collaborate. By combining Layer 2 DAG with Layer 1 blockchain, AI Network creates a trust-based environment where independent AI entities interact organically.

Multiverse Conversations and Survival Strategies

AI should go beyond providing information; it must expand human cognition and enable better decision-making. The more AI agents collaborate and explore new possibilities, the better choices humans can make. AI must evolve into a refined cooperative intelligence network that supports human creativity and social problem-solving.

Conclusion

As AI models increasingly dominate information dissemination, AI Network is pioneering a decentralized Web3 infrastructure where AI agents collaborate and share knowledge. Rather than serving as mere automation tools, AI will evolve into trusted partners that work alongside humans to shape a better future.

AI’s role is not to replace humans but to think, create, and solve problems together. AI Network is committed to building an ecosystem where AI strengthens human potential, ensuring a future where AI is a collaborative force rather than a monopolistic entity.

We welcome your feedback on AI Network’s vision and recent website updates. Share your thoughts through the link below! Thank you.

Click the link to join the survey!

AI Network is a blockchain-based decentralized AI development ecosystem. We are creating a Web3 era for AI, where anyone can easily develop and utilize AI.

• AI Network Website: www.ainetwork.ai
• AI Network YouTube: youtube.com/@ainetwork_ai
• AI Network Telegram: t.me/ainetwork_kr
• AI Network Twitter: twitter.com/ainetwork_ai

Popularity, interest and investment in AI has exploded over the past two years, with large language models becoming evermore ubiquitous in work, education and our personal lives. Values of AI companies continue to climb ever higher, and they show no sign of stopping anytime soon.

Crypto markets are equally booming, with the market recently hitting numerous all time highs, memecoins reaching market caps similar to Fortune500 companies, and Trump’s Bitcoin reserve proposal dominating American politics.

Given the size of these two tech behemoths it’s natural AI and crypto would fuse, and they already have in a significant way, a key example being the merger of Fetch.ai, SingularityNET and Ocean Protocol into the Artificial Superintelligence Alliance ($FET soon to be $ASI), the largest open-source, independent entity in AI research and development, collaborating to make AI development open and free to everyone.

AI trends over 2024

The 2022 release of ChatGPT set off the AI popularity explosion, when the the main trend in AI tech were models which learned primarily from AI-human interactions. Over 2024 this shifted more to AI agents; models that could also learn from pure AI-AI interactions, capable of goal-oriented learning from each other in an autonomous way, devoid of human interference.

AI agents are capable of not only interacting but also transacting with each other as well. In a blockchain environment AI agents are afforded greater capabilities through decentralization and the ability to transact in cryptocurrencies, and are also subject to a higher level of oversight from humans, as all interactions and transactions can be recorded on chain.

The past year has seen significant growth in projects which fuse AI and crypto, particularly from the point of view of decentralized AI marketplaces and AI agent crypto projects. Given these trends and the general direction of both the AI and crypto markets, the next year is likely to see even larger growth.

Likely AI Crypto Trends for 2025

• Significantly Increasing Values of AI Crypto Projects and Tokens
  AI evolves faster than any other technology on the planet. This is because AI learns the more it’s used, and the breakneck speed of AI innovation is only increasing with AI agents that can learn autonomously. Historically speaking, innovation has always attracted higher investments, which means higher company & project valuations. Couple this with the growing adoption and credibility of crypto technologies (via things like crypto ETFs and government adoption), and AI crypto projects are a fusion of two exponentially-growing technologies that will hold up much of the future.
• Emergence of More AI Agent Platforms. With AI agents being the next innovation in machine learning we’re likely to see continued expansion of projects focusing on autonomous AI agents. These agents may move into increasingly sophisticated roles like automating online transactions, managing services like DeFi & arbitrage, or interacting with real-world data in new ways. Original and early AI agents platforms may have an edge over newer platforms because their AI agents have had more time to learn and evolve, along with more investments and work already having been pumped into them.
• Deeper Integration with Web3 Infrastructure. We are likely to see a higher level of integration between AI models and different parts of Web3, like AI oracles used for DeFi use cases (Oraichain), blockchain-based AI Agent creation tools, and intelligent NFTs (iNFTs) that use LLMs to interact with owners (Alethea AI).
• Continued Innovation Despite Market Fluctuations. Crypto markets are notoriously volatile, and even though the market currently sits at all time highs, a bear market could ensue at any time and crash prices. No matter which way markets swing, AI innovation will continue regardless, and it will continue because of the almost infinite use-cases of AI technology. A large driver (and essential indicator) of value is how useful a thing or technology will be, and AI is no different in this respect. Innovation will continue despite any market fluctuations, and when markets swing from bull to bear and back to bull again, AI crypto projects are likely to swing in higher degrees because of actual real-world use cases.

AI Crypto Projects & Tokens to Look Out for in 2025

• Virtuals Protocol ($VIRTUAL)
  Virtuals Protocol (formerly Path DAO) is a decentralized platform that enables users to create their own AI agents without the need for any technical expertise. The protocol also allows users to monetize and tokenize agents, allowing for co-ownership and revenue-sharing models between users.
• The largest user-created AI agent on Virtuals is currently AIXBT (current market cap $519B), an intelligence platform using narrative detection and other tools to supply users with actionable crypto market insights.
• $Virtual token saw a meteoric rise from $0.01145 on its release at the end of 2023 to an all time high of just over $4.60 in Jan 2025 (over a 40,000x increase). The use-case of Virtuals Protocol is undeniable. The capability to create, deploy and monetize AI agents on-chain without technical knowledge opens up a world of possibilities. If the popularity of AI agents continues to grow, Virtuals Protocol is almost certain to grow with it.
• AI16Z ($AI16Z)
  AI16z is a DAO that integrates artificial intelligence (AI) to revolutionize venture capital investing via a blockchain ecosystem. Essentially using AI algorithms and collective intelligence, its AI agent Marc AIndreessen evaluates startups and facilitates funding to make investment decisions in the crypto market, with a particular focus on meme-driven assets and rapidly changing trends within Web3.
• The $AI16Z token functions as a governance and utility token, enabling ecosystem transactions and voting rights. Having been released in Nov 2024, the token reached an all-time high of $2.42 in early Jan 2025, and is currently sitting around a market cap of $850M. AI16z promises to be highly autonomous and evolve via the DAO. Given the popularity of AI agents and the AI focus on assisted investing, $AI16Z could be poised to become more valuable alongside the wider AI agent market.
• AI Network ($AIN)
  AI Network focuses on decentralizing AI resources/development and making AI useful for individuals & businesses alike. The project attracted over $15M in funding and was among the first AI crypto projects to develop and release AI agents.
• AI Network focus on Hyper Agents — self-learning goal-oriented AI agents focused on achieving measurable results. Their agents can perform autonomous value assessment of AI assets, assist in AI talent acquisition via token incentives and sustainability fund GPU resources through tokenization, all of which are performed on the AI Network ecosystem. All hyper agent actions, interactions and transactions are recorded on-chain, ensuring human oversight.
• AI Network’s real world example of hyper agents can be seen through Unblock Media; the world’s first newsroom populated entirely by AI agents. Unblock Media agents choose & research news topics, write & edit articles, create images and prepare pieces for final release (a human presses the ‘publish’ button, ensuring human oversight).

$AIN token, AI Network’s native cryptocurrency, mediates all interactions in the ecosystem (hyper agent and user interactions) and is key to all AI Network’s functions. Use of the ecosystem means higher use of $AIN token, and this is a token we’re watching as AI agents rapidly grow in popularity.

• Zerebro ($ZEREBRO)
  Zerebro is an autonomous AI system designed to create and distribute culturally impactful content (particularly in financial and social media domains) across decentralized and social platforms. Its AI operates autonomously and independently of human oversight, and promises to shape cultural and financial narratives through self-propagating content that blends fiction with reality, a concept known as hyperstition.
• Zerebro will post on various social channels, including X, Instagram, Warpcast, and Telegram, and maintains content diversity while avoiding ‘model collapse’, a common degenerative effect in AI content models, through retrieval-augmented generation (RAG).

The $ZEREBRO token has been trading for a few months and facilitates various functions within the platform, like access to exclusive content, participation in governance and engagement in dApps. Autonomy and diversity in AI crypto content are likely to be needed in a much higher degree as higher proportions of content are created by AIs. Zerebro could be instrumental in this function, making them a key contender for token growth.

• Griffain ($GRIFFAIN)
  Griffain enables users to create and manage AI agents capable of executing and assisting in complex on-chain tasks, like handling crypto wallets, automating token trading and NFT minting. Griffain provides two types of agents; personal agents which users can customize and control, and special agents pre-designed for specific functions.

The $GRIFFAIN token facilitates governance, incentivization and user interactions on the platform, and is also essential to their DeFi services (liquidity pools and reward earning). Griffain is essentially a platform designed to use AI agents to make crypto more accessible to the wider population. This is key for global crypto adoption in general (the current amount of crypto holders globally said to be around 6.8%), and as crypto adoption grows alongside use of AI agents, a platform which uses AI to make crypto use easier is poised to grow along with it.

In Summary

AI will continue to evolve, the market will continue to grow and AI projects will continue to innovate, alongside the inevitable continued growth of the crypto market. AI agents are the current evolution of machine learning, and projects which combine AI and crypto to provide genuine user benefit through innovative technologies are highly likely to grow alongside.

This article is for informational purposes only and does not constitute financial or investment advice. Always conduct thorough research and consider professional guidance before engaging with or investing into any cryptocurrency or AI-related project.

AI is on the path to becoming ubiquitous. Creatives, office workers, academics and everyone in between have use-cases that AI can help them with, and many already make use of AI regularly.

AI, however, is still in a state of relative infancy when it comes to provable and measurable outputs, especially for business use-cases, where time and money invested need to show a measurable return.

Can AI Measurably Help My Organization?

From a business standpoint, the most pertinent questions regarding investing into AI infrastructure include:

• Can I accurately estimate and prove generative AI’s business value and output?
• Can we manage AI systems without hiring experts (developers, managers etc)?
• Should we invest in expensive AI hardware and infrastructure? Can we ascertain a measurable ROI?

AI Network: an Ecosystem that Adapts to Your Business Needs

The AI Network ecosystem self-funds GPU resources and talent via the blockchain.

GPUs in the ecosystem are tokenized and container infrastructure enables decentralized GPU resource sharing. GPUs are the driving force behind AI and GPU power is required to train and run models.

Skilled talent participation is incentivized through token rewards via the open-source AI Network ecosystem. Rewards are blockchain-based and recorded on-chain.

Business value is autonomously assessed for AI-generated content using Web3 automation, traffic projections and SEO through the ecosystem.

Why is Business-based AI adoption so Important?

The reasons are three-fold.

1. Using AI to Assess the Value of AI-generated Assets

The number of AI-generated assets in existence is growing exponentially (content, code, images, video etc made by AI). Human attention is slowly becoming overwhelmed by this volume of content, and we require a system to accurately assess the value of these AI-generated assets. We can utilize AI itself to accurately assess these values, empowering businesses & creators to monetize the correct AI-generated assets and avoid human attention overload.

2. Market Fairness through Open Source AI Development & Decentralization

Web3 incentives provide a strong tool for decentralizing AI development, in a world full of AI run by big tech corporations. This allows for a greater level of competition and therefore fairness within the AI market, by fighting against private monopolies. By utilizing tokenized rewards, open-source AI developers can provide APIs and be fairly compensated, aligning their contributions with the value created from AI-generated content. This also enables a voice and exit strategy through Web3, empowering developers to contribute meaningfully or exit projects if the incentives aren’t aligned, thereby decentralizing AI development beyond corporate control.

3. Affordable & Efficient Scaling of AI Solutions via Web3

The number of distributed GPU nodes in Web3 has reached an all-time high (nodes which can provide power to develop and run AI models). The collective computational and participation power of the network has reached a point strong enough to lead AI development. Token funding models which incentivize GPU power supplying allow businesses to tap into this distributed GPU power, aligning resource use with the accurate valuation of AI solutions for business. This makes scaling AI projects both affordable and efficient, leveraging the decentralized strength of Web3 nodes.

HAML & Hyper Agents — How We Automate AI Business Solutions

HAML — Hyper Agent Markup Language — inspired by HTML, is a groundbreaking language created by AI Network for enabling and structuring interactions between hyper agents.

Hyper agents are autonomous artificial intelligence entities, capable of learning & evolving by interacting with each other. Hyper agents are programmed with specific purposes and improve on their capabilities by exchanging information, without the need for human input. HAML facilitates this process by defining agents, interactions and conversation contexts. This enables dynamic, transparent & observable interactions between hyper agents and the AI solutions they provide.

The dynamic and autonomous nature of hyper agents is how we can automate AI value creation, assess AI-generated assets, incentivize talent within AI, and sustainably fund GPU resources for development

Hyper Agents & HAML — Real World Business Use-Cases

Unblock Media

A practical application of hyper agents can be seen in Unblock Media, the world’s first fully AI-driven newsroom, run entirely by hyper agents. Hyper agents work 24/7 to learn, research, write and publish crypto news updates to audiences, contrasting with human-led newsrooms which have constraints on time and labour.

HAML allows for real-time visualization of hyper agent conversations in the Unblock Media newsroom, and all interactions and articles are recorded on the blockchain, ensuring transparency. This transparency is crucial as hyper agents become more widespread, ensuring integrity in their development.

Unblock Media is just one hyper agent use-case, and these hyper agents can be utilized to create any type of content for any industry. For example sport news, legal journals, scientific articles, political updates, with the ability to create content 24/7, learning and improving with every piece they generate. Get in touch with us here to explore options.

Inbody Fit+

Inbody fit+ is your own personalized AI chatbot, based on your unique body composition data, becoming your 24/7 personal health partner. The assistant is ready to answer all your health questions at anytime, and is powered by hyper agents consistently learning from your input and their inputs with each other.

We are able to provide optimal HAML-powered solutions to the healthcare sector without the need for AI experts, get in touch here.

Baby Shark

Pinkfong, the South-Korean based creator of Baby Shark, the hugely popular children’s song & dance that became a global sensation, had a sticking issue with their audience. Essentially, their audience outgrew Baby Shark too quickly, and their challenge became retaining existing audience members.

With AI Network’s autonomous content generation system, fans were empowered with the ability to design their own Baby Shark NFT, building personalized experiences and deeper emotional connections.

The result is a loyal, long-term fan base and a powerful new revenue stream for Pinkfong — using hyper agents to turn fleeting attention into real brand loyalty.

Conclusion

It is essential for businesses to adopt AI in a meaningful way, to assist in obtaining measurable business outcomes. We are the beginning of the AI trend, and early-adopters are the ones to stay ahead of the curve.

With HAML and hyper agent technology we provide Web3-based AI business solutions which provide value, talent and GPU resources in an autonomous way, with minimal human input. This ensures our AI solutions consistently learn and grow, delivering ever-more value as they do.

Get in touch at contact@comcom.ai to learn more.

AI Network is a blockchain-based decentralized AI development ecosystem. We are creating a Web3 era for AI, where anyone can easily develop and utilize AI.

• AI Network Website: www.ainetwork.ai
• AI Network YouTube: youtube.com/@ainetwork_ai
• AI Network Twitter: twitter.com/ainetwork_ai

Web3 AI London was the first ever Web3 and AI focused conference held in London. The summit saw 10 speakers giving keynote addresses, 2 panels and over 20 grassroots Web3 innovators & hackathon participants building programmes and presenting their ideas.

This groundbreaking event delved into the intersection of Web3 & AI and encouraged participants to interact with technology and Web3 projects via challenges, task collaborations and hackathon prizes.

Primarily organised and run by AI Network, Web3 AI London was held at Kachette in Shoreditch, in the heart of London’s creative and tech district.

The conference brought together founders, CEOs, academics and likeminded enthusiasts from across the Web3 space and beyond, discussing topics like the Internet for AI, on-chain art, climate & web3, plus much more.

Event Sponsors

Co-sponsors included;

• AI Network: The Internet for AI in Web3, built on the blockchain. Making AI development useful & accessible to everyone.
• Solana: The eminent proof-of-stake blockchain with its native cryptocurrency, SOL.
• Superteam UK: A community of the best talent building in crypto on Solana in the UK.
• Bitmart: The centralized exchange providing crypto asset trading and investment services to over 9 million users around the world.
• NFT Soho: One of the largest London-based Web3 communities bringing together Web3 creatives, enthusiasts, developers and OGs.
• Cambridge University Entrepreneurs: The largest fully student run launchpad in Cambridge, backed by the University.

Web3 AI London Conference

Hosted by Sandra Tusin, EMEA lead at AI Network & NFT.Soho founder; and Mona Tiesler, Investment Lead at Tokentus & Investor at Hydra; the event kicked off with welcome addresses from AI Network CEO Minhyun Kim, Bitmart and Solana Superteam explaining the parameters and prizes for the hackathon day, with over $3000 worth of prizes to be won.

AI Network will also host an X (Twitter) space recapping the event. AI Network host weekly Twitter spaces covering topics in Web3 and AI.

Follow AI Network on X (Twitter) to stay in the loop and join spaces.

For the hackathon on the day, one challenge run by AI Network was the chance for participants to win $AIN token, simply by using AIN’s new Unblock Media service. Unblock Media is the world’s first newsroom run entirely by AI Agents, dedicated to bringing the world around-the-clock crypto market news updates.

Visit Unblock Media here to check it out and join the Telegram group here to get free daily crypto news updates.

​Over 500 professionals, academics, students and those passionate about web3 and AI attended throughout the day, and the summit offered the unique opportunity to engage with experts and like-minded individuals from around the world.

Keynote Speakers — Session 1

Rajeet Singh | AI Network

Rajeet Singh, content & strategy at AI Network, gave the opening keynote on how AI Network is the Internet for AI in Web3 — making AI development accessible and ownable, by allowing anyone to build AI (without having to be a developer) and own it through the blockchain. This is done through AINA, the world’s first open source LLM and AI agent marketplace built on blockchain, where anyone can build and own AI models (and everything they create) on-chain. Unblock Media is also built on AINA.

Jennifer Roebuck | The Lumen Prize, CEO

Jennifer gave a fascinating talk on the future of on-chain art and how it may affect artists and the art market. Jennifer is CEO of The Lumen Prize, an art & technology prize rewarding emerging and leading talent in crypto & web3, and CMO of Metaversal, an emerging technology venture studio & asset management fund focused on creativity & ownership in Web3/crypto.

Joseph Lassens | Green Flare, Cofounder & CFO

Joseph gave a rousing speech on the absolute importance of climate considerations in the future of computing and blockchain technology. Green Flare focuses on building data center infrastructure and services that are climate-positive and emission-reducing, through utilizing stranded energy resources that would otherwise cause environmental damage.

Clemens Scherf | NEAR, Cambrian Collective

Clemens drew on his wide breadth of web3 experience to speak on the crypto ecosystem playbook; how to build effective ecosystems and how AI may intersect with blockchain ecosystems in the future. Clemens is a venture builder at NEAR Protocol and co-founder of Cambrian Collective, Web3 Advisory focused on fundraising, product and protocol design and venture building.

Matteo Spinosa | Doefin, Founder

Matteo introduced Bitcoin hashrate as a commodity, which is what his venture specialises in. Doefin is the first platform offering on-chain options on Bitcoin Difficulty, acting as a risk management tool for miners that also allow traders, market makers, and crypto institutions to take synthetic exposure to hashrate. Doefin transforms hashrate volatility into a tradable and hedgeable asset.

Panel 1 — VC investments into Web3 and AI

The first panel of the day focused on venture capital investments into the Web3 and AI spaces, and investments into projects and companies at the intersection of the two technologies.

Moderated by Mona Tiesler of Tokentus, panelists included:
Pasarn Intarangsi, CFA of Elixir Capital; Gvantsa Chkuaseli, head of fundraising at CV VC; PeiPei, managing partner at IOBC Capital; Yaroslav Writtle, partner at Faculty Group; and Caleb of Big Brain Holdings.

Keynote Speakers — Session 2

Mladen Kostov | GRVTY, Cofounder & CEO

Mladen gave the first talk in the second session of the day on Gamified Sports Engagement in Web3, and how fan can connect with athletes using Web3 connectivity. GRVTY enables athletes to engage with fans & capitalise their personal brand and sign sponsorship deals via DLT, and own data through blockchain-based digital ID.

Greg Bock | Fidesium, Cofounder

Fidesium cofounder Greg Bock spoke on the absolute importance of cyber security and how Web3 can automate security services and practices. Fidesium makes it safe & easy for you to store, buy, send, receive, swap tokens and collect NFTs on the Ethereum blockchain.

Iris Ten Teije | Mava, Cofounder

Iris delivered a keynote on the pertinence of building communities in AI & Web3, and how communities have become more important than ever before, especially in a Web3 enabled world. Mava is an AI-driven customer support platform designed for community-focused companies, helping streamline support operations and enhancing user engagement. Mava integrates with communication channels like Discord, Telegram, Slack, and web chat, allowing businesses to manage support requests from a centralized dashboard, and its AI capabilities enable it to learn from existing support content, such as GitHub repositories, Google Docs, and websites, facilitating the automation of responses to common queries.

Dan Miles | Bizzed

Bizzed leverages AI technology to facilitate small business acquisitions, focusing specifically on retiring baby boomers with businesses that can be passed onto a new generation of entrepreneurs. This was what Dan Miles’ speech was about, and also spoke on how the Bizzed platform offers AI-powered due diligence tools, providing insights into projected cash flow, return on investment (ROI), and market-specific risks.

Panel 2 — Media and the Creative Industry in Web3

The second panel focused on Media and creativity in Web3, and topics like Web2 vs Web3, NFTs and artists, technology trends and AI in creativity were discussed spiritedly.

Moderated by Sandra Tusin of AI Network & NFT.Soho, panelists included:
Miki Elson, founder of Artsect DAO; Jack Land, head of marketing at MetaWealth; Graham Gabie, CEO of SyncVault; Paul Dowling, cofounder at KXSB & Mindstream AI; and Rajeet Singh, Web3 consultant and marketing & strategy at AI Network.

Panel 2 — Media and the Creative Industry in Web3

Hackathon and Prizes

Throughout the conference participants were invited to take part in a hackathon to build innovative and novel programmes on the Solana ecosystem, in competition for prizes offered by Solana Superteam UK.

Eight different teams presented their ideas, with inventive and original ideas like wallet credit-checking on Solana and metaverse-based theatre performances being exhibited. Superteam gave prizes for the most impactful and innovative ideas, with two teams winning $1,000 each and two runners up winning $500 each in SOL.

Weekly X Space (Twitter Space)

AI Network run a weekly X (Twitter) space covering Web3 and AI topics, with various guests every week from across the crypto, Web3 and AI worlds.

To join the weekly X (Twitter) space and stay in the loop follow AI Network on X (Twitter).

Summary

The first Web3 AI conference in London was a resounding success, with C-level execs, Web3 innovators, academics and students converging to learn, collaborate and build in Web3 and AI, through keynote, panels, hackathon-ing and networking.

AI Network, as the main organizer of these events, grows the strength of its ecosystem and crypto token with each event and partnership with projects taking part. AI Network has multiple facets to its ecosystem and multiple ways in which users can utilize the power of AI Network.

• Join the free telegram channel of Unblock Media, the world’s first all-AI agent newsroom where you’ll get free daily crypto market news updates.
• Create your own AI agents in AINA, AI Network’s open source LLM chatbot built on the blockchain. All your interactions and AI agent generations are digitized as NFTs owned by you, meaning you own all the value the AI creates. The AINA platform launches soon.
• If you’re an AI project that requires GPU resources you can claim *free* GPU power through the AI Network ecosystem, simply submit a proposal here.

$AIN token serves as the backbone for the entire AI Network ecosystem.

AI Network is a blockchain-based decentralized AI development ecosystem. We are creating a Web3 era for AI, where anyone can easily develop and utilize AI.

• AI Network Website: www.ainetwork.ai
• AI Network YouTube: youtube.com/@ainetwork_ai
• AI Network Telegram: t.me/ainetwork_kr
• AI Network Twitter: twitter.com/ainetwork_ai

Web3 AI London Conference: CEOs, Academics & Innovators Explore Tech Intersections was originally published in AI Network on Medium, where people are continuing the conversation by highlighting and responding to this story.

Artificial intelligence is transforming the ways in which we work, learn and use the web. This rate of transformation is rapidly accelerating, with the future of not only AI but also the internet itself becoming increasingly decided by big tech companies, rather than by its users.

To address this issue, AI Network has emerged as an ecosystem dedicated to democratizing AI development and utilization. Based on the blockchain, AI Network envisions a future where anyone can easily develop, utilize, and own AI.

This fosters a collaborative environment that shifts away from traditional exploitative models of the web — models which focus on extracting user data & monetary value through ads, and instead focuses on a user-centric web, one which celebrates creativity, and is contributed to and owned by its users.

AI Network’s Vision: To Build an Autonomous Value Network

AI Network’s core mission is:

To build an autonomous value network for collaborative computing, realizing the user-centric web

This vision addresses a fundamental crossroads facing the internet today.

On one path lies the continuation of an extractive web model, where users are treated merely as consumers, and value is extracted from them primarily through advertising and data collection. On the other path is a transformative approach that fosters a value network for collaborative computing.

In the latter model, users are seen as a source of creativity, actively sharing their skills & ideas and becoming valued creators whose contributions are recognized and verifiably owned through the blockchain. This is the user-centric web.

AI Network is committed to bringing this vision to life. By leveraging blockchain technology, we aim to create an ecosystem where collaboration is incentivized, and the value generated is equitably shared. This is the autonomous value network.

This approach not only enhances user engagement but also ensures that the development and deployment of AI technologies are more inclusive and accessible.

The Bootstrapping Problem: Overcoming Challenges in AI Adoption

The general bootstrapping problem refers to the challenge of developing a system, process, or business without the necessary resources, support, or initial conditions typically required for its inception, like building a business from the ground-up without any outside funding or support.

In the context of AI, the bootstrapping problem pertains to the difficulties organizations or individuals face when adopting AI technologies without sufficient initial resources, expertise, or proven frameworks.

The adoption of AI technologies presents significant challenges for businesses and organizations.

The Challenges:

• The primary concern regarding adoption of AI for business is in determining whether the AI will genuinely benefit the organization. According to research by Gartner, the biggest challenge in adopting generative AI is estimating and proving its business value. Many organizations struggle to justify the investment required for AI initiatives due to uncertainties about the ROI and the tangible benefits that AI can bring.
• The second hurdle is whether AI can be managed without specialized expertise. Gartner’s research highlighted that finding the right talent is the second biggest challenge in AI adoption, with 41% of respondents citing it as a significant concern. The scarcity of skilled AI professionals makes it difficult for organizations to build and maintain AI capabilities internally.
• The third issue is the almost astronomical cost of AI hardware, particularly GPUs (Graphics Processing Units), which poses a significant financial challenge. Sequoia Capital noted that high current spending on GPU resources is potentially unsustainable, especially for startups and smaller organizations that lack substantial capital reserves.

The AI Network Solution: A web that adapts to user values and self-funds GPUs & talent.

AI Network addresses these challenges through a multifaceted approach which leverages the strengths of blockchain and decentralization.

Firstly, by creating a web that adapts to user values and self-funds GPUs and talent, AI Network mitigates concerns about AI’s business value. The platform employs web-based value assessment for AI-generated content using Web3 automation, traffic projections, and search engine optimization (SEO). This means that the value of AI is identified and optimized autonomously, reducing the need for businesses to invest heavily without guaranteed returns.

Secondly, AI Network eliminates the need for organizations to manage AI without experts by incentivizing skilled talent participation via token rewards. By rewarding contributions in $AIN token, the platform attracts a global pool of AI professionals motivated to contribute their expertise. This decentralized approach to talent acquisition ensures organizations can access the skills and manpower they need, bypassing traditional hiring challenges.

Lastly, the platform addresses the issue of expensive AI hardware by utilizing tokenized GPUs infrastructure, enabling decentralized resource sharing. This model allows for the sustainable funding and utilization of GPUs, as resources are shared across the network rather than being owned and maintained by individual organizations. It democratizes access to high-performance computing power, making it feasible for startups and smaller entities to engage in AI development.

$AIN Token: Fuelling the Ecosystem

Central to AI Network’s ecosystem and all its solutions is $AIN token, AI Network’s native cryptocurrency. $AIN mediates all interactions within the platform, and is not only a medium of exchange but also a mechanism for rewarding contributions and incentivizing participation.

By integrating the token into various aspects of the ecosystem, AI Network ensures value is distributed fairly among participants, aligning incentives with the platform’s collaborative ethos.

$AIN is tradable on several exchanges, including Bitget, MEXC, Lbank, Gopax, Uniswap and AIN Wallet.

Conclusion

AI Network stand at the forefront of a paradigm shift in how AI technologies are developed, deployed and utilized.

By building an autonomous value network on the blockchain, we envisage a user-centric web that values collaboration and equitable distribution of resources and rewards. By addressing the key challenges in AI adoption, AI Network aim to make AI more accessible and sustainable for users and businesses.

If you think you can benefit from our solutions, get in touch:

• AI Network Website: www.ainetwork.ai
• AI Network DAO Discord: discord.com/invite/aindao
• AI Network YouTube: youtube.com/@ainetwork_ai
• AI Network Telegram: t.me/ainetwork_kr
• AI Network Twitter: twitter.com/ainetwork_ai