Conference Presentation, Other
The Real Edge in Production AI | Retainna Lin, Bitdeer AI | RAISE Summit 2026
- Industry Shift in AI Infrastructure Strategy: The transcript highlights a strategic pivot where leading AI companies (e.g., OpenAI, Anthropic) are transitioning from renting cloud compute to investing billions in building proprietary infrastructure to control the full stack.
- Driver for Capital Expenditure: This shift is driven by the evolution from "making AI work" (capability) to "making AI pay" (economic viability, reliability at scale, and P&L value).
- The "Cost Per Outcome" Metric: Current market pricing based on GPU hours is misaligned with business reality; success is determined by the total cost per outcome across the entire path (power, chips, cloud, workflow, deployment).
- Value Leakage Point: In a stitched multi-vendor stack, value leaks at the seams between layers, where no single provider is accountable for the integrated cost economy.
- Three Primary Pressures on AI-Native Companies:
- Inference is the core business, making cost per outcome the direct determinant of gross margin.
- Scaling requires scarce resources (power, compute, low latency), creating supply bottlenecks.
- Enterprise and sovereign demands impose strict data residency, compliance, and security constraints.
- Three Strategic Options for Infrastructure:
- Option 1 (Build): Own power, land, and facilities; requires billions in CapEx, years of execution, and transforms the company into a data center operator.
- Option 2 (Stitch): Aggregate disparate vendors; flexible but results in cumulative costs at every handoff and lacks integrated accountability.
- Option 3 (Partner): Utilize a partner owning the full path (power to result); offers asset-light economics with full control over the four key levers: CapEx, compute, residency, and latency.
- Bitdeer AI Capability Profile:
- Positioning: An NVIDIA preferred partner in Southeast Asia with operations in APAC, Norway, and North America.
- Capacity: Holds 3 gigawatts of power capacity across its global footprint.
- Service Stack: Provides secure power/land (AI Data Center), on-demand/subscribed GPU compute (AI Cloud), and a serverless model studio (Agent Platform).
- Forward-Looking Statement on Competitive Advantage: Winners in the production AI era will not be those owning the most infrastructure, but those controlling the cost per outcome to reflect value in their P&L.
- Due Diligence Recommendation: Organizations evaluating infrastructure partners must explicitly ask if the provider owns the power/land and the data center center, as missing ownership of any layer introduces hidden costs.
- Market Data on AI Adoption:
- McKinsey reports 88% of businesses now use AI in at least one function.
- Enterprise GenAI spending rose to $37 billion (from $11.5 billion), with 67% allocated to use cases rather than infrastructure.
- SWE-Bench verified AI capabilities increased from 65% to nearly 100% in resolving real software issues within one year.
- Agents in the OS world usage grew from 12% to 66% over a similar period.