According to the CEO of Anthropic, the current cost of training AI models is as high as $10 billion, and it could rise to $100 billion or even $1 trillion in the next three years. This forecast has sparked concerns about whether the AI bubble is about to burst.
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Dario Amodei points out that as AI models continue to evolve, hardware demand will also grow exponentially, becoming a major driver of training costs. He also emphasizes the gradual process of artificial intelligence from generative AI to general AI, which is similar to the way human children learn.
In the upward trend of AI training costs, hardware and energy consumption are two significant cost drivers. The delivery volume of GPUs from suppliers like NVIDIA will grow geometrically, and the power demand of data centers will also sharply increase.
In addition, significant costs will also be incurred in areas such as human resources, data collection, and operation and maintenance. If these issues are not resolved, the training cost of AI models could reach $1 trillion by 2027.
Key Points:
⭐ The current cost of training AI models is as high as $10 billion, and it is expected to rise to $100 billion or even $1 trillion in the next three years.
⭐ Hardware and energy consumption are the main drivers of training costs, and as AI models develop, expenditures in these areas will increase dramatically.
⭐ Significant costs will also be incurred in areas such as human resources, data collection, and operation and maintenance. If these issues are not addressed, the training cost of AI models could reach $1 trillion by 2027.
