A Recurrent Neural Network (RNN) is a type of artificial neural network used to process sequential or temporal data. Unlike feedforward neural networks, in which information flows in one direction only, in RNNs information flows in a loop, i.e. the output at one point in time is used as input at the next point in time.
The ability to process data streams makes them useful for a wide variety of applications, such as speech recognition, machine translation and text generation. One of the main features of RNNs is their ability to model long-term dependencies in data streams.
RNNs have a recurrent structure, which allows information to flow from one layer to another through a hidden state, which stores information about previous states. The hidden state is updated at each time step and is used to influence the output at the next time step. This allows the RNN to have long-term memory and be able to capture patterns in data sequences that extend over time.
The fad coming from the USA that will force the incorporation of AI in the process Surely it is only recently that we have started to hear a new concept in [...]
Read More »One of the decisions faced by a company that needs an IT infrastructure is the choice of where to locate this infrastructure and where to install it.
Read More »How is artificial intelligence helping us? Artificial intelligence (AI) has gone from being the stuff of science fiction movies to a [...]
Read More »Nowadays digital transformation is key in any type of business. The 40% of Spanish companies will not exist in its current form in the next few [...]
Read More »
