What You'll Learn in This Episode

DeepSeek's AI breakthrough didn't just happen—it was engineered for maximum impact. This episode dives into the real reasons DeepSeek went viral, why their approach is a direct threat to OpenAI and Anthropic, and how AI compute demand is about to explode by 1000X.

If you think Big Tech is in control of AI's future, think again. The battle for Artificial General Intelligence (AGI) and AI compute power is just beginning, and you need to know who's really in charge.

🔹 Topics Covered: ✅ How DeepSeek became an AI sensation by open-sourcing their models (DeepSeek on Hugging Face) ✅ Why DeepSeek's $5.6 million training cost was a marketing masterstroke ✅ How Jevons' Paradox proves AI compute demand is about to skyrocket ✅ Why you can't trust Google, Amazon, or Microsoft to power the future of AI ✅ The real future of AGI & AI Agents – and how much compute we'll need to make them work ✅ The rise of Exabits as an independent AI compute provider (Exabits)

🧩 Segment Breakdown & Links 1️⃣ The DeepSeek Disruption – What Happened?

🔹 DeepSeek is a Chinese AI company that trained a ChatGPT-4 level model for just $5.6 million—while OpenAI and Anthropic spend hundreds of millions. 🔹 Their strategy? Go open-source, build a community, and make AI cheaper. 🔹 The result? Mass panic in Big Tech & a 17% drop in Nvidia's stock price. 🔗 DeepSeek on Hugging Face 🔗 DeepSeek R1 Model on GitHub

2️⃣ How DeepSeek Engineered Their Own Virality

🔹 They didn't just launch a model—they launched a movement. 🔹 Their secret sauce? A "David vs. Goliath" narrative against OpenAI & Anthropic. 🔹 Twitter (X) exploded with comparisons to Sputnik, fueling the story. 🔹 The now-infamous tweet from Wall Street Engine (@wallstengine) compared DeepSeek's launch to the AI "moonshot" moment. 🔗 Original viral tweet

3️⃣ The $5.6M AI That Exposed OpenAI's Bloated Costs

🔹 Compare the costs:

• DeepSeek R1 Model – $5.6M
• Anthropic Claude – $50M+
• OpenAI GPT-4 – Estimated $100M to $1B 🔹 This fueled investor panic, leading to market sell-offs for Nvidia and Big Tech. 🔗 OpenAI GPT-4 Overview 🔗 Anthropic's Claude

4️⃣ Jevons' Paradox: Why AI Compute Demand is About to Skyrocket

🔹 The Cloud Storage Parallel: When storage got cheap, demand exploded 1000X. 🔹 The same thing is happening with AI compute: More efficiency → More AI adoption → More GPU demand. 🔹 AI compute demand is now doubling every 6 months. 🔗 Nvidia H100 GPU Specs 🔗 Morgan Stanley Report on AI Compute Demand

5️⃣ Why You Can't Trust Google, Amazon, or Microsoft with AI Compute

🔹 Amazon Web Services (AWS) deplatformed Parler overnight—so what happens if they don't like your AI startup? 🔹 Google already has a history of politically-motivated censorship. 🔹 Microsoft Azure is deeply embedded in OpenAI's operations and prioritizes corporate/government interests over startups. 🔹 The only solution? Independent AI infrastructure like Exabits. 🔗 AWS Censorship Controversy 🔗 Google Free Speech Controversy 🔗 Microsoft OpenAI Partnership

6️⃣ The Future: AGI, AI Agents, and the Race for Compute Power

🔹 AGI (Artificial General Intelligence) is the AI that can think, reason, and learn like a human. 🔹 AI Agents will run businesses, negotiate deals, and replace entire industries. 🔹 To train AGI, we'll need 1000X more compute than today—the equivalent of a small country's energy output. 🔹 Exabits & Other Independent Compute Providers will be the only alternative to Big Tech monopolies. 🔗 Exabits AI Compute Solutions 🔗 DeepMind's AGI Research

💡 Key Takeaways

✅ DeepSeek didn't just go viral—it was engineered to disrupt AI's biggest players. ✅ The $5.6M training cost exposed OpenAI & Anthropic's bloated spending. ✅ AI compute demand is about to skyrocket—Jevons' Paradox proves it. ✅ Google, Amazon, and Microsoft can't be trusted with AI's future. ✅ Independent compute providers like Exabits are the real future of AI.

📢 Get Involved:

🔹 Follow Mark Fidelman on Twitter (X): @MarkFidelman 🔹 Join the AI Marketing Podcast Community – Sign Up Here 🔹 Learn More About AI Compute Alternatives: Exabits

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