Artificial Intelligence, Machine Learning and Deep Learning

Original article was published on Artificial Intelligence on Medium

Artificial Intelligence, Machine Learning and Deep Learning

Artificial intelligence is the act of computers simulating processes that are usually done by humans and encompasses both machine learning and deep learning. Machine learning is where machines learn by experience and acquire skills without direct programming/human involvement and deep learning is a subset of machine learning where algorithms that are inspired by the human brain act as artificial neural networks to engage with and learn from large amounts of data. The below chart, shows the relationship between these three fields:

Since 2015, artificial intelligence and the fields within it have grown rapidly. The main factors that led to advancements are the wide availability of GPU (graphic processing unit) accelerated computing and the increase in overall data. GPU accelerated computing is a new computing model that uses massively parallel graphics processors to spur applications that are also parallel in nature. An example of using GPUs is how scientists used them to do molecular scale simulations to determine the effectiveness of new drugs by visualizing human organs in 3D. Deep learning works similar to how the human mind processes experiences and uses them to learn how to perform a task more efficiently in the future. A deep learning algorithm, will perform a task repeatedly and tweak the process each time in an effort to improve the outcome. Since deep learning requires massive amounts of data to gain “experiences” from, the increase in data generated from human use of technology recently has really contributed to the growth of the field. The below chart gives an idea of how much data is being generated:

As artificial intelligence continues to grow, it will affect all industries. It’s already made a massive impact in some industries, while in others, it’s just starting its journey.

Entertainment: Netflix uses machine learning to create algorithms to recommend movies and shows based on a users history and interests.

Transportation: Autonomous cars are well on their way to being developed. It will take some time for them to be fully implemented, but the use of artificial intelligence has already started the process.

Education: While artificial intelligence hasn’t significantly affected this field quite yet, the possibilities of using virtual assistants to assist teachers and using facial recognitions to see if students are confused or are understanding the subject, have huge potential.

These are just a few examples of how artificial intelligence has begun to grow. It’s impossible to know exactly how much of an impact AI will have on the future, but with the amount of data being generated, it will only continue to grow.

Resources:

https://www.forbes.com/sites/bernardmarr/2018/10/01/what-is-deep-

learning-ai-a-simple-guide-with-8-practical-examples/#1c4c55748d4b

https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/