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Daniel Roberts✓

@danroberts0101

NASDAQ: IREN Co-Founder / Co-CEO Building AI cloud infrastructure at multi-GW scale

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  1. Daniel Roberts✓@danroberts0101
    A thread on where AI infrastructure is heading - and where IREN fits. 🧵
    Daniel Roberts @danroberts0101
    𝐓𝐡𝐫𝐞𝐞 𝐋𝐚𝐲𝐞𝐫𝐬. 𝐎𝐧𝐞 𝐂𝐨𝐦𝐩𝐨𝐮𝐧𝐝𝐢𝐧𝐠 𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞. 𝐓𝐡𝐞 𝐈𝐑𝐄𝐍 𝐓𝐡𝐞𝐬𝐢𝐬. There's been a lot happening at IREN recently. Expansion across North America, Europe and Asia-Pacific. The NVIDIA partnership. The Mirantis acquisition. New GPU deployments. New customer discussions. A growing global footprint. Underneath all of it is a fairly simple view of where the world is heading, and a deliberate strategy for how we position IREN within it. That strategy is built on three layers. Together, they compound into a structural advantage that gets harder to replicate every quarter we execute. Layer 1: Physical infrastructure. Power, land, substations, data centers, cooling. The foundation that everything else sits on. Layer 2: Compute infrastructure. The GPUs, servers and networking that go inside those buildings. Deployed at scale. Generating revenue. Building execution track record. Layer 3: Software and operational capability. The orchestration, deployment tooling and enterprise expertise that makes the first two layers work harder for customers, and opens the door to a broader, higher-value market over time. Layers 1 and 2 are where the overwhelming majority of IREN's value is being created today. Layer 3 is where that advantage compounds further over time, but only because Layers 1 and 2 are built, owned and controlled at scale by IREN, not subscale nor contracted from a third party. Think of Amazon. They didn't win e-commerce by building a great website. They won it by controlling the fulfilment infrastructure at a scale nobody else could replicate. The foundation you don't control becomes the ceiling on your business. That is exactly how we think about IREN. The physical infrastructure - the land, the power, the substations, the data centers - is owned and controlled by us. The compute deployed into it generates the revenue and execution track record. And the software, orchestration and enterprise capability we are more methodically building on top is what turns the total product into a vertically integrated AI Cloud platform that compounds over time and deepens into a competitive moat. AI is still early. The bottleneck is increasingly physical. And we have spent eight years building the foundations.
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  2. Daniel Roberts✓@danroberts0101
    𝐓𝐡𝐫𝐞𝐞 𝐋𝐚𝐲𝐞𝐫𝐬. 𝐎𝐧𝐞 𝐂𝐨𝐦𝐩𝐨𝐮𝐧𝐝𝐢𝐧𝐠 𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞. 𝐓𝐡𝐞 𝐈𝐑𝐄𝐍 𝐓𝐡𝐞𝐬𝐢𝐬. There's been a lot happening at IREN recently. Expansion across North America, Europe and Asia-Pacific. The NVIDIA partnership. The Mirantis acquisition. New GPU deployments. New customer discussions. A growing global footprint. Underneath all of it is a fairly simple view of where the world is heading, and a deliberate strategy for how we position IREN within it. That strategy is built on three layers. Together, they compound into a structural advantage that gets harder to replicate every quarter we execute. Layer 1: Physical infrastructure. Power, land, substations, data centers, cooling. The foundation that everything else sits on. Layer 2: Compute infrastructure. The GPUs, servers and networking that go inside those buildings. Deployed at scale. Generating revenue. Building execution track record. Layer 3: Software and operational capability. The orchestration, deployment tooling and enterprise expertise that makes the first two layers work harder for customers, and opens the door to a broader, higher-value market over time. Layers 1 and 2 are where the overwhelming majority of IREN's value is being created today. Layer 3 is where that advantage compounds further over time, but only because Layers 1 and 2 are built, owned and controlled at scale by IREN, not subscale nor contracted from a third party. Think of Amazon. They didn't win e-commerce by building a great website. They won it by controlling the fulfilment infrastructure at a scale nobody else could replicate. The foundation you don't control becomes the ceiling on your business. That is exactly how we think about IREN. The physical infrastructure - the land, the power, the substations, the data centers - is owned and controlled by us. The compute deployed into it generates the revenue and execution track record. And the software, orchestration and enterprise capability we are more methodically building on top is what turns the total product into a vertically integrated AI Cloud platform that compounds over time and deepens into a competitive moat. AI is still early. The bottleneck is increasingly physical. And we have spent eight years building the foundations.
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  3. Daniel Roberts✓@danroberts0101
    A lot of questions this week on funding, so here's how a GPU typically gets funded at $IREN. First, the customer signs a multi-year take-or-pay contract and agrees to a prepayment. On our recent 3-year contracts, prepayments have been 45% to 55% of the associated GPU capex. Second, financing is committed, secured by the contracted GPUs. On the Microsoft contract we secured an A-rated facility at around 6%, which together with prepayments covers 96% of GPU capex. More recently, for a non-investment grade counterparty at Mackenzie, we secured financing at 9% fixed, which together with prepayments covers more than the full cost of the GPUs. That's the GPU side. The data centers are a separate, long-term asset base, and we own the ones our GPUs run in. Construction has been funded from cash to date, with no debt against these multi-billion dollar assets. As they come online with contracted customers, they can support financing in their own right. The processes behind the next facilities are continuing, and new paper will cost what the market charges. With GPU paybacks of around two years on our recent 3-year contracts, a wider spread barely moves the economics. There's more customer demand than we can build for. As we noted at our recent earnings, 2026 is largely sold out, recent 3-year contracts are at more than double the prior year's pricing, and demand for anything we can bring online in 2027 covers it several times over, with prepayments a focus in every negotiation. Conversations on 2028 capacity are already underway. Meanwhile announced capacity keeps slipping across the industry, which is the point: signing deals isn't the bottleneck in this market, bringing GPUs online is, and that's our focus.
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  4. Daniel Roberts✓@danroberts0101
    A few people asked over the weekend what the calls to slow the pace of frontier AI mean for the buildout. Some thoughts: Even if models never improved from here, just rolling out what they can already do would take more compute than the world can build for years. The debate about how fast AI should be allowed to improve is a fair one to have. It's about future generations of models. Existing demand is the part I think people are misreading. Anthropic CEO Dario Amodei said in May they'd planned for 10x growth and were running at an 80x pace in the first quarter, and that's why they've had trouble supplying compute. OpenAI president Greg Brockman said in July they'll be in a compute shortage no matter what, and are choosing which products to scale. Google says it's processing 7x the tokens it did a year ago. Hundreds of millions of people use these models today, and most of them use a small part of what the models can already do. And every time more compute comes online, usage steps up again: limits come off for people already using it, customers who were turned away get on, and new use cases show up that weren't in anyone's plan. Now supply. The constraint is HBM, the memory that sits inside every major AI chip. Three companies make it and all three are sold out this year. A new memory plant takes years to build. TrendForce has HBM shipments growing 50-60% next year. NVIDIA, the biggest buyer of it, expects its revenue to grow about 70% next year and calls that outlook 'supply-constrained', noting its customers' forecasts point closer to 100%. On our own bottom-up work, the memory constraint lands in about the same place as NVIDIA's growth number. Then the chips need a building with power connected, which takes longer again. Goldmans reckons only about half the US capacity scheduled over the next two years will actually be built on time. The risk to demand continues to seem heavily weighted to the upside. The risk to supply continues to seem weighted toward less capacity getting built, not more.
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  5. Daniel Roberts✓@danroberts0101
    Goldman's CommTech conference, San Francisco. 48 hours of @IREN_Ltd investor meetings, and the mood has shifted meaningfully. Key takeaways:
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  6. Daniel Roberts✓@danroberts0101
    Posts @danroberts0101
    8. The enterprise wave is the one to watch (and really excites us internally). Enterprise AI needs virtualization, security, compliance and real support. Early conversations are starting. When that demand hits, software and services on the same MWs can expand margins materially.
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  7. Daniel Roberts✓@danroberts0101
    Posts @danroberts0101
    9. The next 12-18 months are all about execution, and the delay chatter was constant. 3 sites commissioning between now and year end, 4,000+ people on the ground. We're in the spotlight, and it's delivery time.
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  8. Daniel Roberts✓@danroberts0101
    A few people have Thursday's numbers tangled, so let me untangle them. The majority of the $684m loss is the cost of retiring Bitcoin miners as we convert those sites to AI Cloud. Non-cash. The cloud business underneath ran ~87% gross margins (ex D&A). Every megawatt that comes off mining goes back on at multiples of the revenue. Recent 3-year AI Cloud contracts are at >$20m per MW (IT), more than double late last year. And the $25-30bn of forecasted FY27 capex isn't an equity number. Customer prepayments can cover about half the GPU capex. Lenders can fund most of the rest. We raised ~$19bn over the last twelve months and only ~$3bn of it was equity. We haven't borrowed a dollar against the data centers yet either. $4bn of ARR is contracted, with three sites commissioning between now and year end to bring it online. And that's the 2026 story. The real ramp is 2027, when Sweetwater and the next wave of capacity come into play. It's delivery time.
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  9. Daniel Roberts✓@danroberts0101
    The constraint in this industry is delivery, not demand. 4,000+ people on sites across three continents, bringing compute online.
    IREN @IREN_Ltd
    Execution at scale. From Childress and Sweetwater in Texas to Mackenzie, Prince George and Canal Flats in British Columbia. IREN is building across multiple campuses simultaneously, with development advancing at Kiowa (Oklahoma), Bundey (Australia) and Badajoz (Spain). Over 4,000 personnel. Millions of work-hours completed to date. Building at speed and scale. That is the advantage of IREN's vertically integrated model.
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  10. IREN✓@IREN_Ltd
    Execution at scale. From Childress and Sweetwater in Texas to Mackenzie, Prince George and Canal Flats in British Columbia. IREN is building across multiple campuses simultaneously, with development advancing at Kiowa (Oklahoma), Bundey (Australia) and Badajoz (Spain). Over 4,000 personnel. Millions of work-hours completed to date. Building at speed and scale. That is the advantage of IREN's vertically integrated model.
    Download
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  11. Daniel Roberts✓@danroberts0101
    Every new AI data center creates more demand for AI, not less. That's what people referring to past booms keep getting wrong about this one. Better AI needs more computing power to run. Cheaper AI gets used more, not less. And every step change in capability creates use cases that didn't exist a year ago. Demand grows at the speed of software, but supply cannot. Supply grows at the speed of the real world: power connections, transmission lines, concrete, steel, and the thousands of people it takes to build. In past booms, technology helped supply catch up. This time, technology is on the other side of the equation. It's fueling exponential demand, and the real world can't build fast enough to keep up.
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  12. Daniel Roberts✓@danroberts0101
    Nine months ago we signed a contract. Today Microsoft has accepted delivery of Horizon 1: 50MW of direct-to-chip liquid cooled AI infrastructure, built, commissioned and handed over. A greenfield build of this scale typically takes 2-3 years. Owning the land, the power, the substations and every workstream in between is how you compress that. Proud of the 3,000+ people on site who make it happen. Three more Horizons to go this year.
    IREN @IREN_Ltd
    Horizon 1: delivered. IREN has delivered Horizon 1 to Microsoft and achieved NVIDIA Exemplar Cloud status on NVIDIA GB300 NVL72. Read more:
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  13. IREN✓@IREN_Ltd
    Horizon 1: delivered. IREN has delivered Horizon 1 to Microsoft and achieved NVIDIA Exemplar Cloud status on NVIDIA GB300 NVL72. Read more:
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  14. Daniel Roberts✓@danroberts0101
    Daniel Roberts
    RT @IREN_Ltd: Texas is asking the right questions about data center growth: how to ensure Texans reap the benefits while protecting their natural resources. At IREN, that has been our approach from day one. Read more from @danroberts0101:
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  15. Daniel Roberts✓@danroberts0101
    Data centers. Compute. Software. Under one roof. Three layers. One compounding advantage. Yesterday, we closed the acquisition of Mirantis, strengthening layer three with a team that has spent over a decade building and operating cloud infrastructure for 1,500+ enterprises globally.
    IREN @IREN_Ltd
    AI builders rely on a cloud that moves at their pace. Today, IREN takes another step forward with the completion of our acquisition of Mirantis. By bringing together IREN’s owned and operated data centers and compute with Mirantis’ flexible, interoperable software layer, we’re giving customers greater choice and control in how they deploy and scale AI workloads. Developers and enterprises want flexibility as the AI landscape evolves. We're building an open foundation that grows with you, so you’re ready for what's next. Read more:
    1221451.7K139K
  16. IREN✓@IREN_Ltd
    AI builders rely on a cloud that moves at their pace. Today, IREN takes another step forward with the completion of our acquisition of Mirantis. By bringing together IREN’s owned and operated data centers and compute with Mirantis’ flexible, interoperable software layer, we’re giving customers greater choice and control in how they deploy and scale AI workloads. Developers and enterprises want flexibility as the AI landscape evolves. We're building an open foundation that grows with you, so you’re ready for what's next. Read more:
    Download
    591641.5K283K
  17. Daniel Roberts✓@danroberts0101
    8 years ago Will and I started accumulating powered land because we thought compute would eat the world. Some weeks the market agrees with us more than others. What we know today: demand for our capacity exceeds everything we can build, 85% of our $4bn+ 2026 target is signed, and there are thousands of people on our sites right now pouring concrete and racking GPUs. We've been through way worse than this. Back to it.
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  18. Daniel Roberts✓@danroberts0101
    One of the most common questions we get about AI data centers is how much water do they use? Fair question. Older designs cooled servers by evaporating water and people naturally assume ours do too. They don't. $IREN's sites are different. Direct-to-chip liquid cooling in a closed loop. Same idea as a car radiator or a fridge. Fill it once and the water just goes round and round. Over the life of a 200MW site, the initial fill plus every top-up averages out to about as much water each year as 3 households. Not a town. Not a suburb. Not a street... 3 houses. Water matters in the regions we build in. Which is precisely why our cooling barely uses any.
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