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NEW YORK (Reuters) -Wall Street lost ground on Tuesday as investors closed the book on a remarkable year for equities, during which the U.S. stock market was powered to record highs by the twin ...
The AI boom may have a profound cultural, philosophical, [64] religious, [65] economic, [66] and social impact, [67] as questions such as AI alignment, [68] qualia, [64] and the development of artificial general intelligence (AGI) [68] became widely prominent topics of popular discussion. [69]
If 2023 was a year of wonder about artificial intelligence, 2024 was the year to try to get that wonder to do something useful without breaking the bank. There was a “shift from putting out ...
Industrial artificial intelligence, or industrial AI, usually refers to the application of artificial intelligence to industry and business. Unlike general artificial intelligence which is a frontier research discipline to build computerized systems that perform tasks requiring human intelligence, industrial AI is more concerned with the application of such technologies to address industrial ...
ChatGPT, the first artificial intelligence app developed by OpenAI, has already created sweeping changes in certain industries. Publishers are laying down standards for AI use for writers -- or, in...
The second thesis is that advances in artificial intelligence will render humans unnecessary for the functioning of the economy: human labor declines in relative economic value if robots are easier to cheaply mass-produce then humans, more customizable than humans, and if they become more intelligent and capable than humans. [8] [9] [10]
According to Sizing the Prize, the analysts at PwC see AI adding $15.7 trillion to the global economy through various production improvements and consumption-side effects by 2030.
There are notable advantages and disadvantages of utilizing machine learning tools in economic research. In economics, a model is selected and analyzed at once. The economic research would select a model based on principle, then test/analyze the model with data, followed by cross-validation with other models. On the other hand, machine learning ...
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