$NVIDIA (NVDA.US)$ In the "Top of Mind" report, author Allis...

$NVIDIA(NVDA.US)$ In the "Top of Mind" report, author Allison Nathan elaborated on the current trends in AI technology:
Generative AI technology is believed to change companies, industries and society, so many large companies plan to invest $1 trillion in AI-related things in the next few years, such as data centers, chips and power grids. But so far, this money has not seen other obvious results except for a little improvement in the efficiency of developers. Even Nvidia's stock price, which has benefited the most from it, has fallen.

We asked some industry and economic experts to see whether these huge expenditures will bring benefits and returns from AI, and discussed what impact will it have on the economy, companies and markets if it does or does not bring returns.

Jim Covello, head of equity research at Goldman Sachs, pointed out:

The cost of developing and running AI technology is very high, estimated to be about $1 trillion. To make this investment worthwhile, AI needs to solve very complex problems, but AI can't do it now. Disruptive technologies like the Internet can replace high-cost solutions with low-cost solutions even in the early stages. AI is expensive now and cannot provide cheaper alternatives.

Moreover, Covello doubts that the cost of AI can be reduced enough to make large-scale automation cheap, given the high initial cost of AI and the complexity of producing key components (such as GPU chips). This complexity may also limit competition in the field of AI.

He believes that AI is unlikely to significantly increase company valuations because the efficiency gains brought by AI are likely to be quickly caught up by competitors, and it is unclear how AI will actually bring revenue growth.

Finally, Covello questions whether AI can truly replicate the most valuable human capabilities because AI is trained on historical data. He believes that AI will not reach the level of human performance in these areas.

Among the many experts interviewed by Goldman Sachs author Nathan, the most notable is Daron Acemoglu, a professor at MIT, who is also skeptical about AI.

Acemoglu estimates that generative AI technology may contribute less to U.S. productivity and economic growth than many people expect over the next decade or more. He believes that only about a quarter of tasks can be automated by AI, which means that AI will only affect less than 5% of all tasks.

Although the technology will become more advanced and less expensive over time, Acemoglu believes that the progress of AI models will not be as fast or impressive as many people think.

In addition, he questioned whether AI would create new jobs and products. He believed that these effects were not "natural laws" and that AI technology could not be expected to automatically bring about a large number of new jobs and products. Therefore, he predicted that AI's actual impact on the economy in the next decade would be limited, and AI would only increase US productivity by 0.5% and GDP by only 0.9%. This would result in the tens of billions of dollars invested being wasted, and the trillions of dollars in market value gained by the "Seven Sisters" of the US stock market could be the biggest bubble in history.