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Sam Altman’s $7 Trillion AI Dream: Visionary Or A Leap Too Far?

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Sam Altman’s plans to overhaul the semiconductor industry with an injection of up to $7 trillion in private investments could be as unrealistic as they are ambitious.

The CEO of OpenAI, whose company recently shattered growth records with revenues of over $2 billion last year, is chasing the quest of building an artificial general intelligence: an AI model able to universally perform better than humans on any given task.

For this, the executive is embarking on a quest to raise a sum that seems impossible for a company its size.

Earlier this month, a report by Cathie Wood’s Ark Invest predicted that the cost of training AI programs would drop by 75% on a yearly basis until 2030

In a Monday speech, Nvidia Corp’s (NASDAQ:NVDA) CEO Jensen Huang echoed Ark’s prediction, saying that advances in computing technology will significantly reduce the costs associated with developing artificial intelligence.

Altman himself confirmed that the cost of training GPT-4, the latest AI language model behind the company’s successful ChatGPT, was above $100 billion.

However, the processing capacity needed to build exponentially more powerful models is beyond today’s reach. The complex process of manufacturing high-performance chips needed in AI system training requires the coordination of many areas including supply chains, facility development and expert training, many of which fall short of today’s resources.

There are currently only a handful of companies in the world with the infrastructure and the know-how to manufacture the most advanced chips that will train the next generation of AI systems. Taiwan Semiconductor Mfg. Co. Ltd. (NYSE:TSM), Intel Corp (NASDAQ:INTC) and Samsung have all been investing heavily in new manufacturing facilities that are becoming the backbone in the ongoing race to dominate AI technology.

Also Read: Nvidia CEO Jensen Huang Urges Nations To Embrace ‘Sovereign AI,’ Predicts Data Center Spending To Hit $2 Trillion By 2029

Both Big Tech companies and governments have become aware of the need to support the growth of AI as a strategic asset in securing market dominance and geopolitical power, respectively.

Securing the necessary infrastructure to make those developments is a key step along the way. In many cases that means investing heavily in chip factories.

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