E52: Apertus AI Disaster (1 of 2) - Switzerland's 20 Million Franc Reality Check: Why Europe is Building Yesterday's Tech with Tomorrow's Money

20 million Swiss francs. 4,096 cutting-edge chips. 90 days of training. Result? An AI that Hacker News calls "comparable to Llama 3.1" – a model from July 2024. Meanwhile, China builds GPT-4 competitors for $5.6 million.

Breaking down:

• The Swiss Reality: 20M CHF funding | 8.85M GPU-hours | 70B parameters | Apache 2.0 open-source
• Efficiency Disaster: Apertus: 126,000 GPU-hours per billion parameters | DeepSeek: 4,155 GPU-hours | That's 30x LESS efficient
• The Benchmarks: Apertus 8B: 44% | Llama 3.1: 72% | Even Swiss companies use OpenAI instead
• Europe's Structure Problem: 12% of global AI funding | 4-5% of computing capacity | Electricity 3x more expensive

Plus: Why UBS, Swiss Re, and Novartis ALL use American AI models – not Swiss ones.

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