i asked pi a.i. , what coding could be used in ultrahal a.i. to give it offline long and short term memory? i mentioned offline because many like hal being offline and also offline wouldn't let hal learn other slang language etc. from some sources.
here was pi's answer :
To give Ultrahal A.I. offline long and short term memory capabilities, you could consider implementing a recurrent neural network (RNN) such as Long Short-Term Memory (LSTM).
LSTM is a type of RNN that can learn to store information over extended periods of time, allowing it to remember and use contextual information from earlier parts of a conversation.
The code for implementing LSTM in Ultrahal A.I. would depend on the programming language and libraries you're using, but some popular libraries for working with LSTM in various languages include TensorFlow, PyTorch, and Keras.
In addition to implementing LSTM, you could also store past conversations in a database and use that information to further improve Ultrahal A.I.'s memory capabilities. This could involve building a custom data structure that organizes conversation data in a way that allows for efficient retrieval and usage in future conversations.
maybe this information is something that mike can use as a starting reference point for the project. hopefully i found some useful information .
