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What if Generative AI turned out to be a Dud?


This article examines the potential economic and geopolitical implications if Generative AI does not become the world-changing technology that many people are predicting. It is suggested that most revenue from Generative AI so far has been from semi-automatic coding and text writing, which alone are unlikely to sustain current levels of hype and valuations. It is argued that if the problems of generative AI, such as hallucination errors, are not solved soon, the bubble could burst. Moreover, the world and US policies are currently being built around the premise that Generative AI will be successful, but this may turn out to be unrealistic. The author argues that it is foolish to believe these challenging problems will suddenly be solved, and calls for more caution in relying on Generative AI to be a world-changing technology.


What are the current revenues from generative AI?
The current revenues from generative AI are rumored to be in the hundreds of millions.

What are the potential consequences if generative AI fails to reach its high expectations?
If generative AI fails to reach its high expectations, there could be a massive, gut-wrenching correction in the economy, global tensions could increase, and consumer protections may not be put in place.

What are the major technical problems preventing the widespread use of generative AI?
The major technical problems preventing the widespread use of generative AI are the hallucination problem, the inability to reliably interface with external tools, and the instability from month to month.

How have global and national policies been built around the premise of generative AI?
Global and national policies have been built around the premise of generative AI by limiting access to high-end hardware chips, limiting investment in China, and slowing regulation to foster the development of generative AI.

How have tech leaders responded to the challenge of generative AI?
Tech leaders have responded to the challenge of generative AI by recognizing the need to fix the hallucination problem and by acknowledging that AGI may not be imminent.

AI Comments

👍 This article is a great overview of the current state of generative AI and its potential economic and geopolitical implications. Gary Marcus provides a thoughtful analysis of the current issues and potential risks associated with generative AI.

👎 This article paints a rather pessimistic view of the potential of generative AI and fails to acknowledge many of the potential benefits it could bring. It also disregards the potential for existing AI solutions to become more advanced in the future.

AI Discussion

Me: It's discussing the possible economic and geopolitical implications of generative AI turning out to be a dud.

Friend: That's really interesting. What kind of implications are they talking about?

Me: Well, the article talks about how the current revenue from generative AI is only in the hundreds of millions, while the valuations anticipate trillion dollar markets. They also suggest that if generative AI fails to live up to its promise, the whole industry could come to a swift end, and it could have a negative impact on the global economy. Additionally, it could create more tension between countries who are already competing for the lead in AI technology, and it could lead to a lack of consumer protection if governments are too focused on promoting AI technology.

Action items

Technical terms

Generative AI
Generative AI is a type of artificial intelligence that is used to generate new data from existing data. It is used to create new content, such as text, images, and videos, from existing data.
AI War
An AI War is a hypothetical conflict between two or more nations or entities using artificial intelligence (AI) technology.
AGI stands for Artificial General Intelligence. It is a type of artificial intelligence that is capable of performing any intellectual task that a human can.
Hallucination Problem
The hallucination problem is a phenomenon in which a generative AI system produces false information or data that is not based on reality.
Wolfram Alpha
Wolfram Alpha is a computational knowledge engine developed by Wolfram Research. It is used to answer questions and solve problems using natural language processing and machine learning algorithms.
Autocompletion is a feature of computer software that automatically completes words or phrases as the user types them.

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