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The buzz around Generative AI (GenAI) is louder than ever—but are we seeing the whole picture?

This presentation was designed for a broad audience, avoiding technical jargon while addressing the real opportunities and challenges AI brings.

🔍 A few key insights from the presentation:

💡 Innovation under constraint: DeepSeek achieved remarkable results at a fraction of competitors’ costs.

🔄 The productivity paradox: AI may boost output for writers and coders but may reduce job satisfaction for scientists.

🤖 The shifting definition: “AI is what computers can’t do; once they can, it’s just software.” — Mustafa Suleyman

⚡ The GPU Bottleneck: Big Tech is turning to custom chips and nuclear energy to meet AI’s soaring computational demands.

♻️ Energy-Hungry AI: AI’s energy needs are driving investments in dedicated nuclear power for datacenters.

Slide decks are meant to support live talks, so they might not capture the full story on their own. If you are curious to dive deeper, feel free to reach out—I would be happy to discuss these ideas in a more interactive setting.

Feel free to check out my LinkedIn post for further discussion: linkedin.com/posts/merckel_intro-to-genai-activity-7300095492862930946-rnL9