11 Cool Ways to Use Machine Learning - InformationWeek
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11 Cool Ways to Use Machine Learning

Machine learning is becoming widespread, and organizations are using it in a variety of ways, including improving cybersecurity, enhancing recommendation engines, and optimizing self-driving cars. Here's a look at 11 interesting use cases for this technology.
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Understand Legalese 

Legal documents are often too complicated for the average person to easily comprehend. Some hire a lawyer. Others may skim the documents, or even ignore a document's content, hoping that somehow everything will work out. Some are overconfident about their ability to understand the documents. Deep learning can help. 
'We built a legal language model that allows us to translate legal language into a big string of numbers. We're using deep learning and topological data analysis, which is sort of a dark corner of geometry,' said Dan Rubins, founder and CEO of Legal Robot, in an interview. 'A lot of techniques have been developed for natural language processing on normal language, but there's nothing natural about legal language.' 
In addition to translating legal language into plain language, Legal Robot can determine what's missing from a contract and whether there are elements in a contract that shouldn't be there, such as a royalty fee section in a non-disclosure agreement. When it comes to contracts, there is often a disparity of bargaining power between the parties, such as between a payday lender and lendee, or between a corporation and an individual. Because contracts usually contain a lot of complicated language, people often agree to terms and conditions that favor the other party. 
(Image: edar via Pixabay)

Understand Legalese

Legal documents are often too complicated for the average person to easily comprehend. Some hire a lawyer. Others may skim the documents, or even ignore a document's content, hoping that somehow everything will work out. Some are overconfident about their ability to understand the documents. Deep learning can help.

"We built a legal language model that allows us to translate legal language into a big string of numbers. We're using deep learning and topological data analysis, which is sort of a dark corner of geometry," said Dan Rubins, founder and CEO of Legal Robot, in an interview. "A lot of techniques have been developed for natural language processing on normal language, but there's nothing natural about legal language."

In addition to translating legal language into plain language, Legal Robot can determine what's missing from a contract and whether there are elements in a contract that shouldn't be there, such as a royalty fee section in a non-disclosure agreement. When it comes to contracts, there is often a disparity of bargaining power between the parties, such as between a payday lender and lendee, or between a corporation and an individual. Because contracts usually contain a lot of complicated language, people often agree to terms and conditions that favor the other party.

(Image: edar via Pixabay)

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batye
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batye,
User Rank: Ninja
2/3/2016 | 11:12:04 AM
Re: amazing
@kstaron, yes I could not agree more as security is important this days... and you could never have lot of security... 
kstaron
50%
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kstaron,
User Rank: Ninja
12/21/2015 | 9:50:37 AM
amazing
Some of these are reallt interesting. I love that it could help detect Malware and inprove Cybersecurity. The ones that help read legalese and out wit the other litigator thought I think would probably first only be used by the ones that already have the advantage over the other party, leading to an even greater advantage that I don't feel entirely comfortable with. It's amazing what we've been able to accomplish with machine learning though.
batye
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50%
batye,
User Rank: Ninja
12/7/2015 | 11:20:35 PM
Re: interesting
thank you, as I did learn something new...
LisaMorgan
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LisaMorgan,
User Rank: Moderator
12/7/2015 | 11:09:00 AM
Re: interesting
Thanks!  Glad you enjoyed it!
batye
50%
50%
batye,
User Rank: Ninja
12/6/2015 | 12:51:19 AM
interesting
interesting to know, thank you...
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