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Part 7:  Compute Sovereignty & Trusted Data — Pillars 3 & 4

  • Writer: Tetsu Yamaguchi
    Tetsu Yamaguchi
  • Jun 3
  • 1 min read

Japan’s edge in power‑efficient hardware and privacy culture can translate into tangible AI leverage—if compute and data are marshalled as national assets rather than siloed perks.

1. Pillar 3️⃣ — Domestic Compute Commons

Fugaku‑LLM proved CPUs can pre‑train a 13 B‑parameter Japanese‑centric model in 12 days ; ABCI 3.0 will add 4 500 H100s by 2025 Q4 . The proposed Compute Commons federates these public clusters with telco and utility data‑centres.

Provisioning tier

Stakeholders

Pricing

SLAs

Academic & SME (30 % capacity)

MEXT, J‑Startup

power + cooling cost only

90 % uptime; free night‑batch

Industrial R&D (50 %)

Corporate consortia

Cost + 20 % overhead

99.5 % uptime; H100 & quantum nodes

Commercial cloud resale(20 %)

NTT Data, KDDI Cloud

Market rate

99.9 % uptime; multi‑AZ

Governance: an open ledger logs GPU hours vs carbon intensity; credits tradeable under Japan’s ETS.


2. Pillar 4️⃣ — Trusted Data Spaces & Privacy‑Enhancing Tech

The Digital Agency’s light‑touch AI Bill plus Hiroshima G7 guidelines position Japan as a middle‑way between the U.S. “anything goes” and EU “risk tiers.”


4.1 Sector Sandboxes

  • Health: federated cancer genome learning across 23 prefectural hospitals using secure enclaves.

  • Mobility: HD‑map RAG APIs expose hashed road‑scene embeddings—usable for model training yet anonymous.

  • Manufacturing: robot telemetry broker under OPC UA‑compatible schemas.

4.2 PET Hack Grants

Annual ¥1 bn contest funds open‑source libraries for homomorphic inference, differential privacy, and split learning. Winning teams get automatic integration credits on Compute Commons.


3. Roadmap

Year

Deliverable

2026

Compute Commons portal (single sign‑on, carbon ledger) goes live

2027

Health & mobility trusted spaces publish first reference datasets

2028

PET grants deliver homomorphic INT4 infer‑lib compatible with Bamba‑Tiny

2030

50 % of Japanese SMEs report using Commons resources in annual METI survey

Outcome: Compute + data become as inter‑operable as the Shinkansen network, giving domestic innovators a friction‑free launchpad.

 
 
 

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