Artificial Intelligence Will Going to Play an Important Role in Future

The booming growth of machine learning and artificial intelligence (AI), like most transformational technologies, is both exciting and scary. It’s exciting to consider all the ways our lives may improve, from managing our calendars to making  medical diagnoses, but it’s scary to consider the social and personal implications — and particularly the implications for our careers. As machine learning continues to grow, we all need to develop new skills in order to differentiate ourselves. But which ones?

It’s long been known that AI and automation/robotics will change markets and workforces. Self-driving cars will force over three thousand truck drivers to seek new forms of employment, and robotic production lines like Tesla's will continue to eat away at manufacturing jobs, which are currently at 12 million and falling. But this is just the beginning of the disruption. As AI improves, which is happening quickly a much broader set of “thinking” rather than “doing” jobs will be affected. We’re talking about jobs, that, until the last few years, we couldn’t imagine being done without the participation of an actual, trained human being.  Jobs like teacher, doctor, financial advisor, stockbroker, marketer, and business consultant.

We can look at any number of occupations to see that this holds true.  Doctors perform tests, analyze the results, interpret the results to make a diagnosis, plan a course of treatment, and then work with the patient to make this treatment plan a reality.Financial advisers gather and analyze data about their clients and potential investment vehicles, interpret the implications given a variety of factors such as risk tolerance, recommend an investment strategy, and help their clients carry this strategy out over time.

Some people may say that we will never trust machines with important decisions such as the management of our health and money, but this is twentieth century thinking.  But a new generation is engaging with smart machines that they trust, and often prefer.  Further, it’s hard for anyone to argue with results.  IBM’s Watson is already cracking medical cases that stump doctors.It takes a person, however, to sit with a patient, understand their life situation (finances, family, quality of life, etc.), and help determine what treatment plan is optimal.

Don’t fight the progress of technology. Machine learning and AI have the ability to improve outcomes and lower cost — so don’t fight the robots. Welcome the change in our industry and work to make it fruitful and complementary.What we have to offer — what we can do better than any smart machine — is relate to the people around us.If we can be an outstanding motivator, manager, or listener, then we will still have a part to play as technology changes our industry.

Machine Learning

Nowadays, Machine Learning is the most popular growing technology. Machine Learning is a type of Artificial Intelligence that provides computers with the ability to learn without being explicitly programmed. Machine Learning focused on the development of computer programs that can change when exposed to new data.

The process of Machine Learning is similar to that of data mining. Both system search through data to look for patterns. However extracting data for humans comprehension as in the case in data mining application machine learning uses that data to detect pattern in data & adjust accordingly. Machine Learning algorithms are often categorized as being Supervised or Unsupervised. Supervised algorithms can apply what has been learned in the past to new data while Unsupervised algorithm can draw inference from data sheet.

                          

 How Machine Learning is different from Artificial Intelligence?

AI is a branch of computer science attempting to build machines capable of intelligent behavior, while Stanford University defines machine learning as "the science of getting computers to act without being explicitly programmed". You need AI researchers to build the smart machines, but you need  machine learning experts to make them truly intelligent. Google currently working on developing this machine learning; desperately pushing computers to learn the way a human would in order to progress what many are calling the next revolution in technology – machines that 'think' like human.

Over the past decade, machine learning has given us self driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. But how does it work?

Let’s take a very simplified example. When you make a typo, for instance, while searching in Google, it gives you the message: "Did you mean..."? This is the result of one of Google's machine learning algorithms; a system that detects what searches you make a couple seconds after making a certain search.

                          

For example, suppose you were searching for 'WIRED' on Google but accidentally typed 'Wored'. After the search, you'd probably realize you typed it wrong and you'd go back and search for 'WIRED' a couple of seconds later. Google’s algorithm recognizes that you searched for something a couple of seconds after searching something else, and it keeps this in mind for future users who make a similar typing mistake. As a result, Google 'learns' to correct it for you. While this is a very basic example, data scientists, developers, and researchers are using much more complex methods of machine learning to gain insights previously out of reach. 

AI is the science and machine learning is the algorithms that make the machines smarter. "AI is going to bring major shifts in society through developments in self-driving cars, medical image analysis, better medical diagnosis, and personalized medicine. And it will also be the backbone of many of the most innovative apps and services of tomorrow". But in order for AI to progress, machine learning must make big jumps in terms of performance, and this is rarely possible in the traditional high-performance computing world, where problems are well-defined and optimization work has already been happening for many years.

                             

Machine learning algorithms still have room for improvement, and that’s why a lot of the large technology companies are making it a central focus to their strategy, and working tirelessly to make it more intelligent, in order to push forward and create the next innovation, such as completely autonomous and 100 per cent safe self-driving cars.

Artificial Intelligence Will Predict how Scenes Will Play Out

A new artificial intelligence system can take still images and generate short videos that simulate what happens next similar to how humans can visually imagine how a scene will evolve, according to a new study.Humans intuitively understand how the world works, which makes it easier for people, as opposed to machines, to envision how a scene will play out. But objects in a still image could move and interact in a multitude of different ways, making it very hard for machines to accomplish this feat, the researchers said. But a new, so-called deep learning system was able to trick humans 20 per cent of the time when compared to real footage.Researchers at the Massachusetts Institute of Technology (MIT) pitted two neural network against each other, with one trying to distinguish real videos from machine-generated ones, and the other trying to create videos that were realistic enough to trick the first system.

Early Stages

Still, film directors probably don’t need to be too concerned about machines taking over their jobs yet — the videos were only 1 to 1.5 seconds long and were made at a resolution of 64 x 64 pixels. But the researchers said that the approach could eventually help robots and self driving cars navigation dynamic environments and interact with humans, or let Facebook automatically tag videos with labels describing what is happening.

The system is also able to learn unsupervised, the researchers said. This means that the two million videos — equivalent to about a year's worth of footage — that the system was trained on did not have to be labeled by a human, which dramatically reduces development time and makes it adaptable to new data.

AI Filmmakers

The MIT team is not the first to attempt to use Artificial Intelligence  to generate video from scratch. But, previous approaches have tended to build video up frame by frame, the researchers said, which allows errors to accumulate at each stage. Instead, the new method processes the entire scene at once — normally 32 frames in one go.

The results are far from perfect, though. Often, objects in the foreground appear larger than they should, and humans can appear in the footage as blurry blobs, the researchers said. Objects can also disappear from a scene and others can appear out of nowhere, they added.

"The computer model starts off knowing nothing about the world. It has to learn what people look like, how objects move and what might happen," Vondrick said. "The model hasn't completely learned these things yet. Expanding its ability to understand high-level concepts like objects will dramatically improve the generations."

Another big challenge moving forward will be to create longer videos, because that will require the system to track more relationships between objects in the scene and for a longer time, according to Vondrick.

"To overcome this, it might be good to add human input to help the system understand elements of the scene that would be difficult for it to learn on its own," he said.

Intelligent Automation:A new era of Innovation

• Automation: Automation is the use of various Control System for operating equipment such as machinery, processes in factories, boilers and heat treating ovens, switching on telephone networks, steering and stabilization of ships, aircraft and other applications with minimal or reduced human intervention.The biggest benefit of automation is that it saves labor; however, it is also used to save energy and materials and to improve quality, accuracy and precision.Automation has been achieved by various means including mechanical, hydraulic, pneumatic, electrical, electronic devices and computers, usually in combination. Complicated systems, such as modern factories, airplanes and ships typically use all these combined techniques.
• Artificial Intelligence:Artificial intelligence (AI) is the intelligence exhibited by machines. In computer science, an ideal "intelligent" machine is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at an arbitrary goal.
• Intelligent Automation:It is nothing but combination of artificial intelligence and automation.Intelligent Automation marries artificial intelligence-including natural language processing machine learning and machine vision with automation.Artificial intelligence and automation are hardly new,but the technologies have progressed substantially in recent years.Some intelligent automation technologies such as those powering a new generation of collaborative robots and Google's self driving cars,analyze and respond to a stream of situational data from sensors.

Nowadays companies in nearly every sector are investing in intelligent automation.There are three primary forms of intelligent automation applications deciders,doers and movers

1. Deciders are information system that automate decision making
2. Doers,such as collaborative robots,automate physical tasks
3. Movers use sensors and artificial intelligence to automate transportation 

Advances in artificial intelligence,robotics and automation,supported by substantial capital investments,are fueling a new era of intelligent automation,which likely to become an important driver of organizational performance in the years to come.It is important for companies in all sectors to understand and adopt intelligent automation,or risk falling behind

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