Tip of the Day

Do not go where the path may lead, go instead where there is no path and leave a trail.

Is there something that Deep Learning will never be able to learn?


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The word “will never” which indicates that no one can’t guarantee that. Currently there are lots of things that Deep learning can’t do but it might in the future. We just don’t know. For example, learning from one domain and apply it into the other domain (Transfer learning) like beating a 3x3 tic-tac-toe and apply it to 5x5 tic-tac-toe.
One shot learning, a learning that needs low amount of training data like human does on object recognition. And lots of things that we need to do to make it behave more intelligent. One thing is to learn the structure of the model itself not just adjusting weights and biases.
Right now, the subject on Machine Learning is trending — everything about it is mostly down to the sense of accuracy, able to absorb large amount of data and compute to its belonging, grouping where they most fit and the percentage of accuracy turned to high. It’s all down to application-based on how we utilized the Deep Learning machine.
There are few researchers continue to solve problem and trying to figure out how to go about bringing it to life.
Present AI is limited to only 1st kind of learning through mostly text and vision data. So, here is the first limit on machines.
Again, AI is rule based learning…So, you feed the rules of learning and the computer will learn anything. But the most important thing is that do we know all the rules of learning. Or in other words are we omniscient. NO.
So, limit of any AI system is boundary of our own knowledge. And until we become omniscient a dream of all knowing machine is…just a dream.
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Himanshu Rai

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