Header Ads

Deep Learning Enabling Artificial Intelligence to Grow

Sci Fi Movies and Science Fiction are about to become a reality soon. Remember the Jetsons? Apparently, that may soon be our reality. Only, we will be able to keep our dog with us in our ship.
Moving further, Deep Learning is the term that is causing some extravagant difference in the field of Machine Learning. And taking us closer to the goals of Artificial Intelligence.

What is Deep Learning?

It is a deep structured learning process for Machine Learning that includes algorithms that are inspired by structure and function of the brain i.e. Machine Learning Neutral Networks.
It is a new part of Machine Learning Innovation, and has become a vital part of the research process. The Deep Learning Architecture is aiding in refining AI Machine Learning. It is basically a subfield that translates the brain functions.

How is it Evolving?

Recently, news said that a six person startup from Seattle built an augmented tele-robotics software which would enable humans to have greater control on remotely operated robots that can be useful for exploring planets or outer space.  
Take a look at the research groups and labs currently working on deep learning: http://deeplearning.net/deep-learning-research-groups-and-labs/
In the last year, Google also revealed that for almost a year they were using chips called Tensor Processing Units to implement deep learning and machine learning applications.
We are aware the Artificial Intelligence involves a vast range of technologies that eventually is predicted to solve problems through thinking like humans. Within that area, Machine Learning is going to play vital role where Deep Learning is a small sub category that will be contributing for Neutral Networks and help machines to think!
Deep Learning is transforming the IT industry and the leaders are predicting that tomorrow, in the AI Market, Deep Learning will be have a huge chunk! 
“There are fundamental changes that will happen now that computer vision really works,” says Jeff Dean, Leader – Google Brain Project
He went on to rephrase the sentence and said “Now that the computers have opened their eyes” It is like they were in hibernation all this while. Now, it is time that they will do the talking for us. Sounds a little twisted, doesn’t it?
With the recent study and research, Deep Learning has evolved with the passage of time. With the BigData, extreme power resources, many machines can recognize objects and translate speech in real time.
When they say that we can extend Deep Learning to applications, they mean taking applications beyond sound, speech and image recognition. With the help of Neural Networks, we humans will be able to build a BRAIN. That works and acts like a human, and gets better with time and more information fed to it.
Neural Networks, said to be developed 1950 helps in simulating the data by recognizing the patterns of the brain, functions of anticipation and action. This system is much improved now. It selects the set of virtual neurons from the brain and then gives random numerical values to these neurons to establish a connection between the neurons and the values. These values determine the response of each simulated neuron. This value is determined between 0 and 1. This then showcases the frequency of response and each unit of sound are the spoken syllables.
Until recently, Neural Networks could not reason,  it did not recognize a pattern. In 1980, there was finally a way to recognize these patterns through neural networks with ‘DEEP’ models. These deep models were smarter as they used software neurons in a more evolved way than ever before. Although back then it required more human attention and power resources. Later Hinton developed a more efficient way to train individual layers which made this system more comprehensive with time.
Later in 2011, Microsoft came out with their Deep Learning Algorithms for commercial speech recognition products. Then the following year, Google came with their own suit of Deep Learning Technology.
And in the last year, sometime around June, Google took this project to next level when they introduced the neural network with billion connections. This project was led by Professor Andrew Ng, Standford Computer Science and Google Employee Jeff Dean. And we all saw how Deep Learning enabled a system to identify objects that humans also never defined or described before.
Now there are many open source software and libraries for Machine Intelligence and Artificial Intelligence and the most popular one led by Elon Musk i.e. OpenAI
Now 2017, Facebook open sourced its Deep Learning Framework Caffe for AI Machine Learning developers and programmers to experiment and improvise with Machine Learning techniques and applications.
And just yesterday, Microsoft released Open Source Toolkit for Deep Learning. So we are just going one step further at a time with Deep Learning and that too at a faster rate. Tomorrow, we will see the manufacturing industry making the most of Artificial Intelligence with Deep Learning and Machine Learning Systems. Robots are the future but it will be because of the efforts made by Humans. We should just hope to have control over them. 

I hope this read was good enough to have an understanding of deep learning and its evolution since its inception. It has hugely transformed the AI industry and soon we will see some interesting robots and innovations. Until then, keep it deep!
Powered by Blogger.