Sam Altman and the day Nvidia’s meteoric rise came to an end

2025-06-07 · Source: Marcus on AI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, AI Industry & Market Analysis · Depth: Intermediate, short

Summary

Nvidia's stock, after a 1200% rise over five years, has plateaued, dropping 2% in the last six months, signaling a shift in investor confidence. This change is attributed to the debunking of the "scaling = AGI" myth, heavily promoted by OpenAI's Sam Altman, who falsely claimed in January 2025 to know how to build AGI. The turning point was August 7, 2025, when OpenAI's GPT-5 was introduced, failing to meet its exaggerated claims of performing at a PhD level. This event exposed the limitations of large language models (LLMs) as non-AGI, unreliable, and expensive commodities, leading to investor rotation out of tech stocks. Nvidia, which traded at 181 on August 7, 2025, now stands at 177, while Coreweave dropped from 129 to 89, and Oracle from 250 to 150.

Key takeaway

For investors evaluating AI-related stocks, recognize that the market is correcting its overvaluation of LLMs based on the "scaling = AGI" myth. Your portfolio should reflect the reality that LLMs are powerful but commoditized tools, not a direct path to AGI, and their profitability may be modest. Consider rotating out of companies whose valuations are primarily driven by unproven AGI promises and seek out firms developing more robust, differentiated AI approaches.

Key insights

The "scaling = AGI" myth's collapse led to a tech stock plateau, revealing LLMs' commodity nature.

Principles

• Hype can drive market valuation temporarily.
• LLMs are powerful but not AGI.
• Commoditization leads to price wars.

In practice

• Evaluate AI claims critically.
• Diversify tech investments beyond LLM-centric firms.

Topics

• AI Hype Cycle
• Large Language Models
• Artificial General Intelligence
• Tech Stock Performance
• OpenAI Strategy

Best for: Investor, Tech Journalist, Executive

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Editorial summary, takeaway, and curation by AIssential. Original article published by Marcus on AI.