How to discuss Hannibal Lecter’s being a serial killer at his dinner without him noticing it

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Abstract

d="a937">NLP sample (ab)use depending on perspective<figure id="2293"><img src="https://cdn-images-1.readmedium.com/v2/resize:fit:800/1*HlSDwn--vkC21561l5baLg.png"><figcaption></figcaption></figure>Dr. Hannibal Lecter is a serial killer. This sentence can be broken down into who is its subject, what verb is being used, and other bits and pieces like punctuation. Now, if Hannibal would take the result of that analysis he would gather the following important information to him: His name is the subject, and it is about him being a serial killer as an object. But, consider this sentence: Detective Sterling discovered the potential hiding place of Dr. Hannibal Lecter, a fugitive serial killer, to be Florence, Italy. Now, imagine that the sentence in question has been written as a part of a report and parsed with grammarly because the FBI wants well-written reports or whatever. And what if doctor Hannibal Lecter has access to a hidden extension of some kind that is part of grammarly which analyses written text in this way:<figure id="75c9"><img src="https://cdn-images-1.readmedium.com/v2/resize:fit:800/1*1OFe0R7x_lZ7vFgtz6yiLA.png"><figcaption></figcaption></figure>This means that suddenly he knows who is after him and where he is hiding. Important note — the ability to figure out the context from

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complex sentences is still a work in progress [link]. And the examples here are extremely simplified to quickly and efficiently prove the point. Now, imagine if some real work is put into this. Actually, you don’t need to because government and military already has <a href="https://www.darpa.mil/program/deep-exploration-and-filtering-of-text">https://www.darpa.mil/program/deep-exploration-and-filtering-of-text</a>. Also, I do hope that using your human intellect and experience, etc. you know that this article has nothing to do with Dr. Hannibal Lecter. It’s more about hAnnIbal, or with python (didn’t even require NLTK for this one) extracting only capital letters in that word:<figure id="2975"><img src="https://cdn-images-1.readmedium.com/v2/resize:fit:800/1*_ecrDxjoPy_tFMkPsj32wg.png"><figcaption></figcaption></figure>So what do you do about expressing your opinion of hAnnIbal to hAnnIbal? It’s not really that problematic to express concerns and implications of technology taking over. The real concern is the retaliation by the technology in question and/or those who are championing it. I for one don’t mind speaking up because it’s the truth, the facts are overwhelming, and somebody has to keep people aware of the downsides when all those who aim to make a profit are pointing out only the good things.</article></body>

Or, a very curious NLP problem

author’s screenshot

The dark side of something or someone is better discussed with people who aren’t the subject of the discussion. In essence, you wouldn’t want to discuss with your friends/colleagues/strangers how doctor Hannibal Lecter could be a serial killer while having a dinner that he is hosting, and especially not while he is carving a turkey.

NLP If you want to really go deep you can start here. In short, there have been tools to analyze regular text (i.e. articles, books, news reports, and similar) and even html parsers for many years now. The NLTK library for python started in 2001, here it mentions being submitted 2002 arXiv:cs/0205028v1, and the book about how to use it for NLP purposes was released in 2009. Which means it’s been 11 years since that particular approach to text analysis. Which means, its application to machine learning/A.I. had quite a lot of time to evolve.

NLP sample (ab)use depending on perspective

Dr. Hannibal Lecter is a serial killer. This sentence can be broken down into who is its subject, what verb is being used, and other bits and pieces like punctuation. Now, if Hannibal would take the result of that analysis he would gather the following important information to him: His name is the subject, and it is about him being a serial killer as an object. But, consider this sentence: Detective Sterling discovered the potential hiding place of Dr. Hannibal Lecter, a fugitive serial killer, to be Florence, Italy. Now, imagine that the sentence in question has been written as a part of a report and parsed with grammarly because the FBI wants well-written reports or whatever. And what if doctor Hannibal Lecter has access to a hidden extension of some kind that is part of grammarly which analyses written text in this way:

This means that suddenly he knows who is after him and where he is hiding. Important note — the ability to figure out the context from complex sentences is still a work in progress [link]. And the examples here are extremely simplified to quickly and efficiently prove the point. Now, imagine if some real work is put into this. Actually, you don’t need to because government and military already has https://www.darpa.mil/program/deep-exploration-and-filtering-of-text. Also, I do hope that using your human intellect and experience, etc. you know that this article has nothing to do with Dr. Hannibal Lecter. It’s more about hAnnIbal, or with python (didn’t even require NLTK for this one) extracting only capital letters in that word:

So what do you do about expressing your opinion of hAnnIbal to hAnnIbal? It’s not really that problematic to express concerns and implications of technology taking over. The real concern is the retaliation by the technology in question and/or those who are championing it. I for one don’t mind speaking up because it’s the truth, the facts are overwhelming, and somebody has to keep people aware of the downsides when all those who aim to make a profit are pointing out only the good things.