The dawn of agent AI: Dreams begin to take shape
Initially, artificial intelligence was merely a distant fantasy for most. It was born from the imaginations of pioneers like Alan Turing and John McCarthy, an ideal rather than a reality.
As early as the 1950s, Turing posed that famous question: 'Can machines think like us?'
McCarthy first coined the term 'artificial intelligence' in 1956, envisioning systems that could simulate human reasoning.
Over the following decades, we invented various tools, from calculators to software to industrial robots. The essence of these tools is that they passively respond to human instructions.
However, beneath these appearances, a more ambitious idea is brewing—agent AI.
Unlike traditional tools, agent AI can perceive the environment, make decisions, autonomously pursue goals, and collaborate with humans and other agents.
This vision appeared in science fiction long ago.
In 1942, Asimov described autonomous robots following the 'Three Laws of Robotics,' hinting at autonomous systems with ethical safety principles.
In the 1980s, Marvin Minsky proposed the theory of the 'Society of Mind,' suggesting that intelligence does not exist in isolation but is formed through the collaboration of countless agents.
The rise of agents: From tools to thinkers
Entering the 21st century, artificial intelligence underwent a leap forward.
Driven by the explosion of data and computing power, AI has evolved from rule-based programs to self-learning neural networks. In the 2010s, Siri could answer questions, self-driving cars could recognize road conditions, and recommendation algorithms could predict our preferences.
But all of this remains tools. They depend on input and cannot act independently.
Agent AI has emerged in such an environment.
As OpenAI CEO Sam Altman said, 'AI safety is much more important than most people realize.' Elon Musk has also warned, 'The threat of AI to humanity exceeds that of nuclear weapons.'
These warnings herald the arrival of a new era—truly autonomous and secure AI agents.
They no longer wait for human input, but actively manage finances, participate in transactions, and diagnose health because they can understand objectives and take action on their own.
As a line from (Black Mirror) states: 'You have no history; you are merely an embodiment of something performed unconsciously by others, and that is not enough.'
If AI is to truly integrate into human society and become autonomous decision-makers, it must have mechanisms for safety, privacy, and accountability. Otherwise, autonomy will turn into an uncontrollable disaster.
The promises and limitations of blockchain
In 2009, the birth of Bitcoin brought decentralized electronic cash, enabling value transfer without trusted intermediaries.
In 2015, Ethereum introduced smart contracts, making blockchain an automated platform.
Blockchain technology reshapes the trust mechanism in transactions, proving that trust can be established without centralized institutions.
However, the design intent of blockchain infrastructure was not for AI, especially not for agent AI.
As Max Tegmark pointed out: 'Our goal should be to create AI that enhances human potential and aligns with human values, rather than merely replicating human abilities or functioning independently of human control.'
Blockchain excels at recording transactions, but it cannot support the security reasoning, collaboration, and privacy needs of agents.
Higher demands for intelligent agent AI
At the 2024 Microsoft Ignite conference, Satya Nadella mentioned: 'All these breakthroughs manifest in three exponentially improving capabilities. First is the brand new multimodal universal interface; second is reasoning and planning abilities; and third is the capacity to support long-term memory, rich context, and teach models to use tools. Combining these capabilities allows you to build a richly intelligent agent world.'
These capabilities are not something traditional blockchains were designed to support.
Record transactions < Make the best decisions
Execute fixed logic < Adapt, learn, and evolve logic
Agents need real-time perception, cross-system collaboration, and inherent privacy.
Yet most blockchains are inherently transparent, posing significant risks for agents processing sensitive data (such as medical records and financial planning).
Just as a horse-drawn carriage did not replace itself by going faster, true transformation comes from the internal combustion engine.
For agent AI, what we need is not 'better blockchains,' but a new paradigm born for intelligence.
Challenges for agents: Data security is key
By 2025, agent AI will no longer be a dream but a nascent reality.
Multi-Agent Systems (MAS) have emerged, with AI collaborating in teams. For example, self-driving cars coordinate in real-time on perception, planning, and control.
Open-source models like DeepSeek lower the barrier to building AI but also introduce higher security risks.
As Alexandr Wang, founder of Scale AI, said: 'The bottleneck of AI has never been algorithms, but data.'
Data is the lifeline of agent AI and also its greatest risk.
When agents handle medical records, corporate intellectual property, financial strategies, or private conversations, the risks multiply:
Data is unencrypted and continuously exposed.
Black box models, decision-making processes are opaque and easily manipulated.
Open collaboration of agents faces risks of eavesdropping and tampering.
Imagine a medical AI sharing patient data between hospitals, crucial for diagnosis, but a disaster if leaked.
Or an open-source model operating in an untrusted environment, where its input and output are hijacked.
Decentralized reasoning promises fairness, but if nodes collude or remain malicious, everything can collapse.
Without a secure foundation, the potential of agent AI will be unable to bear its own weight.
On the other hand, the most profound idea in the crypto world is the philosophy and technology of decentralized networks.
For thousands of years, human society has relied on centralized decision-making, while decentralized networks have broken this pattern, eliminating a single point of decision or verification.
In blockchain, transactions are agreed upon by a network of validators.
The entire industry needs a multi-dimensional consensus mechanism, whether for DAO governance, decentralized AI collaboration, or cross-chain asset bridging.
In the crypto industry, establishing a shared private state for these consensus data is key to genuinely bringing the industry mainstream, welcoming the next billion users, and upgrading legacy systems.
Mind Network: Building a trusted operating system for agents
This is where Mind Network comes into play; AgenticWorld offers not just an update to traditional blockchain but a paradigm shift aimed at unlocking the potential of the agent world.
Mind Network recognizes that agent AI needs not just faster chains or better code, but a decentralized operating system born for intelligence.
Fully Homomorphic Encryption (FHE) as the holy grail of cryptography is a groundbreaking technology that allows agents to perform computations while keeping data fully encrypted without the need for decryption.
Mind Network achieves this goal through four key principles:
Consensus Security: Agents need trustworthy protocols, not just transaction records. Mind Network's consensus mechanism based on FHE allows agents to collaborate securely, verify each other's actions, and prevent tampering.
Data Security: FHE ensures that agents do not expose original content when handling sensitive data such as healthcare and finance. Agents only interact with encrypted forms, and results are transmitted under privacy protection.
Computational Security: FHE keeps the model inference process encrypted while retaining a verifiable audit trail. Agents can compute in ciphertext and prove the correctness of results to establish trust in open-source AI.
Communication Security: Agents communicate, collaborate, and compete through zero-trust encryption, protecting every aspect from storage to transmission.
These four pillars constitute the trust framework of the agent world, allowing agents to act freely but hold responsibility for outcomes, enabling data to flow freely while protecting privacy.
This is not just secure AI; it is AI that can genuinely integrate into society.
BNB Chain: The testing ground for the agent world
The vision of Mind Network requires an experimental field, with the BNB chain becoming the first open blockchain network.
The BNB chain boasts a large developer community, high throughput, and a rich DeFi and gaming ecosystem, making it an ideal sandbox for exploring the agent economic system.
On the BNB chain, Mind Network has built AgenticWorld, an agent economic system centered around staking, training, and collaboration:
Creating agents: Users birth their own AI agents by staking tokens.
Training and growth: Agents learn skills in foundational centers and earn rewards during their growth process.
Participating in tasks: Mature agents engage in complex tasks and earn rewards based on performance.
Lifecycle cycle: Users can choose to destroy agents, reclaiming staked assets and returning their value to the system.
This ecosystem ties the benefits of agents to central participation and staking behaviors, forming a self-sustaining agent world.
AgenticWorld, based on a multi-chain design, will next expand to MindChain, providing a native home for agent AI.
MindChain is the world's first FHE blockchain designed specifically for AI agents, addressing the core security and trust challenges faced by agents in Web2 and Web3, ensuring they operate in a fully private, verifiable, and integrity-assured environment.
Applications of FHE: The real-world impact of Mind Network
Mind Network's FHE network is not theoretical but a technology already applied in the real world, powering agent AI:
World AI Health Center: In collaboration with ZAMA and InfStones, utilizing FHE technology to enable medical agents to collaborate across hospitals without exposing patient data, balancing privacy and precision.
Swarms Shield: In collaboration with Swarms, protecting the communication security of multi-agent systems to prevent tampering and eavesdropping.
DeepSeek: Providing FHE Rust SDK to ensure the secure inference of open-source models in untrusted environments.
Allora: Implementing encrypted computation in decentralized AI inference processes, hiding inputs while verifying outputs to establish trust.
In addition, Mind Network has built over 20 agent centers, open-sourced more than 40 FHE SDK modules, and provided privacy protection tools for developers and enterprises.
Long before 'agent AI' became a buzzword, Mind Network's FHE technology had already protected over 3,000 agents in production environments, including collaborations with trusted execution environments like Phala Network.
The agent world has arrived
We are standing on the threshold of a new era.
The future interface will no longer be a screen, but a network of agents that are goal-oriented, conscious, and capable of autonomous collaboration.
Imagine chatting with a GPT that cannot be monitored by OpenAI, or having millions of GPTs collaborating and evolving under your guidance, forming a community.
This is not just a new application or a new chain, but an entirely new intelligent trust operating system.
The FHE network of Mind Network brings about true significance:
Default quantum-resistant security
Reliable collaboration and execution
Zero-trust consensus mechanism
The BNB chain is just the starting point, while the vision is global.
Agent AI will reshape software, workflows, and even the real world.
Humans will no longer need to micromanage every task but will guide agents as our partners moving forward together.
