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What is a Markov chain and how can it be used in creating artificial intelligence?

A Markov model includes the probability of transitioning to each state considering the current state. "Each state" may be just one point - whether it rained on specific day, for instance - or it might ...
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Is Nassim Taleb right about AI not being able to accurately predict certain types of distributions?

Yes and no! There's no inherent reason that machine learning systems can't deal with extreme events. As a simple version, you can learn the parameters of a Weibull distribution, or another extreme ...
• 8,877
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How can supervised learning be viewed as a conditional probability of the labels given the inputs?

This formulation/interpretation can indeed be confusing (or even misleading), as the output of a neural network is usually deterministic (i.e. given the same input $x$, the output is always the same, ...
• 33.8k
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• 9,379
1 vote
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How can I improve this word-prediction AI?

Seems like recurrent neural networks (RNN) should work for your use case. An excellent introduction is available at: The Unreasonable Effectiveness of Recurrent Neural Networks
• 243

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