The Future of Artificial Intelligence and Machine Learning
Machine learning and deep learning have similar origins within computer science, employing a lot of the same concepts and method. Essentially, machine learning is an product of artificial intelligence that allows a system to obtain knowledge with the use of a supervised learning experience. The process, in a nutshell, goes like this: a human being inputs data for analysis and offers error-correcting feedback which enables the system to correct itself. On the other hand, deep learning can do this with little to no human supervision.
Machine learning is already a major component of people’s daily lives. Speaking to your phone, for example, through Google Now, Siri, or Cortana, was made possible by machine learning. However, machine learning is still in its early stages. There is a lot that machine learning is expected to do in the future, and tech companies are spending millions in research and development to make computers smarter than they are now.
Artificial intelligence is believed to be the next big thing. Right now, numerous companies are using it to power products and services including automated cars, personalized learning, chatbots, sports, and many others. Machine learning has shown promise that it will continue to transform a lot of industries, including transportation and education. In fact, experts predict that automated transport is not the far into the future. Because human error is a huge factor when it comes to accidents and fatalities on the road, automated driving is expected to reduce injuries and deaths.
Augmentation is another hot topic for machine learning. Experts believe that machine learning can be used to boost human intelligence and improve the brain’s cognitive power. Another area where artificial intelligence shows considerable promise is the job market. Dangerous jobs are predicted to become obsolete, which AI replacing most of them. With more processing power, AI can also possibly be used to address social issues like climate change, the prediction of natural calamities, healthcare, and more.
Costs of Machine Learning Development
Google recently paid a staggering $400 million for a London-based specialist in machine learning research, DeepMind. The head of research for Microsoft also went on record to declare that world-class deep learning experts can expect to earn seven-figure salaries in today’s technological environment. These are just some examples of how much tech companies are willing to pay to further their machine learning and AI research. However, machine learning research and development does not always come at this steep price.
Because of the decreasing price of computing power, machine learning is quickly turning into a commercial reality. With the increasing strides being made in cloud technology and the application of the graphic processing units (GPU) to power the neural networks which are essential for machine learning research, the entire field is accessible even to those companies who do not have limitless budgets.
The Human Factor
Machine learning is well-known for detecting patterns and integrating sizable quantities of data. This is useful, especially when it comes to identifying and benefitting from consumer behavior. However, while human behavior can be fairly predictable, there is still a lot of randomness in it. When dealing with other people, for instance, most of us are experts at this, but there are certain aspects of it where technology may falter. This is also why when people deal with customer service, most would rather hear a human voice instead of canned responses from a machine.