In honor of Johann Sebastian Bach’s birthday, which might be his 333rd, Google created associate AI Doodle on the homepage of their search to honor him and celebrate trendy technology. Created by Google’s Magenta and try groups, the Doodle lets users produce their own music by exploitation machine learning to harmonize melodies. Magenta was chargeable for the machine learning facet of the project whereas try created the flexibility to use it within the application. The machine-learning model, known as Coconet, analyzed 306 of Bach’s original anthem harmonizations thus it absolutely was ready to produce a consonant tune with the user’s notes. This exposes the ground for discussion on AI in music and whether or not or not it will produce music sort of a human and what meaning for artists within the trade. several debates have surfaced around this issue once it involves AI being a vicinity of the music trade and therefore the credibleness of it. This is Google’s initial dive int...
This is a dangerous time moving forward we need to be more vigilant with what wetrust from the internet, i mean great .So here we synthesize Mr Obama and create a fake video.this whole process based on encoding the images and then decoding them at the outputcalled autoencoders. And Autoencoder is a neural network of 3 layer. input layer , Encoding layer & decoding layer , the network of these 3 layer is train to reconstruct its input which forces the hidden layer to try to learn good feature representation of the inputTo train an Autoencoder we first need to collect hundreds or thousands imagesof Both person A and person B then we build an encoder to encoder all thesepictures using a Deep convolution neural network the Deep version of CNN then we use decoder to reconstruct the image this auto encoder has over millions ofparameter encoder need to extract the most important feature to recreatethe original image think about it like is the reverse engineering of a plane toreverse.
It first we need to deconstruct the whole plane now its like a heap of scrap thats what encoded did, creates a future map image and to reconstruct theplane back into its original form there is a big in our brain according to that we start redesigning it thats what decoder did we train encoder anddecoder using back propagation algorithm the Training goes till the time input willmatch close to the output when you training over millions of images theprocess of generating right feature or good feature gonna take you so long Imean this is a time consuming some time it took your days or weeks the wholething depends the kind of hardware you using after training process videoframe a frame and then swap the face of a person with another one thats whatsomething work behind these Chinese virtual news anchor a small step towardsa bigger virtual world welcome to Revolution 4 The revolution of AI if this video helped you and boost your knowledge.
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