Description

NVIDIA just became the first company in history to hit a $5 trillion valuation — and most analysts think it’s overpriced.

But what if they’re completely wrong?

In this episode, Malcolm Werchota breaks down why NVIDIA’s $5 trillion market cap might be the biggest misjudgment in tech investing. With $500 billion in signed chip orders, 90% market share in AI chips, and an unbreakable software moat called CUDA, NVIDIA isn’t just riding the AI wave — they’re building the infrastructure that makes everything else possible.

🧠 You’ll discover:

• Why NVIDIA has $500B in VISIBLE revenue already locked in (no speculation needed)
• The “railroad analogy” that explains why this isn’t another dot-com bubble
• How CUDA software creates 6–18 months of switching costs for any competitor
• Why China’s reopening could add $50B in annual revenue (pure upside not priced in)
• The power-grid crisis that proves AI infrastructure demand is already locked in
• What it means when companies become GPU-rich vs GPU-poor

Malcolm explains why NVIDIA isn’t a speculative bet on AI — they’re the picks-and-shovels manufacturer in the largest infrastructure transformation since electricity.

Whether AI apps succeed or fail, the hardware stays.

📍 Recorded in London — real analysis, zero BS.

🔥 Notable Quotes

“NVIDIA is probably the first technology company in history with visibility of half a trillion dollars of revenue.” — Jensen Huang

“Every single European company I meet is GPU-poor — they simply can’t get enough NVIDIA chips.”

“Top AI talent goes where the best hardware is. Access to GPUs has become a recruiting advantage.”

“NVIDIA isn’t the speculative railroad company. They’re the track manufacturer, the locomotive builder, and the OS provider.”

“It doesn’t matter which AI app wins — they’ll all run on NVIDIA hardware.”

“It’s a $5 trillion misjudgment. We’re laying the tracks of the next industrial age.”

📈 Key Stats to Remember

• $5 T – NVIDIA’s market valuation (first ever)
• $500 B – Signed chip orders (visible revenue)
• 90%+ – Market share in AI data-center GPUs
• 3.5 M – CUDA developers
• $50 B – China upside
• 1 GW – Power per AI data center
• 6–18 months – Switching cost from CUDA
• 95% – Former China share

📡 Connect with Malcolm Werchota

🌐 Website: www.werchota.ai

💼 LinkedIn: Malcolm Werchota

🎥 YouTube: @werchota

🐦 X / Twitter: @malcolmwerchota

📸 Instagram: malcolmwerchotaai

🎧 TikTok: @malcolmwerchota

📬 Email: malcolm@werchota.ai

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