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The concept of pay-TV first emerged in the 1960s as a way for viewers to access
premium programming that was not available on broadcast television. The first pay-TV
service, called Subscription Television (STV), was launched in Pennsylvania in 1963.
STV was a closed-circuit system that used a set-top box to scramble and unscramble
the signal, which prevented non-subscribers from accessing the premium channels.
The service offered movies, sports, and other programming for a monthly fee, and
it was initially successful in attracting subscribers.
However, pay-TV faced several challenges in the 1960s and 1970s, including technical
issues with the set-top boxes, high subscription costs, and resistance from broadcasters
and regulators who were concerned about the impact of pay-TV on the traditional
broadcast model.
As a result, pay-TV did not become a widespread phenomenon until the 1980s, when
technological advancements and regulatory changes made it more feasible and attractive
to consumers.
In the 1980s and 1990s, cable television became a major player in the media landscape,
with the consolidation of the industry leading to the emergence of large media conglomerates
like Comcast, Time Warner, and Viacom. The growth of the internet and the emergence
of new digital technologies have also had a significant impact on the cable industry,
with many cable providers now offering high-speed internet and other digital services
alongside traditional cable television.
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Gemini (Google), and/or
Arya (GabAI), and/or Grok
(x.AI), and/or DeepSeek artificial intelligence
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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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