Inference has become dominant #AI computing demand
The current AI compute demand is undergoing a structural shift from training to inference
According to multiple industry studies, inference workloads have become the primary consumer of AI compute:

Inference share continues to rise:
Multiple sources indicate that inference now accounts for 80% to 90% of AI computing resources.
Gartner predicts that by 2026, 55% of AI-optimized IaaS spending will be used to support inference workloads, and this will exceed 65% by 2029.
Deloitte predicts that inference will account for two-thirds of all AI computing by 2026, up from one-third in 2023 and half in 2025.

Inference costs dominate in the long run:
According to industry reports, inference can account for 80% to 90% of the lifecycle costs of production AI systems.
Training is a sporadic investment when models are updated, while inference generates ongoing costs—each prediction consumes compute and electricity.

Inference profits are substantial:
A report by Morgan Stanley shows that AI inference factories benchmarked at 100 megawatts of power generally have average profit margins exceeding 50%, making them a profit hub that tech giants are racing to capture.


Data centers prioritize inference workloads; storage is under pressure
Against this backdrop, #data center operators are prioritizing resource allocation to high-profit inference workloads rather than traditional storage capacity.
Microsoft’s CFO has already warned that Azure’s capacity constraints will run through the entire 2026 fiscal year, even as capital expenditures continue to rise.
Microsoft CEO Satya Nadella has clearly stated that electricity is the key limiting factor. The company holds a large number of GPUs that remain unpowered due to lack of electricity.


Filecoin’s differentiated positioning: #Archived data layer
Unlike the centralized data centers above that prioritize inference workloads, Filecoin focuses on the #decentralized archived data storage layer.
Its network core mechanism is to coordinate storage on already deployed hardware, rather than to push for building new #data centers.

Specifically:

Leverage existing capacity: Filecoin’s storage providers can deploy nodes anywhere in the world with electricity, using already available and powered hardware capacity—without having to wait in long queues for grid interconnection.

Competitive pricing: Filecoin’s pricing comes from market competition among many independent providers, not from the cost structure of a single company. This makes its storage services more resilient and better able to withstand risks.

Archived storage scenarios: #Filecoin’s positioning aligns perfectly with the current trend in which data centers prioritize inference workloads, pushing out cold data/archive needs. It offers an alternative path for data that requires long-term, low-cost, #decentralized storage.


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