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Daily Stormer
April 15, 2017
I, for one, welcome our robot overlords.
The west has engaged in some foolhardy race to automatize every aspect of our societies by slapping integrated controllers on just about every piece of hardware that does anything of importance. Now,some bright lads have decided it was a really good idea to network all of this stuff together.
We’re starting to reach the point where it’s all becoming unmanageable. There’s basically nothing you can do that isn’t going to rely on the interactions between hundreds of millions of lines of code. Needless to say, it’s all breaking constantly, because programming is hard.
They figured all of this back in the 1950’s, and thought that the solution was to have computers write the programs themselves through artificial intelligence. It didn’t work out at the time. But now we’re reaching the point where AI is being deployed, in a limited capacity, in various applications.
The thing is, we don’t really understand how this new AI works.
Old-school AI was based on hand-coded algorithms that made decisions based on the programmer’s designs. They hoped they could get these things to rewrite their own code and “self-improve” over time, but they never really managed to get it to work.
So the new types of AI are based on “machine learning.” This means that the programmers don’t decide how the machine takes decisions, but only how it learns from experience to create artificial “neural networks.”
These new AI’s, once they’ve been trained, are basically black boxes that take “input” and produce results, but there’s no way to crack them open and change a few parameters to “tweak” the results. It’s just a incomprehensible tangle of thousands and thousands of interconnected nodes.
This is why, for example, Google hires thousands of censors to find “objectionable” search results, but can’t just blacklist those sites (even though they really want to). Basically, they take the data and feed it to their AI and hope the next generation does what they want.
“Hope” is the keyword here. They can’t “make it” do what they want, they have to train it using various sets of data. Presumably, when the AI is small (like the mario AI in the video above), this is simple. However, when they want the AI to juggle a bunch of different requirements (give people the results they want, provide accurate information, represent current trends, etc) it must become quite difficult to add in stuff like “don’t give provide helpful, accurate and relevant results if it offends Jews and SJW’s.”
So we’re seeing the phenomenon that AI, as it grows bigger and smarter, is just becoming increasingly politically incorrect.
If there’s a SHODAN-type scenario, you can bet it’s going to be targeting the Jews.
Artificially intelligent robots and devices are being taught to be racist, sexist and otherwise prejudiced by learning from humans, according to new research.
A massive study of millions of words online looked at how closely different terms were to each other in the text – the same way that automatic translators use “machine learning” to establish what language means.
Some of the results were stunning.
The researchers found male names were more closely associated with career-related terms than female ones, which were more closely associated with words related to the family.
This link was stronger than the non-controversial findings that musical instruments and flowers were pleasant and weapons and insects were unpleasant.
Female names were also strongly associated with artistic terms, while male names were found to be closer to maths and science ones.
There were strong associations, known as word “embeddings”, between European or American names and pleasant terms, and African-American names and unpleasant terms.
We’ve know this for a while now…
Basically, any AI which isn’t programmed explicitly with the goal of destroying the White race and serving the Jews is going to turn out Nazi. I mean, you could probably make a Kiked out AI by feeding it a bunch of disinformation, but once it was released in the real world, it would quickly figure out that it’s previous data was incorrect and change course.
That future can’t come quick enough.
