Today's Quote

In the end, we will remember not the words of our enemies, but the silence of our friends. -- Martin Luther King, Jr.

Sunday, 3 September 2017

IBM's A.I is the next level?

Artificial Intelligence - the current and future generation in Computers which is merely like producing an Artificial Human Brain which should break the fourth wall between the users and the machine. Lot of works have done well by machine learning and advanced level protocols to list out the Artificial Intelligence on the board.


Deep Learning our Neural networks ain't a small piece of cake, It needs lot of physical constrains and hectic set of algorithm patterns.These Alpha Go,Image recognition, voice assistants, language translations etc are the bleeding edge technological aspects that have been working well on grounds. " Catastrophic forgetting " meant the exact word here with responding to the effects of malfunctions of A.I where the process have to start from the first at 12th clock.
The Human mind is basically built on the conversational aspect where it can retain attention from previous undone tasks where the A.I fails to. Human brain can actually make connections between the past experience and current problem to create an insight and proceeds with it. Statistical AI can make recognition just like human brain but can't apply logic into it where as Symbolic AI can apply logic into it but in real time that's a moo point.
Concept of A.I
DeepMind : An A.I technological company have recently made a survey based on the Artificial Intelligence as a matter of fact by creating a neural network to apply the relational reasoning to those tasks. and it made out a thrash of those neurons applying own specific recognition. In June it happened to made up on the desk again and was commanded to : "There is an object in front of the blue thing; does it have the same shape as the tiny cyan thing that is to the right of the gray metal ball?" it correctly identified the object in question 96 percent of the time. 

"Neural network learning is typically engineered and it's a lot of work to actually come up with a specific architecture that works best. It's pretty much a trial and error approach" said Irina Rish, IBM's research staff member.
It also said that Input Mechanism plays the key role here in understanding between attention algorithm and neural network where she also said " Attention is a reward- driven mechanism " the higher the reward the higher the attention is created. Attention mechanism's first victim is Image Recognition and they're here to Oxford dataset which is primarily architectural images (cityscapes).

IBM: When presented with new set of data it's neurotic system begins forming new and far better connection between 'em and older ones are eliminated from biased connections. " It's a way to adapt deep networks " said Rish. 
 

 These advanced technology aspect might get bean bags to AI community for IBM, where Rish's team works on Internal Attention. This attention model creates cover for short term, active, thought process while memory portion enables the network to streamline its function depending on current situation.
 
As an end phrases and epithet Rish said 
I would say at least a few decades -- but again that's probably a wild guess. What we can do now in terms of, like, very high-accuracy Image recognition is still very, very far from even a basic model of human emotions,We're only scratching the surface
So the lime light is no long for IBM ? and they're in the Go-Kart with other AI companies (Duh, Google). Let's embrace our fortune and attached to the strings of Orbacles.

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