by Taniya Arya
I am sure that you have browsed through the Artificial Intelligence aka AI enabled tech gadgets that were showcased at the Consumer Electronics Show (CES) this year. I did and I was fascinated by the new technologies that were showcased at the grand tech event, right from the Smart Autonomous Cars to the Delightful Robots to the powerful Lego Boost Robotic Kits that can teach coding. This blog post talks about the latest AI advancement- Deep Learning, which is fueling the computing industry and will completely transform the corporate architecture in the coming years.
Deep learning is creating efficiencies in our power grids, percolating into our smart gadgets, gaining momentum across healthcare, augmenting our agricultural productions, and interestingly enough helping us find solutions pertaining to weather change.
Google by putting its DeepMind artificial intelligence in charge of its data center facilities, gets about 40% reduction in power consumption.
The Concept Demystified
Deep Learning is a subset of Machine Learning, which in turn is a subset of Artificial Intelligence. This whole architecture incorporates most logic and rule-based systems designed to solve problems. Machine Learning under the AI field encompasses a suite of algorithms that sift through data to improve the decision-making process. And, within machine learning you have deep learning, which can make sense of this data using multiple layers of abstraction.
The AI Revolution
Decades-old discoveries in the field of artificial neurons are now transforming the computing industry by bringing massive disruption. Not to mention that AI capabilities are fueling innovation at an unprecedented rate and quantum leaps have happened in the quality of a multitude of everyday technologies. Most obviously, the speech-recognition systems on our smart devices work more flawlessly than they used to. Nowadays, when you use a voice command to connect with your spouse, you reach them and not your angry boss!
Deep Learning is an exciting tool that is supporting a host of industries creating cutting-edge AI applications, right from self-driving cars to speech-recognition systems. – Andrew Ng, Chief Scientist at Baidu
In today’s milieu, one can seamlessly interact with computers by simply talking to them, whether it’s Amazon’s Alexa, Apple’s Siri, Microsoft’s Cortana or Google’s tremendous voice-responsive features. Machine translation and other forms of natural language processing have become far better with continuous advancements happening in the field of artificial intelligence. In line with voice recognition, advancements have also happened in the field of image recognition. Tech pioneers having prowess in deep learning, are building high-profile applications that have features that let you search or organize collections of images with no identifying labels. You can ask to be shown, all the ones that have snow in them or even something as subtle as say the shadow of buildings.
Tech behemoths are increasingly aligning towards deep learning to unleash improvements in robotics, autonomous drones, and of course driver-less cars. For example, Tesla, Baidu and Alphabet are all testing prototypes of autonomous vehicles on roads. But, have you ever realized that all these breakthroughs are the same breakthrough? Deep Learning, that’s right!
The science behind deep learning, also referred to as deep neural networks dates back to the 1950s, however many of the breakthrough researches and inventions happened in 1980s and 1990s. The most exciting thing about the neural network is that no human programmed a computer to perform any of the feats mentioned above. In fact, the programmers fed a computer with a learning algorithm, exposed it to zettabytes of data (in form of audio, video and images) to train it, and then allowed the computer to figure out for itself- how to identify specific objects, words, images, etc.
The Bottom Line
Evolutions and advancements in raw computing power have made deep learning a reality and not just an academic thing. Research Firm CB Insights proclaims that equity funding of AI startup companies reached an all-time high last quarter of more than $1 billion. Venture Capitalists who weren’t even aware of the deep learning technology five years back, today are circumspect about startups that don’t have expertise in it. We are now living in a world where it is going to be inevitable for tech-firms building high-profile software applications to not have a deep learning arm. The day is not far when people will demand, “where is your natural language processing version?” or “How do I talk to your application? Because I don’t want to tab across menus.” Thus, it is needless to say that deep learning will soon have a major influence in all aspects of our life and the more it’s used the more charge it will get.