Artificial Intelligence is Not the Future, It’s Now

Artificial intelligence may be the most transformative and disruptive advancement since the Industrial Revolution. After decades of hype and disappointment, AI is poised to fuel the next wave of innovation, and potentially provide unprecedented opportunities for companies and investors. 

I wondered, how predictions can take shapes; from AI to deep learning, and how it will remake our world, we thought robots are future? but all of that is part of our today. Thanks to advances in artificial intelligence, machines can now perform many tasks and play games. Machines, data and people are converging. I refer to this quote by Pedro Domingos (Author "The Master Algorithm") - “Machine learning is the automation of discovery — computers learning by themselves by generalizing from data instead of having to be programmed by us.” 

Can machines think? That’s the question Alan Turing posed in 1950. Turing, an English scientist, is considered by many to be the father of computer science and a key figure in artificial intelligence.

Today, the answer to his question is getting closer to yes, depending on how you define thinking. But during the past few years, huge strides have been made toward machines that can figure things out without being told what to do. Machines are using reason, logic and experience and tons of data in ways that are remarkably human and, for some, alarming.

These machines are already transforming manufacturing, transportation, health care and hundreds of other elements of daily life on both personal and industrial levels. They are in use in schools, homes, hospitals, and cars, and they are changing the way the world works.

For some, machines are a threat, especially to jobs. But AI also has the potential to improve the standard of living around the globe, provide companies with new profit opportunities and reward investors.

“There are periods of fundamental change that can transform the way we live and work,” says portfolio manager Rob Lovelace. “Today it seems as if we are in the middle of another revolution, and clearly these changes pose significant challenges and opportunities for long- term investors.”

Artificial intelligence has been around as a scientific concept since the 1950s, going through several periods of boom and bust. The term refers to a collection of technologies that enables computers to simulate elements of human thinking. But for years, computers have had to be programmed in painstaking detail.

Things have changed. Through “machine learning,” a subset of AI, computers can learn from data without being explicitly programmed. They can teach themselves by analyzing massive amounts of data from the web, smartphones and other Internet-connected devices. Also, processing power has soared. Nearly everything online involves machine learning. Netflix, for example, uses it to recommend movies.

Recently, deep learning has taken AI to the next level. Deep learning is a type of machine learning that uses artificial neural networks that loosely mimic how brains work. A machine can now train itself to perform tasks, such as speech or image recognition, without being programmed to do so. Rather than having to be spoon- fed information for every eventuality, machines can analyze vast amounts of data using layers of artificial neural networks.

Whether that’s thinking or not, machines can now figure many things out for themselves. 

Artificial Intelligence Makes the Next Great Leap. AI May Be the Most Disruptive Change Since the Industrial Revolution 

• Mention artificial intelligence and the first thing that comes to mind is probably a movie — Terminator, Westworld, 2001: A Space Odyssey. In almost each story, the computer or the robot ends up going haywire. So it’s not surprising that many people are ambivalent about AI. But that’s fiction. The fact is most people already have a working relationship with a machine that does some thinking and talks to them — their smartphone. Going forward, AI is going to be a bigger part of the way people work, play and learn. 
• Instead of the dystopian future that’s often depicted in movies, the age of artificial intelligence is more likely to feature advances that were once considered futuristic becoming commonplace, such as driverless cars and machines that can converse with humans. Indeed, there seems to be little cause for concern that AI is an imminent threat to humankind. In many ways, the technology is already part of daily life, and it’s reshaping life in schools, homes, and hospitals. Actually, AI has been shaping society for years. 
• Many AI applications are likely to increase productivity, improve transportation and enhance the quality of life for millions. But this technology will also create profound challenges. While it may increase productivity, it will replace some jobs and impact income. But, in many cases, AI will be critical to people’s futures, and employees will be working with AI, not replaced by it. In fact, Hollywood now uses AI technologies to help bring its man-versus-machine movies to the screen. 

 Artificial Intelligence Comes of Age - AI Moves Beyond Patchy and Unpredictable, Thanks to Machine Learning and Deep Learning.

• Artificial intelligence is usually associated with the future, but as a scientific concept, AI dates from about World War II. Since then, artificial intelligence has gone through some booms, but mostly busts. Now, after decades of ups and downs, artificial intelligence is getting smarter. The credit goes to the development of machine learning and deep learning, as well as the increasing capability of microchips, an explosion in the amount of available information, and the ability of supercomputers to analyze data. 
• Machine learning is a field of study that gives computers the ability to learn without being explicitly programmed. Machine learning enables such features as Amazon’s recommendation algorithm. It’s similar to data mining. Machine learn- ing uses data to detect patterns and adjust program actions accordingly — essentially the machine draws an inference from the data. Facebook’s News Feed uses machine learning to personalize each member’s feed, and make changes when exposed to new data. 
• Deep learning is a type of machine learning that uses artificial neural net- works that loosely mimic how our brains work. The machine thinks in layers, with each layer capable of analyzing data at a deeper level of complexity and abstraction. Deep learning requires tremendous amounts of data and processing power, neither of which were available until the era of big data and cloud computing. Now, thanks to deep learning, AI is moving closer to delivering human-level capabilities envisioned decades ago. 

The Age of Automation Has Arrived - From Factory Floors to Financial Services, AI and Robotics Are Redefining How Work Gets Done 

• The robots aren’t coming — they’re already here. Industrial robots have been around in the thousands for decades. Now, Agri bots, service robots, Robo-advisors and co-bots are becoming part of the landscape. Soon, various forms of automation are likely to roll or walk, out of laboratories and into the real world. It’s been predicted for years, but the coming age of automation is starting to happen now thanks to advances in sensors, hydraulics, and artificial intelligence, mostly in the field of machine learning. 
• Robo-advisors are an example of technological disruption in wealth management. These machines provide online and automated portfolio management services. This is done through the use of algorithms, meaning human involvement is kept to a minimum. Though new and untested, and clearly lacking in the human touch a financial advisor provides, Robo-advisors are becoming increasingly widespread. Assets con- trolled by Robo-advisors could grow to more than $250 billion by 2020.
• The accelerating pace of automation has sent robot sales soaring. Between 2010 and 2015, sales of industrial robots increased 16% a year. In 2015, nearly 254,000 industrial robots were sold worldwide. Still, only about 10% of manufacturing is done by robots. By 2025, robots will account for 25% of manufacturing. This paradigm shift potentially may be among the most disruptive in history, with the possible displacement of human labor presenting a profound challenge for business and society. 

The Internet of Things — Connecting Machines, Data and People - The Convergence of Big Data, Machine Learning, and Cloud Computing Is Transformative 

• How many machines will be connected to the internet by 2020? General Electric puts the number at 50 billion. Industrial equipment, cars, home appliances, even heart monitors — seemingly everything will be tied together via the Internet of Things (IoT). IoT is a network of the internet- connected physical objects that contain sensors. The technology allows them to communicate and transfer data over a network. The data can then be used for purposes ranging from monitoring crops to synching traffic signals.
• IoT is another example of a decades-old idea that now has practical applications thanks to big data and the increase in computing power to analyze information. Many businesses have already embraced IoT for cost savings and data collection, and IoT has the potential to transform the lives of individuals as significantly as the spread of mobile internet. IoT now seems on the brink of having a profound impact on industries from manufacturing to health care, and particularly transportation.
• Autonomous vehicles will be rolling examples of IoT. They will use an array of sensors and massive amounts of data to navigate roads without a human driver. The cars represent an opportunity for companies that haven’t been part of the auto industry. Companies working on elements of the driverless car include IBM, Intel, Analog Devices, Texas Instruments and Maxim Integrated Products. Many other companies worldwide are developing cameras, radars, sensors and other equipment. They include Delphi, Continental, TRW, DENSO, and Autoliv.