- Charlie Munger, who passed away at the age of 99 on Tuesday, made a significant statement regarding AI, suggesting that it is excessively hyped.
- The renowned investor expressed his personal skepticism towards the exaggerated enthusiasm surrounding artificial intelligence.
- Current evidence seems to support his viewpoint, indicating that AI is currently costly and not profitable.
Charlie Munger’s insightful predictions were accurate.
His decisions to support companies like Apple, Costco, and Coca-Cola alongside his investing partner Warren Buffett solidified Munger’s status as a legendary investor, contributing to Berkshire Hathaway’s impressive cash reserve of $157 billion.
Despite his passing at the age of 99, Munger remained critical of trendy industries like cryptocurrency and bitcoin, labeling them as “rat poison.”
In a statement made in May, Warren Buffett also expressed doubts about the excessive excitement surrounding artificial intelligence.
This skepticism coincided with the significant investments made in AI startups by entities like OpenAI, the creator of ChatGPT, which received substantial funding from Microsoft and venture capitalists, leading to inflated valuations.
In an unexpected turn of events, Munger’s final notable prediction could hold true: AI might indeed be overhyped.
Here’s a breakdown of why:
1. Lack of Profitability
The primary source of the 2023 AI frenzy, OpenAI, is currently embroiled in internal turmoil following a tumultuous boardroom reshuffle.
The company’s valuation of $86 billion seems unjustified given the recent chaotic events. While private and public valuations differ, comparisons with companies like Ferrari, British American Tobacco, and Dell raise doubts.
Moreover, OpenAI’s intricate corporate structure, with a nonprofit parent company overseeing a profit-capped entity, raises concerns about its growth potential from an investor’s standpoint.
The profitability of AI ventures remains uncertain, with entities like DeepMind, acquired by Google, struggling to balance research goals with commercial viability, resulting in significant financial losses.
2. Reliance on Venture Capital
Many AI startups, including competitors of OpenAI like Stability AI, Inflection AI, and Anthropic, heavily rely on venture capital for sustenance.
Munger’s skepticism towards the investment decisions of venture capitalists resonates here, highlighting the fine line between strategic investments and speculative gambles.
The rapid return expectations associated with venture capital may not align with the long-term research and talent requirements of AI firms.
3. Unproven Potential
The overarching question remains whether AI will fulfill its lofty promises and transformative potential.
While AI is positioned as a groundbreaking technology comparable to the internet, doubts persist regarding its practical realization. Claims of AI matching human intelligence are met with caution, considering the technology’s dependency on existing data and susceptibility to errors like hallucinations.
Furthermore, the generalization capabilities of AI beyond training datasets are under scrutiny, as highlighted in recent research by Google scholars.
