Is NLP considered artificial intelligence ?

I have used Python, Natural Language Processing and web scraping technology to do some deep mining of Google's vast warehouses of articles on the web.

Is what I described considered artificial intelligence?

Or, in order to satisfy the requirement of AI must that model also automatically adjust it's algorithms based on the results of the searches? In my case, the adjustments were manual.


curiouswebsterSoftware EngineerAsked:
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in order to satisfy the requirement of AI must that model also automatically adjust it's algorithms based on the results of the searches? In my case, the adjustments were manual.

I think most people would consider your manual adjustments as disqualifying  the operation from being considered artificial intelligence.
In you manual case the intelligence applied is not artificial.
Yes NLP is a branch of AI.

Based on your description of your process and the following reference, I would say that what you were doing is at a minimum piecemeal AI. That is, every time you run your program you are doing an AI operation. When you become wiser based on the data or patterns that you observe, you change the algorithm that is a different new and improved AI algorithm.  But better algorithms fall into the AI subcategory of machine learning, where the algorithm learns automatically from the data.
if I can write a very clever program that has human-like behavior, it can be AI, but unless its parameters are automatically learned from data, it’s not machine learning.

The fact that you are using data and modifying the algorithm manually suggest that you were on the road to machine learning.

Machine learning and deep learning rely on modeling the brain. By changing the weights of the simulated synaptic regions of inputs and outputs, you might consider that as a change in the algorithm, but I just see this modifying parameters as leaving the algorithm intact. But we'll leave aside this semantic issue.

You  didn't say what mechanism you are your algorithm manually. But machine learning gets change initially through supervised or unsupervised learning. As you read through the link and subsequent link on deep learning, we'll see that we need a huge amount of Big Data in order to properly teach our machine how to do the assigned tasks. This huge effort has been mitigated by using massively parallel GPU systems reducing the learning time from 20 to 40 days to just one day.

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