Post by account_disabled on Mar 6, 2024 5:20:01 GMT -5
The great potential of generative artificial intelligence (AI) as a transformer of production processes and innovation has been highlighted for some time, but the enormous success of ChatGPT is accelerating this vision. In recent months, anything that smells like artificial intelligence is attracting the attention of the media and, above all, investors. The North American S&P index has gained 17% since the beginning of the year, but 75% of this increase is explained by just five companies with large interests in AI. In January, Microsoft invested $10 billion in OpenAI (the company that owns ChatGPT). Its shares have racked up a 40% gain since the start of 2023. Alphabet, which owns Google, merged Google Brain and Deep Mind in April to accelerate AI technologies, and its shares have gained 33%. Apple has developed powerful artificial intelligence systems for its Apple Vision Pro (augmented reality glasses) and earns 51%. Amazon has also gained 52% for the year.
Ability to facilitate the production and training of complex generative AI models has undoubtedly encouraged its price. Finally, Nvidia, which produces chips with a specialized instruction set to speed up AI algorithms, gained 206% this year. Even small Job Function Email Database AI companies have value-to-earnings multiples that have led many to believe this is a fad that could become a new bubble. The big guys have jumped on the AI bandwagon Given Ruvic / Reuters One reason that could support this view is the little effect that all these expectations are having on productivity. Solow, a Nobel laureate in economics, said in the 1980s that computers were seen everywhere except in productivity statistics. Paraphrasing, we could now say that you see AI algorithms everywhere except in productivity statistics. Since 2005, the productivity of most countries has stagnated or even fallen, as is the case of Spain, Italy or Portugal.
Adaptation Innovations take time to produce effects on productivity, but in the case of AI this can happen faster: it is software and it is understandable to humans Some authors consider that there are reasons to distrust the potential of these new technologies on productivity. First of all, Robert Gordon, one of the most influential economists in the United States on the subject of productivity, considers that the current revolution cannot be compared in influence with the previous industrial revolution, where the generalization of electricity, the combustion engine internal, chemicals, running water, antibiotics, etc. It was a radical transformation. Secondly, various investigations show a very significant drop in research productivity, one of the main sources of growth of this indicator. For example, the number of researchers needed to double the density of transistors on a chip every two years (Moore's Law) is more than 18 times greater today than in.
Ability to facilitate the production and training of complex generative AI models has undoubtedly encouraged its price. Finally, Nvidia, which produces chips with a specialized instruction set to speed up AI algorithms, gained 206% this year. Even small Job Function Email Database AI companies have value-to-earnings multiples that have led many to believe this is a fad that could become a new bubble. The big guys have jumped on the AI bandwagon Given Ruvic / Reuters One reason that could support this view is the little effect that all these expectations are having on productivity. Solow, a Nobel laureate in economics, said in the 1980s that computers were seen everywhere except in productivity statistics. Paraphrasing, we could now say that you see AI algorithms everywhere except in productivity statistics. Since 2005, the productivity of most countries has stagnated or even fallen, as is the case of Spain, Italy or Portugal.
Adaptation Innovations take time to produce effects on productivity, but in the case of AI this can happen faster: it is software and it is understandable to humans Some authors consider that there are reasons to distrust the potential of these new technologies on productivity. First of all, Robert Gordon, one of the most influential economists in the United States on the subject of productivity, considers that the current revolution cannot be compared in influence with the previous industrial revolution, where the generalization of electricity, the combustion engine internal, chemicals, running water, antibiotics, etc. It was a radical transformation. Secondly, various investigations show a very significant drop in research productivity, one of the main sources of growth of this indicator. For example, the number of researchers needed to double the density of transistors on a chip every two years (Moore's Law) is more than 18 times greater today than in.