Can a recurrent neural network learn to count things?

We explore a recurrent neural network model of counting based on the differentiable recurrent attentional model of Gregor et al. The model thus demonstrates that the ability to learn to count does not depend on special knowledge relevant to the counting task.

Can machine learning predict random number?

No. Machine learning can be used to learn patterns in data. Pure random numbers have no patterns (by definition) and consequently can not be learned. Quantum sources (such as radioactive decay) are true random in physics and can not be predicted even if the full physical state is known in advance.

Why is recurrent neural network hard to train?

One of the simplest ways to explain why recurrent neural networks are hard to train is that they are not feedforward neural networks. In feedforward neural networks, signals only move one way. The signal moves from an input layer to various hidden layers, and forward, to the output layer of a system.

Can LSTMs count?

LSTM Networks Can Perform Dynamic Counting. Proceedings of the ACL 2019 Workshop on Deep Learning and Formal Languages, Florence, Italy, August 2, 2019. In this paper, we systematically assess the ability of standard recurrent networks to per- form dynamic counting and to encode hierar- chical representations.

Can a neural network be used to predict the next pseudo random number?

The neural network could be trained to find certain patterns in the history of random numbers generated by a PRNG to predict the next bit. The stronger the PRNG gets, the more input neurons are required, assuming you are using one neuron for each bit of prior randomness generated by the PRNG.

How do we train RNN?

To train a recurrent neural network, you use an application of back-propagation called back-propagation through time. The gradient values will exponentially shrink as it propagates through each time step. Again, the gradient is used to make adjustments in the neural networks weights thus allowing it to learn.

https://www.youtube.com/watch?v=IV8–Y3evjw