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Threat Modeling Best Practices
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At their core, language models are a prediction model that can interpret, process, and generate human language that can be almost indistinguishable from a human response. While their outputs might seem human, the underlying mechanisms follow principles rooted in statistics and pattern recognition. This means that models fundamentally act as pattern-matching and prediction systems built on neural network architectures.
These models don’t “understand” language in the human sense but instead understand the relationships between words and phrases from how it was trained on a vast amount of data from the internet. This solved one of the key issues with early AI, which was its inability to “teach” itself on a large dataset due to the limited access to the corpus of information (and misinformation) that exists on the internet.
The foundation of this capability rests on two critical components: parameters and vectors.
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