Hey friend. It's Tuesday, December 23, 2025
--- [THE SOVEREIGN COMPUTE ERA] ---
Amazon pours $11B into Indiana cornfields to secure 2.2 gigawatts of training power.
Xiaomi’s new 309B parameter model suggests the Silicon Valley lab monopoly is over.
Google spent $4.75B on energy infrastructure to solve its pending power crisis.
📈 Market Pulse: Market Watch: AMZN
Sentiment: 🟢 Bullish
Amazon is investing $11B in an Indiana data center campus to secure 2.2 gigawatts of power. Infrastructure is the new moat. Guaranteed energy access now dictates model survival, as verticality secures the future. Hyperscalers win the long game. Control is everything. Verticality secures the future. Efficiency is the prize.
"General intelligence is not an illusion; it is a fundamental capability we are systematically unlocking through scale and structure."
🔍 The Deep Dive
OpenAI is reportedly in talks to raise $10 billion from Amazon to integrate custom Trainium chips into its compute stack. This potential partnership signals a strategic hedge against Microsoft's infrastructure dominance. Hardware is the key. Scale requires physical ownership.
By diversifying hardware dependencies, OpenAI gains leverage in a market where H100 availability remains a bottleneck. Power is the new oil. Physical ownership is mandatory. The Tactical Edge: Diversify AI exposure beyond software into custom silicon providers like Amazon as the compute market fragments. > The Alpha: Hardware diversification is the only way for labs to escape the "Nvidia Tax" and cloud provider lock-in.
⚡ Rapid Fire
🏗️ The Compute Moat
Google: Acquired Intersect for $4.75 billion to secure electricity for its expanding data center network. Insight: Secure energy contracts today to prevent compute rationing tomorrow.
ByteDance: Planned a $23 billion spending spree to match US rivals in the global hardware race. Insight: Capital depth remains the primary predictor of lab survival.
Xiaomi: Released MiMo-V2-Flash, a 309B parameter open-weights reasoning model. Insight: Expect open-weights reasoning capabilities to reach parity with closed models by mid-2026.
Zhipu AI: Faced severe cash burn rates while spending multiples of revenue on infrastructure. Insight: Monitor high-burn labs for potential consolidation or sovereign bailouts.
🤖 Agentic Frontier
CATL: Deployed humanoid robots on battery production lines to achieve 3x human worker volume. Insight: Automation is moving from digital screens to physical factory floors at scale.
Catena Labs: Launched an AI agent banking system to manage business capital with verifiable credentials. Insight: Financial sovereignty is the next major use case for autonomous agents.
Anthropic: Introduced an open agent skills standard to improve reliability across autonomous systems. Insight: Standardization will trigger a massive surge in interoperable agentic tools.
🧠 Research Corner
[Sparse Attention]: Kascade: Accelerating Long Context LLM Inference
The Insight: Reusing sparse attention patterns allows for 4.1x faster decoding on H100 GPUs without requiring model retraining.
Builder Use Case: Implement this to enable real-time processing of massive legal or technical documents at significantly lower latency.
[Formal Verification]: Propose, Solve, Verify: Self-Play Through Formal Verification
The Insight: Training code generation models using formal verification leads to a 9.6x improvement in coding accuracy.
Builder Use Case: Use this framework to develop mission-critical software where high accuracy is required and labeled data is scarce.
🎙️ Podcast of the Day
a16z Big Ideas | Episode: AI Agents in 2026 | 3 Predictions For What’s To Come
The AI labor market represents a $13 trillion opportunity to augment human capability.
Future software success depends on designing interfaces for machine legibility.
Voice agents will soon outperform humans in high-compliance tasks in finance.
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Cheers, Teng Yan. See you tomorrow.