What a Neural Network Actually Computes: From Token IDs to Matrix Multiplication
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NLP models cannot process words directly, which is why tokenization[1] exists. Tokenization ends with a list of integers — token IDs like [30642, 1634, 318, ...] . That list is what actually gets fed into a model. This article answers why NLP models cannot process raw text directly. The answer is simple: NLP models consist of neural networks that perform matrix multiplication, which needs a list of numbers, not characters. One Layer of a Neural Network: Multiply, Add, Then a Small Nonlinear…
1Key Takeaways
- NLP models cannot process words directly, which is why tokenization[1] exists.
- Tokenization ends with a list of integers — token IDs like [30642, 1634, 318, ...] .
- That list is what actually gets fed into a model.
- This article answers why NLP models cannot process raw text directly.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that nLP models cannot process words directly, which is why tokenization[1] exists.
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