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The GENIUS Act shows us what happens when lawmakers use a scalpel, not a Swiss Army knife. Its reserve and redemption rules could enable AI agents to transact on crypto rails. I dive into both GENIUS and CLARITY acts in my Crowdfund Insider interview. crowdfundinsider.com/2025/07/244870…

I am honored to step into the role of CEO for io.net, effective immediately. Under @shadid_io 's leadership, io.net has grown into one of the fastest growing AI companies in the world. Going forward, we will continue to execute on the vision that Ahmad set forth when he founded io.net - to become the world’s largest AI compute network and bring AI to the world. As of today, the network has onboarded approximately 20K cluster-ready GPUs and is serving end-to-end AI inference and model training workloads across AI companies like WonderAI, Krea and Leonardo. For the last 6 months, I have worked closely with Ahmad, the io.net team, and our incredible roster of backers to streamline the day to day operations of io.net as the COO. io.net’s operations have been transitioned to the leadership team under my oversight and we will be sharing the full scope of io.net leadership team changes over the coming days. What’s next? We are excited to launch $IO on June 11th at 12:00 UTC and to continue accelerating io.net’s growth post launch. The launch of the token ushers in a new phase of growth for the network. We remain unwavering in our mission to build the world’s largest decentralized AI compute network and expect to focus heavily on acquiring and retaining suppliers and onboarding new customers. AI compute spend is on track to be on the order of $100B in 2024, and yet there remain significant and structural gaps in access to existing resources. io.net’s vision is a world where AI products of the coming decade are built on open, permissionless platforms that are accessible to all. We're excited to continue building the internet of GPUs. I want to thank the community, our partners, our investors, and the io.net team for supporting the project as we start this next chapter in the company’s journey.

It’s been a big year for @ionet We built a global network of GPUs, raised over $40M from top tier investors, and launched our $IO token So what’s next? Read below to see exactly how we plan to disrupt the $2.5 Trillion Cloud and help usher in a new age of AI: 👇

A new $200 trillion economy is emerging right now—bigger, faster, and more transformative than anything we’ve ever seen. The technology driving this isn’t just another innovation. It’s not like the internet, mobile, or social media. It’s something bigger. AI isn’t just technology—it’s becoming the very fabric of our global economy. AI will become the operating system for every market, every industry, every decision we make. But there’s a problem. AI doesn’t just run code—it thinks. And thinking takes enormous power, massive scale, and unprecedented infrastructure. The current cloud wasn’t designed for that. And you can already see it breaking: •Scale: By 2030, GPU production will barely meet half of the world’s AI compute needs. •Reliability: From 2022 to 2024, cloud outages doubled. Infrastructure is already showing it can’t support the demands of AI. •Access: Right now, 96% of major AI models are controlled by just a few large corporations, restricting innovation, limiting access, slowing down progress. •Control: A researcher tested ChatGPT in 15 different political scenarios—14 of those showed hidden ideological biases. If centralized corporations own the AI, they also own the ideas. •Cost: Compute costs have doubled from 24% to 50% of revenues in just one year. Innovation can't survive if infrastructure eats half your margin. AWS was built for software. Azure was built for applications. Google Cloud was built for search. They’re powerful—but they were never built to handle trillions of autonomous agents, real-time cognition, or a global-scale intelligence system. Centralized AI isn’t humanity’s future—it’s our biggest risk. People won’t see the danger clearly until the rails are already locked down—closed off, controlled, and bottlenecked. That’s the nature of these things. By the time you notice the risk, it’s usually too late. Decentralized AI isn’t just another tech trend. It’s the infrastructure we need for what’s coming next. Look at what decentralized AI can already do: •Scale instantly: @ionet expanded GPU access to 138 countries in under a year. @AethirCloud has activated 400K GPUs. @Filecoin onboarded over 2 EiB of data without breaking a sweat. •Resilience: @akashnet_ has maintained over 99.99% uptime since launch in 2021. Decentralized systems simply don’t go down. •Openness: Anyone, anywhere can deploy GPU clusters on io.net in 90 seconds—not days or weeks. •Freedom: When Turkey banned Wikipedia, a decentralized network instantly restored it. Decentralized AI is impossible to censor. •Cost: Decentralized networks offer GPU compute at 90% lower costs compared to AWS or Google Cloud. @rendernetwork already delivers GPU rendering at costs up to 80% lower than traditional clouds. Dramatic cost reductions change everything. Built specifically for AI. Engineered explicitly for scale. Open by default. Decentralized AI is the only architecture designed to handle this wave. Crypto wasn’t created to speculate on coins. It was made for exactly moments like this: To keep infrastructure open. To stop power from centralizing. To give us a chance to own our future, before someone else does. If you see clearly what’s coming, you know that right now we don’t need more apps. We need infrastructure. Don’t wait. Build the rails.

$IO Nation – I believe in “building in public”. So going forward, @ionet is going to start sharing detailed monthly reports on our progress, giving you a peak behind the curtain of what we’re doing. This is the first one… 👇 🧵

The robots are here. Are we ready for a world where machines pay machines? ➢ We're on the cusp of the sixth wave of innovation: embodied AI. Not the cute robots that vacuum your floor or the industrial arms welded to factory floors, but the science fiction vision we've envisioned since the 1960s – general-purpose humanoids that will fundamentally reshape our economy. The numbers are staggering: a projected global labor shortfall of 85 million workers, creating an $8.5 trillion hole in future GDP. The solution isn't more software or productivity hacks. It's intelligence poured into steel and silicon – a new form of labor that works 22 hours a day, never unionizes, and whose marginal cost trends toward zero. That's a $42 trillion addressable market. Let that sink in. The players are lining up: @Apptronik, @Figure, and a legion of others racing to build the Model T of humanoids. Techno-optimists paint a utopian future of abundance. Doomers envision masses of economically redundant humans subsisting on UBI. Both sides are missing something critical. The real story isn't the robots themselves. It's the orchestration layer. The silent, invisible financial and logistical nervous system that will allow billions of these autonomous agents to function in a coordinated economy. And that system will not be built on legacy banking rails or corporate silos. It'll be built on crypto... not because it should be, but because it has to be. This isn't a bullish prediction. It's an inevitability – a collision of necessity and technological capability. The scaling of general-purpose robots faces five fundamental problems that traditional tech stacks simply can't solve: ➢ 1) The Machine-to-Machine (M2M) Economy Problem When you have a billion robots performing micro-tasks – hauling boxes, scanning shelves, frying eggs – you need a payment system that can handle billions of microtransactions with finality and near-zero fees. Visa can't do this. SWIFT can't do this. Traditional banking infrastructure would collapse under this load. Stablecoins on a high-throughput blockchain can handle this with ease. This isn't a nice-to-have feature; it's a non-negotiable prerequisite for a frictionless economy of things. Imagine a delivery robot that needs to pay a charging station $0.0023 for a quick top-up, then pays a traffic optimization DAO $0.0015 for priority routing information. All of this happens in seconds, with no human intervention, at a cost that rounds to zero. The legacy financial system would drown in the overhead of these transactions. ➢ 2) The Verifiable Truth Problem Did the delivery robot actually leave the package at the correct GPS coordinate? Did the manufacturing bot complete its quality assurance scan properly? For robots to trust each other and for humans to trust robots, we need cryptographically signed, tamper-proof proofs of work, location, and identity. A centralized database owned by Amazon or Google represents a single point of failure and a target for manipulation. A decentralized ledger provides a source of verifiable truth that no single entity controls. Projects like @openmind_agi's FABRIC and @AukiNetwork's Posemesh aren't building gimmicky features – they're building the fundamental trust layer for physical automation. When your life depends on a robot surgeon not glitching out, you'll want that surgical procedure logged on an immutable ledger, not in some hospital's SQL database that can be edited retroactively. ➢ 3) The Data Famine Problem The current bottleneck in robotics isn't hardware or even algorithms – it's a lack of diverse training data. A robot trained to make coffee in a San Francisco startup's kitchen will short-circuit in a dimly lit Tokyo cafe. We need a global, incentivized network to gather this data. Crypto is the only vehicle that can efficiently coordinate and pay a global army of data contributors with stablecoins, bypassing forex complications and legacy payment bottlenecks. @silencioNetwork and @OVRtheReality represent early examples – decentralized physical infrastructure networks (DePINs) that pay humans to feed sensory data to machines, building the dataset for the robot uprising one microtask at a time. ➢ 4) The Capital Formation Problem A high-quality humanoid robot costs around $50,000 today. Scaling to millions of units requires capital on a scale that makes even venture capitalists nervous. Crypto enables fractional ownership and leasing models via tokenization. You won't "buy" a Tesla Optimus; you'll buy a slice of a robot fleet DAO that generates yield from its labor, democratizing access and solving the funding gap in one move. This is capital finding its most efficient use – the purest expression of what crypto was designed to enable. ➢ 5) The Silo Problem The world does not need ten competing, walled-garden robot ecosystems that can't talk to each other. We need a neutral, decentralized protocol for communication and settlement - an HTTP or TCP/IP for physical labor. This will not be built by a corporation; it will be built as a public good on a blockchain, exactly as OpenMind, Codec, and others are attempting. The market will demand it. Skeptics will scoff. They'll point to the current crypto robotics market cap of $250 million and call it peanuts. They're right. But they're also blind. This is the seed of the system that will run the world. This is the plumbing. The story of the next decade isn't just about who builds the best robot arm; it's about who builds the financial and operational layer upon which all robotic labor transacts. The system's response is to create a new asset class: robotic labor, owned by capital and coordinated by crypto. It is the most profound transfer of economic agency in human history. It won't be gradual. It will be a step-function change in how labor is organized, compensated, and deployed. The horses never saw the car coming. The question is whether we, hurtling toward our own obsolescence, will see the blockchain that powers it.

I am honored to step into the role of CEO for io.net, effective immediately. Under @shadid_io 's leadership, io.net has grown into one of the fastest growing AI companies in the world. Going forward, we will continue to execute on the vision that Ahmad set forth when he founded io.net - to become the world’s largest AI compute network and bring AI to the world. As of today, the network has onboarded approximately 20K cluster-ready GPUs and is serving end-to-end AI inference and model training workloads across AI companies like WonderAI, Krea and Leonardo. For the last 6 months, I have worked closely with Ahmad, the io.net team, and our incredible roster of backers to streamline the day to day operations of io.net as the COO. io.net’s operations have been transitioned to the leadership team under my oversight and we will be sharing the full scope of io.net leadership team changes over the coming days. What’s next? We are excited to launch $IO on June 11th at 12:00 UTC and to continue accelerating io.net’s growth post launch. The launch of the token ushers in a new phase of growth for the network. We remain unwavering in our mission to build the world’s largest decentralized AI compute network and expect to focus heavily on acquiring and retaining suppliers and onboarding new customers. AI compute spend is on track to be on the order of $100B in 2024, and yet there remain significant and structural gaps in access to existing resources. io.net’s vision is a world where AI products of the coming decade are built on open, permissionless platforms that are accessible to all. We're excited to continue building the internet of GPUs. I want to thank the community, our partners, our investors, and the io.net team for supporting the project as we start this next chapter in the company’s journey.

It’s been a big year for @ionet We built a global network of GPUs, raised over $40M from top tier investors, and launched our $IO token So what’s next? Read below to see exactly how we plan to disrupt the $2.5 Trillion Cloud and help usher in a new age of AI: 👇

A new $200 trillion economy is emerging right now—bigger, faster, and more transformative than anything we’ve ever seen. The technology driving this isn’t just another innovation. It’s not like the internet, mobile, or social media. It’s something bigger. AI isn’t just technology—it’s becoming the very fabric of our global economy. AI will become the operating system for every market, every industry, every decision we make. But there’s a problem. AI doesn’t just run code—it thinks. And thinking takes enormous power, massive scale, and unprecedented infrastructure. The current cloud wasn’t designed for that. And you can already see it breaking: •Scale: By 2030, GPU production will barely meet half of the world’s AI compute needs. •Reliability: From 2022 to 2024, cloud outages doubled. Infrastructure is already showing it can’t support the demands of AI. •Access: Right now, 96% of major AI models are controlled by just a few large corporations, restricting innovation, limiting access, slowing down progress. •Control: A researcher tested ChatGPT in 15 different political scenarios—14 of those showed hidden ideological biases. If centralized corporations own the AI, they also own the ideas. •Cost: Compute costs have doubled from 24% to 50% of revenues in just one year. Innovation can't survive if infrastructure eats half your margin. AWS was built for software. Azure was built for applications. Google Cloud was built for search. They’re powerful—but they were never built to handle trillions of autonomous agents, real-time cognition, or a global-scale intelligence system. Centralized AI isn’t humanity’s future—it’s our biggest risk. People won’t see the danger clearly until the rails are already locked down—closed off, controlled, and bottlenecked. That’s the nature of these things. By the time you notice the risk, it’s usually too late. Decentralized AI isn’t just another tech trend. It’s the infrastructure we need for what’s coming next. Look at what decentralized AI can already do: •Scale instantly: @ionet expanded GPU access to 138 countries in under a year. @AethirCloud has activated 400K GPUs. @Filecoin onboarded over 2 EiB of data without breaking a sweat. •Resilience: @akashnet_ has maintained over 99.99% uptime since launch in 2021. Decentralized systems simply don’t go down. •Openness: Anyone, anywhere can deploy GPU clusters on io.net in 90 seconds—not days or weeks. •Freedom: When Turkey banned Wikipedia, a decentralized network instantly restored it. Decentralized AI is impossible to censor. •Cost: Decentralized networks offer GPU compute at 90% lower costs compared to AWS or Google Cloud. @rendernetwork already delivers GPU rendering at costs up to 80% lower than traditional clouds. Dramatic cost reductions change everything. Built specifically for AI. Engineered explicitly for scale. Open by default. Decentralized AI is the only architecture designed to handle this wave. Crypto wasn’t created to speculate on coins. It was made for exactly moments like this: To keep infrastructure open. To stop power from centralizing. To give us a chance to own our future, before someone else does. If you see clearly what’s coming, you know that right now we don’t need more apps. We need infrastructure. Don’t wait. Build the rails.

$IO Nation – I believe in “building in public”. So going forward, @ionet is going to start sharing detailed monthly reports on our progress, giving you a peak behind the curtain of what we’re doing. This is the first one… 👇 🧵

The GENIUS Act shows us what happens when lawmakers use a scalpel, not a Swiss Army knife. Its reserve and redemption rules could enable AI agents to transact on crypto rails. I dive into both GENIUS and CLARITY acts in my Crowdfund Insider interview. crowdfundinsider.com/2025/07/244870…

The robots are here. Are we ready for a world where machines pay machines? ➢ We're on the cusp of the sixth wave of innovation: embodied AI. Not the cute robots that vacuum your floor or the industrial arms welded to factory floors, but the science fiction vision we've envisioned since the 1960s – general-purpose humanoids that will fundamentally reshape our economy. The numbers are staggering: a projected global labor shortfall of 85 million workers, creating an $8.5 trillion hole in future GDP. The solution isn't more software or productivity hacks. It's intelligence poured into steel and silicon – a new form of labor that works 22 hours a day, never unionizes, and whose marginal cost trends toward zero. That's a $42 trillion addressable market. Let that sink in. The players are lining up: @Apptronik, @Figure, and a legion of others racing to build the Model T of humanoids. Techno-optimists paint a utopian future of abundance. Doomers envision masses of economically redundant humans subsisting on UBI. Both sides are missing something critical. The real story isn't the robots themselves. It's the orchestration layer. The silent, invisible financial and logistical nervous system that will allow billions of these autonomous agents to function in a coordinated economy. And that system will not be built on legacy banking rails or corporate silos. It'll be built on crypto... not because it should be, but because it has to be. This isn't a bullish prediction. It's an inevitability – a collision of necessity and technological capability. The scaling of general-purpose robots faces five fundamental problems that traditional tech stacks simply can't solve: ➢ 1) The Machine-to-Machine (M2M) Economy Problem When you have a billion robots performing micro-tasks – hauling boxes, scanning shelves, frying eggs – you need a payment system that can handle billions of microtransactions with finality and near-zero fees. Visa can't do this. SWIFT can't do this. Traditional banking infrastructure would collapse under this load. Stablecoins on a high-throughput blockchain can handle this with ease. This isn't a nice-to-have feature; it's a non-negotiable prerequisite for a frictionless economy of things. Imagine a delivery robot that needs to pay a charging station $0.0023 for a quick top-up, then pays a traffic optimization DAO $0.0015 for priority routing information. All of this happens in seconds, with no human intervention, at a cost that rounds to zero. The legacy financial system would drown in the overhead of these transactions. ➢ 2) The Verifiable Truth Problem Did the delivery robot actually leave the package at the correct GPS coordinate? Did the manufacturing bot complete its quality assurance scan properly? For robots to trust each other and for humans to trust robots, we need cryptographically signed, tamper-proof proofs of work, location, and identity. A centralized database owned by Amazon or Google represents a single point of failure and a target for manipulation. A decentralized ledger provides a source of verifiable truth that no single entity controls. Projects like @openmind_agi's FABRIC and @AukiNetwork's Posemesh aren't building gimmicky features – they're building the fundamental trust layer for physical automation. When your life depends on a robot surgeon not glitching out, you'll want that surgical procedure logged on an immutable ledger, not in some hospital's SQL database that can be edited retroactively. ➢ 3) The Data Famine Problem The current bottleneck in robotics isn't hardware or even algorithms – it's a lack of diverse training data. A robot trained to make coffee in a San Francisco startup's kitchen will short-circuit in a dimly lit Tokyo cafe. We need a global, incentivized network to gather this data. Crypto is the only vehicle that can efficiently coordinate and pay a global army of data contributors with stablecoins, bypassing forex complications and legacy payment bottlenecks. @silencioNetwork and @OVRtheReality represent early examples – decentralized physical infrastructure networks (DePINs) that pay humans to feed sensory data to machines, building the dataset for the robot uprising one microtask at a time. ➢ 4) The Capital Formation Problem A high-quality humanoid robot costs around $50,000 today. Scaling to millions of units requires capital on a scale that makes even venture capitalists nervous. Crypto enables fractional ownership and leasing models via tokenization. You won't "buy" a Tesla Optimus; you'll buy a slice of a robot fleet DAO that generates yield from its labor, democratizing access and solving the funding gap in one move. This is capital finding its most efficient use – the purest expression of what crypto was designed to enable. ➢ 5) The Silo Problem The world does not need ten competing, walled-garden robot ecosystems that can't talk to each other. We need a neutral, decentralized protocol for communication and settlement - an HTTP or TCP/IP for physical labor. This will not be built by a corporation; it will be built as a public good on a blockchain, exactly as OpenMind, Codec, and others are attempting. The market will demand it. Skeptics will scoff. They'll point to the current crypto robotics market cap of $250 million and call it peanuts. They're right. But they're also blind. This is the seed of the system that will run the world. This is the plumbing. The story of the next decade isn't just about who builds the best robot arm; it's about who builds the financial and operational layer upon which all robotic labor transacts. The system's response is to create a new asset class: robotic labor, owned by capital and coordinated by crypto. It is the most profound transfer of economic agency in human history. It won't be gradual. It will be a step-function change in how labor is organized, compensated, and deployed. The horses never saw the car coming. The question is whether we, hurtling toward our own obsolescence, will see the blockchain that powers it.

I have a new piece out at @beincrypto. Centralized AI is the choke point. Three clouds set prices, rules, and the mute button. DeAI is the alternative → permissionless models, compute, and data so anyone can build. beincrypto.com/decentralizati…