Do you mean, instead of feeding the net data and learning, to instead request new output data/solutions?
Doing so is how we train ourselves, mentally. We can step forward, chaining. We store the data output AND update the model. If you know enough knowledge, you can stop eating data and start fabricating deeper discoveries yourself now. It's better you research along the way, actually. As for w2v, the net has every word in it, cat, hi, dog, home, run. Based on context, you link words to each-other with probabilities of how similar they are. You just started a Heterarchy. These are update-able links (weights). Done digesting your data (ex. ran out of data), you can keep building your Heterarchy. You say OK cat=horse/zebra/etc and dog=horse/zebra/etc, so I'm going to make a link between them / make that link stronger. This is Online Learning. This web is meant for translation tasks, even entailment, because entailing words 'look' like similar words, and you'll generate either 'dog ran to' or 'dog cat horse', which are both sentences. The latter is a list of items. ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Ta664aad057469d5c-M5f3fd9534b0af29351f59add Delivery options: https://agi.topicbox.com/groups/agi/subscription
