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GOP Blames FEMA Cash Shortage on Migrant Assistance, FEMA Pushes Back

4 months ago
3.75K

GOP Blames FEMA Cash Shortage on Migrant Assistance, FEMA Pushes Back

10 Comments

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  • Some of us are OVER (((your))) Democrat/Republican (((PILPUL))), JEW. Send the ILLEGAL INVADERS to JIZraHELL and let them BLOT OUT the MEMORY of the (((JEW STATE))).

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  • What they are either doing intentionally or just because it works and is the path of least resistance for them is to throw such much shit at the wall that no one ever wants to clean it up. That is, they are overloading peoples brains with such much shit no one can track any of it and essentially the higher orders of thinking shut down. It's the "shock and awe" against peoples consciousness. Overwhelm them with so much shit that it just creates chaos. So much confusion that no resistance can be formed, that they can get away with anything, and that most people are not able to process what is really happening. Let me explain to you how this works: In mathematics there is something called sampling. It is fundamental almost all things and more so than what wikipedia suggests: https://en.wikipedia.org/wiki/Sampling Sampling is when you take sample points/data points/snap shots/measurements/etc of things. You do this 100% of the time every instant throughout the day in billions of ways. Every nerve in your body is taking samples of what it measures through chemical processes which connect to every other process. Your eyes are taking samples of the visual field and they are fed into your brain was samples. When you peruse the news you are taking samples. Sampling has been well studied and there are fundamental principles behind how they work. Sampling has to do with any type of information. https://en.wikipedia.org/wiki/Sampling_(signal_processing) [Everything is a signal BTW] Any time you sample something, called "sampling a space" you are taking "data points". You then form a perception of that space through the sampling. You do this because 1. The space is too large to know in totality so you are forced to take "bits and pieces"(samples). 2. It may be more efficient to have fewer samples to represent the space. If the space is a "line"(called a linear space) you only need 2 sample points to describe it. Any more is pointless.

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  • They love dividing the plebs. Who made the decisions to give immigrants money(if they really got any?) was it immigrants or was it rich governments fucks who likely embezzled most of it?

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  • Cringe Jean-Pierre admitted to this 2 years ago. Jimmy did a piece on this like 2 days ago

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  • ... It is then well understood that when you sample a space that there is a relationship between the # of samples AND the ability to extract meaningful information. Clearly if you do not have any samples(data points) you can't reason about the space at all. If you even have a few it may not be enough. It depends on how complex the space is. https://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem Now, if you sample a space and have too few data points you will get aliasing: https://en.wikipedia.org/wiki/Aliasing This means that the data points you have will give you an inaccurate view of the entire space and lead you to draw the wrong conclusions about that space. E.g., if you just sample the news 1 story a day likely you will draw wrong inferences about what is really going on in the world. ALSO, if you sample only certain areas of the space then clearly you will have bias and likely have the same problems. This is the point I'm making. Most people do not spend every waking hour trying to get as much info as they can. They might hear some BS from their coworkers or spend 30 minutes watching the local news. This then means they will not understand the larger scope of things and almost surely, except by luck, form the wrong conclusions about what is really going on. EVERYONE has this issue. It is like gravity. You cannot be it. It's part of "Information theory". That is, it's part of information itself. It should be obvious in the sense that if you don't have enough data you can't form the right conclusions. Hence, by making the space so chaotic that it requires a lot of sampling to "see the truth"(the underlying structure) means that most people will not be able to understand what is going on. It's not their fault... but it is our problem.

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  • ... This is what is meant by "overloading". When you overload the "sampler" with too much information it essentially becomes useless. In music/audio(every mic) there is something called and ADC which samples the air pressure to convert sound into digital samples(numbers). The ADC's are designed to handle certain levels of complexity. A typical human audio system doesn't work for dogs or whales. Which leads to another principle: The more complexity the more time. Complexity = time. It's called Time complexity: https://en.wikipedia.org/wiki/Time_complexity but time and data are actually the same thing. Well, they are inversely related. It is well known that one can trade time for data. E.g., something that requires a lot of time to complete can be memorized instead and then done nearly instantly. E.g., When you think about something and have to "recall it" you can make it faster if you just memorize it(which does take time but after that it is fast). The basic idea: https://en.wikipedia.org/wiki/Lookup_table The point here is that "time is money" and when time is money and time is complexity complexity is money. Cheap ADC's, for example, cannot convert complex signals. To make better ADC's to deal with more complex "spaces"(signals in this case) requires more $$$. The same works with humans. We are just machines. Much of the principles involved in engineering apply exactly to humans and humanity too. Our brains function nearly the same as AI(because AI was modeled after the human brain). Hence understanding AI helps one understand the human brain... just like understanding a model train helps one understand a real train. It's why models are important. E.g., AI NN's also have the same problems I've outlined such as information overload(this is why they require very large(Deep) networks which also costs a lot of money = energy). The point is that the world is very complex and most peoples brains essentially are unable to process any of it.

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  • It's both

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