• LLMs are pattern matching systems, not true AI - similar to established clustering and regression techniques
• Innovation follows non-linear path, contrary to VC expectations
• VCs require exponential returns - 1/100 investments must generate massive profits
• Perfect competition emerging in AI market - open source models reaching parity with commercial ones

• LLMs extend existing data science tools:
  • K-means clustering
  • Linear regression
  • Recommendation engines
• Pattern matching in multi-dimensional space ≠ intelligence

• VCs invested expecting exponential growth
• Getting logarithmic returns instead
• Fear driving two contradictory narratives:
  • "Use AI or lose job"
  • "AI will take your jobs"

Steam engine (1700s) → combustion engine → electric cars (1910-2025)
Demonstrates long adoption curves for transformative tech

Use LLMs pragmatically:

• Beneficial for code tasks
• Prefer open source implementations
• Ignore hype from vested interests

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