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Brainy Fact



                    A Convolutional  Neural  Network  (CNN)  is  a  type  of  artificial  neural  network  used  in  image  recognition  and
                    processing that is specifically designed to process large pixel data. Facebook ‘tags’ its images using CNNs.





                      What Machine Learning Can and Cannot Do?

              The first thought that arises in one’s mind after learning about AI and ML is if they will replace humans. In which case,
              what are humans for?

              Humans as the commander-in-chief know ‘what to count”, whereas computers know “how to count”. Smart machines
              can be put to best use only when we understand what it can do and cannot do.

              AI and ML are tools, like a calculator, that help us in solving complex problems which otherwise are complicated for
              the human brain to solve. For instance, we would not use a calculator to multiply “4 x 2”, and would when we have to
              multiply “798 x 347”.
              Here are a few examples of machine learning that we use every day:

              1.   Virtual Personal Assistants: Like Siri, Alexa, Google Home, etc.
              2.   Predictions While Commuting: Like traffic forecasts on Google Maps.

              3.   Video Surveillance Systems: Nowadays are powered by AI that makes it possible to detect crime before they
                   happen. They track unusual behaviour of people like standing motionless for a long time, stumbling, or napping
                   on benches etc.
              4.   Social Media Services: Like Facebook friend suggestion. Facebook continuously notices the friends that you
                   connect with, the profiles that you often visit. On the basis of continuous learning, a list of Facebook users is
                   suggested that you can become friends with.

              5.   Email Spam and Malware Filtering: Emails are arranged according to some standards as per email spam. Mail
                   filtering manages received mails, detects and removes the ones holding malicious codes such as virus, trojan or
                   malware.
              6.   Product Recommendations: You often receive emails from similar merchandizers after you have shopped online
                   for a product. The products are either similar or match your taste, it definitely refines your shopping experience.
                   Did you know that it is machine learning doing its magic in the back?

              7.   Online Fraud Detection: Machine learning is lending its potential to make cyberspace a secure place by tracking
                   monetary frauds online. For example, PayPal is using machine learning for protection against money laundering.
              Even with the advancements we have made in machine learning over the years, there are instances where a Grade 2
              student has been able to beat a computer by solving a problem faster.

              1.  Any problems or questions which require social context will take longer for a machine to solve
              2.   Particularly with respect to text analytics, there are two main challenges. First is “Ambiguity”—this means that the
                 same word can mean many things. Second is “Variability”—indicating the same thing can be said in many different
                 ways.




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