AI programs that attempt to understand, manipulate, and interpret human language. It can make use of machine learning, as well as statistical, and computational linguistics. The rise of Large Language Models (LLMs) has provided exciting opportunities, but really hasn't changed the issues related to understanding and taking actions based on human language input; although chatGPT et all can reply in useful ways, it struggles to DO what we want instead of just talking.
See also:
class RNN: # ... def step(self, x): # update the hidden state self.h = np.tanh(np.dot(self.W_hh, self.h) + np.dot(self.W_xh, x)) # compute the output vector y = np.dot(self.W_hy, self.h) return y
The np.tanh (hyperbolic tangent) function implements a non-linearity
that squashes the activations to the range [-1, 1]. The input, x, is combined
with the xh matrix via the numpy dot product vector operation. It is added
to the dot product of the internal state and the hh matrix, then squashed
to produce a new internal state. Finally, the output is processed through
the hy matrix and returned.
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