How do I make my LSTM model more sensitive to changes in the sequence?

I have a many to one LSTM model for multiclass classification. For reference, this is the architecture of the model model.add(LSTM(147, input_shape=(1000, 147))) model.add(Dense(5, activation=’softmax’)) model.compile(loss=’categorical_crossentropy’, optimizer=’rmsprop’, metrics=[‘accuracy’]) The model is trained in 5 types of sequences is able to effectively classify each sequence I feed into the model with high accuracy. Now my new…

Will AI still fit in a box without never can go out..?

Following Brian Cantwell Smith : We need some “decidable interpretation” of the world before we can decide over it using logical operations. so “computation” requires a proper “interpretation” of the world. But There is no “natural interpretation” of the world that fits with logical operations where our logically decidable set of algorithms can operate over.…