Gay Nineties

The term "Gay Nineties" typically refers to the 1890s, a period of time known for its lively and exuberant social scene in the United States and parts of Europe. It's often characterized by its emphasis on leisure, entertainment, and cultural shifts.

In the United States, the Gay Nineties were marked by economic growth and urbanization. The term "gay" in this context doesn't necessarily refer to sexual orientation, but rather to the sense of carefree and vibrant living that was associated with the era. This was a time of technological advancements, with the spread of electricity, the expansion of urban infrastructure, and the emergence of new forms of entertainment.

During the Gay Nineties, vaudeville shows, musical theater, and other forms of entertainment gained popularity. It was a time of optimism and consumerism, with the upper and middle classes enjoying the new urban lifestyle. The Gibson Girl, a fictional character created by artist Charles Dana Gibson, came to symbolize the idealized independent and confident woman of this period.

Fashion also played a significant role during the Gay Nineties, with women's clothing featuring hourglass silhouettes, high collars, and elaborate hats. Men's fashion included formal suits and top hats for more formal occasions.

The Gay Nineties saw the emergence of some social issues as well, including the Women's Suffrage Movement advocating for women's right to vote and the beginning of discussions around labor rights and workers' conditions.

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AI Technical Trustability Update

While working on an update to my RF Cafe Espresso Engineering Workbook project to add a couple calculators about FM sidebands (available soon). The good news is that AI provided excellent VBA code to generate a set of Bessel function plots. The bad news is when I asked for a table showing at which modulation indices sidebands 0 (carrier) through 5 vanish, none of the agents got it right. Some were really bad. The AI agents typically explain their reason and method correctly, then go on to produces bad results. Even after pointing out errors, subsequent results are still wrong. I do a lot of AI work and see this often, even with subscribing to professional versions. I ultimately generated the table myself. There is going to be a lot of inaccurate information out there based on unverified AI queries, so beware.

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