
Spotlight on Compute: From Bitcoin Mines to AI Megacenters
2025.12.03
Bitdeer CEO Jihan Wu joined the Bloomberg New Economy 2025 program in Singapore on Nov 21 for a focused discussion on how mining infrastructure, chip design, and data center development can accelerate the next wave of AI capacity.
Bitdeer CEO Jihan Wu joined the Bloomberg New Economy 2025 program in Singapore on Nov 21 for a focused discussion on how mining infrastructure, chip design, and data center development can accelerate the next wave of AI capacity. In this 20-minute session, “Spotlight on Compute: From bitcoin Mines to AI Megacenters”, Jihan outlined Bitdeer’s approach to dual-use sites, the SEAL chip roadmap, and how vertical integration across power, silicon, and operations can shorten time to value for AI while supporting efficient bitcoin mining. A lightly edited transcript follows.
Why mining infrastructure matters for AI
Shery Ahn: How will we power the AI revolution, and how does Bitdeer connect mining, hardware, and AI infrastructure?
Jihan Wu: Bitdeer designs its own bitcoin mining chips and manufactures mining machines. We operate across the full mining value chain. A key advantage is our large power development pipeline, with substantial capacity in the United States that can be converted to AI data centers over time. Mining has already built the hard parts of infrastructure — transmission, substations, permits, construction, and skilled labor — that AI requires. Using existing sites can shorten timelines for AI deployments compared with starting from scratch.
Timelines and dual-use sites
Shery: How quickly can facilities be converted?
Jihan: The fastest conversions can be completed in about a year, with others taking two to three years depending on permits, interconnects, and build scope. Our approach is to design sites as dual-use where practical. We may initially mine bitcoin at high efficiency, then convert all or part of the capacity to AI as contracts and timelines align. This creates flexibility while infrastructure and demand scale.
Power strategy and vertical integration
Shery: Will Bitdeer add self-generation instead of relying fully on utilities?
Jihan: North America needs more generation and transmission. Vertical models that link power development and compute demand in one platform can be effective. We focus on sites with competitive resources and clear pathways to profitable utilization. Mining provides a dependable offtake while AI demand ramps, which supports investor confidence in new generation and grid upgrades.
Why continue bitcoin mining
Shery: Why keep mining if AI is the next growth curve?
Jihan: We have mined since 2012 and believe in bitcoin’s long-term role. Mining at best-in-class efficiency supports cash flow, validates our hardware in production, and de-risks large power investments while AI demand and timelines are still forming. Mining is a practical hedge that helps partners commit to heavy capital projects with confidence that capacity will be used.
Manufacturing, supply chains, and resilience
Shery: How are you managing geopolitical risk and manufacturing?
Jihan: We adapt to the current supply-chain landscape by aligning design and manufacturing with resilient partners and regions. We are also building manufacturing capabilities in the United States that emphasize automation. The goal is to improve reliability, lead times, and learning cycles for our mining systems, while preparing for future U.S. production of machines.
R&D focus and efficiency ambitions
Shery: What are you pursuing in chip R&D?
Jihan: We are advancing our SEAL chip roadmap for mining and exploring innovations that could materially reduce power usage for compute-intensive chips. Some of this work involves new circuit families and internal EDA code. If successful, the techniques could be broadly useful to high-performance compute. These are active R&D efforts and timelines are subject to development progress.
The path ahead
Bitdeer’s strategy links proven mining operations with staged AI readiness. By developing power-rich, dual-use sites, validating hardware in production, and investing in chip and systems R&D, we aim to shorten time to value for AI infrastructure while maintaining discipline through cycles.
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