The Data Exchange with Ben Lorica Why China's Engineering Culture Gives Them an AI Advantage
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Sep 6, 2025 
Evangelos Simoudis, a venture capitalist at Synapse Partners and a corporate innovation blogger, dives deep into AI's complex landscape. He reveals the challenges of AI regulation in the U.S. compared to China's engineering-centric approach. The discussion highlights how China's governance fosters rapid technological advancement. They also explore issues around intellectual property in training data and the need for transparent regulations. Simoudis emphasizes the importance of balancing innovation with ethical considerations amid a rapidly evolving AI industry.
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Regulate By Domain, Not Blanket Models
- Foundation-model-wide regulation is premature given rapid model change and uncertainty about future architectures.
- Domain-specific regulators (health, transportation, finance) are more efficient at addressing concrete risks and uses.
Audit Training Data And Usage
- Check both how a foundation model was trained and how it's used inside your application before deploying it.
- Audit outputs for IP risk and system safety when embedding models into enterprise workflows.
IP Pressure Is Forcing Licensing Moves
- Creators want transparency and control over whether their works train foundation models.
- Legal pressure and licensing deals are already forcing some model-makers to pay for training data.
