Not too long ago it was often said that computer vision could not compete with the visual abilities of a one-year-old. That is no longer true: computers can now recognize objects in images about as well as most adults can, and there are computerized cars on the road that drive themselves more safely than an average sixteen-year-old could. And rather than being told how to see or drive, computers have learned from experience, following a path that nature took millions of years ago. What is fueling these advances is gushers of data. Data are the new oil. Learning algorithms are refineries that extract information from raw data; information can be used to create knowledge; knowledge leads to understanding; and understanding leads to wisdom. Welcome to the brave new world of deep learning.
Oil has traditionally been considered one of the most valuable physical assets for the last few centuries. But this important commodity may have a new replacement: Data.
The arrival of the computer and subsequent evolution of internet has created a human reliance on technology. It has given birth to the importance of data. The top five giants of the tech world – Apple, Amazon, Facebook, Google, and Microsoft – know more about our daily interaction with gadgets than we ever will. These companies are collecting vast amounts of data from tens of millions of users every single day.
Deep learning is a branch of machine learning that has its roots in mathematics, computer science, and neuroscience. Deep networks learn from data the way that babies learn from the world around them, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. The origin of deep learning goes back to the birth of artificial intelligence in the 1950s, when there were two competing visions for how to create an AI: one vision was based on logic and computer programs, which dominated AI for decades; the other was based on learning directly from data, which took much longer to mature.
In the twentieth century, when computers were puny and data storage was expensive by today’s standards, logic was an efficient way to solve problems. Skilled programmers wrote a different program for each problem, and the bigger the problem, the bigger the program. Today computer power and big data are abundant and solving problems using learning algorithms is faster, more accurate, and more efficient. The same learning algorithm can be used to solve many difficult problems; its solutions are much less labor intensive than writing a different program for every problem.
Data is to the Information Age as is Oil to the Industrial Age.
How we make products, solve human problems, and use data in a constructive way will define the next wave of technology. Oil has evolved the world into a better place by creating an enormous amount of wealth and prosperity. Data perhaps holds the similar potential and is already responsible for creating four of the five most valuable brands in the world, led by Google.
Data has become the most valuable resource on the planet. However, it needs to be ethically extracted, refined, distributed and monetized. Like the way oil has driven growth and produced wealth for powerful nations, the next wave of growth will be data driven marketing agencies.