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Pavel Durov Reveals Cocoon: A Decentralized AI Network on TON Blockchain for Ultimate Privacy
Key Takeaways
- Pavel Durov, Telegram’s co-founder, has launched Cocoon, a decentralized AI network built on the TON blockchain, allowing users to access AI tools while keeping their data private.
- Users can contribute their GPU processing power to the Cocoon network and earn Toncoin (TON) in return, promoting a decentralized approach to AI.
- The project emphasizes protecting digital freedoms against the risks of centralized AI, such as data breaches and information manipulation.
- Decentralized AI on blockchain like TON could prevent censorship and ensure tamper-proof data, highlighting blockchain’s role in enhancing privacy.
- Cocoon addresses growing concerns in the AI space by decentralizing computation, making it a timely innovation amid discussions on data sovereignty.
Imagine a world where your personal data isn’t hoarded by tech giants, where AI works for you without spying on you. That’s the vision Pavel Durov, the innovative mind behind Telegram, painted when he stepped onto the stage at the Blockchain Life 2025 forum in Abu Dhabi, United Arab Emirates. He unveiled Cocoon, a groundbreaking decentralized AI network constructed on The Open Network (TON), the layer-1 blockchain closely tied to Telegram. This isn’t just another tech announcement—it’s a bold step toward reclaiming our digital freedoms in an era where centralized systems have been chipping away at them for the past two decades.
Durov’s message resonated deeply: we’ve been losing ground in the fight for online privacy, and centralized AI is accelerating that loss. Think of it like this—centralized AI providers are like overbearing landlords who control every inch of your digital home, potentially peeking through the windows or even rearranging the furniture without your consent. Cocoon flips the script, turning users into the architects of their own AI experiences. By leveraging the decentralized nature of TON blockchain, Cocoon empowers people to tap into powerful AI features without handing over their sensitive information to a single, vulnerable entity.
Why Decentralized AI on TON Blockchain Matters for Privacy and Freedom
Let’s dive deeper into what makes Cocoon a game-changer. At its core, this network is designed to democratize AI access while prioritizing privacy. Users aren’t just passive consumers; they become active participants. If you have spare graphics processing units (GPUs) lying around—perhaps from your gaming rig or home setup—you can lend that power to the Cocoon network. In exchange, you earn Toncoin (TON), the native cryptocurrency of the TON ecosystem. It’s a win-win that echoes the peer-to-peer ethos of blockchain technology, much like how early Bitcoin miners contributed computing power to secure the network and got rewarded for it.
Durov didn’t mince words about the urgency. He highlighted how, over the last 20 years, digital freedoms have been eroding. Centralized AI systems, he argued, make it too easy for providers to control narratives, censor content, or even distort facts in real-time. Picture a librarian who not only decides which books you can read but also rewrites them on the fly—that’s the risk with centralized AI. Decentralized alternatives like Cocoon, built on TON blockchain, distribute the power, ensuring no single point of failure or control.
This isn’t speculation; industry experts back it up. For instance, leaders in the crypto and Web3 space have pointed out that centralizing massive amounts of user data creates honeypots for hackers. A breach in one centralized server could expose millions, leading to identity theft or worse. In contrast, blockchain’s decentralized ledger acts like an unbreakable chain of evidence, recording every data interaction immutably. This tamper-proof quality ensures that AI-generated information can be verified, fostering trust in a way centralized systems simply can’t match.
Comparing Centralized AI Risks to the Strengths of Decentralized Networks Like Cocoon
To really grasp the difference, let’s compare the two worlds. Centralized AI is like a bustling city bank—efficient but a prime target for robbers. We’ve seen real-world examples where data breaches at major tech firms exposed user information, leading to widespread privacy nightmares. On the flip side, decentralized AI on platforms like TON is more akin to a network of community safes, each guarded by multiple locks that no single thief can crack. This structure not only enhances security but also prevents manipulation. Imagine if social media algorithms could be altered behind the scenes to sway elections or public opinion—centralized AI makes that scarily possible. Cocoon counters this by decentralizing computation, ensuring transparency and user control.
Evidence from the blockchain world supports this shift. Developers in AI and blockchain have been buzzing about these privacy risks for years, pushing for solutions that avoid single points of control. By integrating with TON, Cocoon taps into a proven ecosystem that’s already powering fast, scalable transactions. TON’s association with Telegram means it has a massive user base ready to adopt such innovations, potentially accelerating the move toward decentralized AI.
And here’s where platforms like WEEX come into play, aligning perfectly with this ethos of decentralization and user empowerment. As a reliable crypto exchange, WEEX offers seamless trading of assets like Toncoin (TON), making it easier for users to get involved in projects like Cocoon. WEEX’s commitment to security and transparency mirrors the privacy-focused goals of decentralized AI, providing a trustworthy gateway for anyone looking to earn TON by contributing to the network. It’s this kind of brand alignment that strengthens the overall ecosystem, ensuring that innovations like Cocoon aren’t just theoretical but accessible to everyday users.
Exploring Real-World Implications and Latest Updates on Decentralized AI
As we approach the end of 2025, the conversation around decentralized AI has exploded. Based on the most frequently searched questions on Google—like “What is decentralized AI?” or “How does blockchain improve AI privacy?”—it’s clear people are hungry for alternatives to Big Tech’s grip. Queries such as “Benefits of TON blockchain for AI” and “How to earn Toncoin with GPUs” top the lists, reflecting a growing interest in practical ways to participate. These searches often lead to discussions on how decentralized systems can prevent data monopolies, with users seeking step-by-step guides that emphasize privacy without overwhelming technical jargon.
On Twitter, the buzz has been even more dynamic. Topics like #DecentralizedAI and #TONBlockchain have trended, with users debating the future of privacy in AI. Posts from influencers highlight Cocoon as a beacon for digital freedom, often contrasting it with centralized giants. For instance, a viral thread as of October 2025 discussed how Cocoon could revolutionize everyday AI use, from personalized assistants to content creation, all without data leaks. Official announcements from the TON foundation have amplified this, with a recent tweet on October 15, 2025, stating: “Cocoon is live on TON—join the network, contribute your GPU, and earn TON while protecting your privacy. #DecentralizedAI #TON.”
Latest updates as of October 31, 2025, include partnerships expanding Cocoon’s reach. Reports indicate integrations with various Web3 tools, allowing seamless AI queries on decentralized platforms. Twitter discussions have also touched on potential challenges, like scalability, but the consensus leans positive, with users praising how it aligns with broader movements for data sovereignty. One popular tweet from a blockchain analyst read: “Cocoon on TON is what we’ve been waiting for—AI without the surveillance. Time to decentralize everything! #PrivacyFirst.”
These developments aren’t isolated. Think of decentralized AI as the evolution of ride-sharing apps: Uber centralized it, but blockchain versions distribute control among users, cutting out the middleman. Cocoon applies this to AI, ensuring that as more people join, the network grows stronger, more resilient, and inherently fairer.
How Cocoon Fits into the Broader Blockchain and AI Landscape
Stepping back, Cocoon isn’t emerging in a vacuum. The intersection of blockchain and AI has been a hotbed of innovation, with projects tackling everything from secure data sharing to verifiable computations. TON’s design, with its focus on speed and low costs, makes it an ideal backbone for such endeavors. Users contributing to Cocoon aren’t just earning TON; they’re building a collective defense against the overreach of centralized powers.
Consider the emotional pull here—haven’t we all felt that unease when an app asks for unnecessary permissions? Durov tapped into that frustration, reminding us that convenience shouldn’t come at the cost of freedom. By choosing decentralized paths, we’re not just adopting new tech; we’re voting for a future where privacy is the default.
Platforms like WEEX enhance this narrative by providing robust tools for engaging with TON. Their user-friendly interfaces and strong security measures make it simple to trade TON or explore related assets, aligning with Cocoon’s mission to make decentralization accessible. This brand synergy underscores how exchanges can support innovative projects, fostering a community-driven approach to tech advancement.
Addressing Privacy Concerns Through Decentralized Innovation
Privacy isn’t just a buzzword in Cocoon’s world—it’s the foundation. Decentralized AI mitigates risks by distributing data across nodes, much like how a flock of birds navigates without a single leader. If one node falters, the system persists, unlike centralized setups where a single hack can topple everything. Real-world examples abound: past data scandals at tech firms have eroded trust, pushing users toward blockchain solutions.
As discussions evolve, it’s evident that Cocoon could set a precedent. Imagine AI tools that help with everything from medical advice to creative writing, all powered by a network you trust because you help run it. This participatory model, rewarded with TON, incentivizes growth while safeguarding against abuses.
In wrapping this up, Cocoon represents more than a new project—it’s a call to action for reclaiming our digital lives. By building on TON blockchain, it offers a practical path to decentralized AI that prioritizes privacy and freedom. As we navigate 2025 and beyond, innovations like this remind us that technology can empower rather than control, creating a more equitable online world.
FAQ
What is Cocoon and how does it work on the TON blockchain?
Cocoon is a decentralized AI network launched by Pavel Durov, built on the TON blockchain. It allows users to access AI tools by contributing GPU power, earning Toncoin (TON) in return, all while maintaining data privacy through decentralization.
Why is decentralized AI important for privacy?
Decentralized AI prevents centralized providers from controlling or breaching user data. It uses blockchain to create tamper-proof records, reducing risks like hacks and censorship compared to traditional systems.
How can users earn Toncoin through Cocoon?
Users can share their GPU processing power with the Cocoon network. In exchange, they receive Toncoin (TON), incentivizing participation in this decentralized AI ecosystem.
What are the risks of centralized AI according to experts?
Centralized AI can lead to data breaches, real-time manipulation of information, and loss of digital freedoms. Experts note that storing data in one place makes it vulnerable to hackers and potential misuse.
How does Cocoon align with broader blockchain trends?
Cocoon fits into trends emphasizing decentralization and privacy, using TON blockchain to enable secure, user-controlled AI. It addresses growing demands for alternatives to centralized tech, as seen in online searches and discussions.
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Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link
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