90% of the world’s data has been generated in the last two years. Thanks to improved processing speeds, computers can easily process this huge amount of data and data scientists can make sense out of it. Data Science is a field of Computer Science which focuses on extracting knowledge and insights from data. It then uses this data to solve real-world problems. Data Science focuses on using statistical methods to find patterns in data. Statistical machine learning uses the same math as data science; integrating the math into algorithms that can learn on their own to make predictions. Data Science is not just Machine Learning, it also includes data mining, cleaning data, and making sense out of the data. The different data science domains include statistics, data visualization, data mining, database and data preprocessing, neurocomputing, machine learning and pattern recognition. Neurocomputing, machine learning and pattern recognition usually fall under a single umbrella.
Artificial intelligence is an area of Computer Science which emphasizes on the creation of intelligent machines that work and react like humans. Artificial intelligence does not simply program a car to obey traffic signals, artificial intelligence also enables the car to make decisions when there are signs of a road rage. It is one of the most important parts of the technology industry and an exciting field to work in today. There is a vast research going on in this field and it can definitely be thought of as the future of Computer Science. Right from credit-card fraud detection, email spam filtering, playing games, online customer support using bots to SIRI, Cortana, Amazon Alexa, IBM Watson, Google Assistant and self-driving cars, AI is everywhere.
Machine Learning can be thought of as a branch of AI that works best with Data Science. Deep learning is a branch of Machine Learning. “Don’t touch that vessel because it is hot” is Machine Learning. Learning from the above sentence to conclude “You should not touch hot things” is Deep Learning. The main question here is: why are more and more data scientists joining AI companies? As already stated, data science, machine learning, deep learning and artificial intelligence are all correlated fields. In fact, machine learning which uses data science can be thought as a branch of Artificial Intelligence. So, Artificial Intelligence can be thought as the root of the tree with data science and machine learning as the descendent nodes.
The migration of data scientists towards AI companies is like moving from a more specific field to a more general field. AI is broadly divided into two categories; narrow/applied AI and general purpose AI of which machine learning is an important part. Data Science and Machine Learning deal with deriving insights from data, recognizing patterns, making predictions with the use of statistics. AI takes this to another level by using the output generated by machine learning to solve more real-world complex problems. Machine Learning is a part of AI, but AI has machine learning and much more. For example, the self-driving cars that describe themselves to be using AI are actually using very little machine learning and are mostly using rule-based systems.
Many forward thinking data scientists are turning towards Artificial Intelligence today. The main reason being, AI is everywhere and it's practice included everything a data scientist could want: statistics, machine learning and deep learning. As Elon Musk of Tesla rightly said “Humans must merge with machines or become irrelevant”. AI is the future and its importance is being realized today. Instead of concentrating just on one branch of AI (i.e. Data Science and Machine Learning), professional data scientists prefer to have a range of options to work on. Joining an AI company does not take one away from the minutia of Machine Learning or Data Science, instead it helps an individual grow professionally and apply his or her Data Science knowledge to a vast range of problems.
Artificial intelligence is a vast field for research and learning, it will take over the world in less than a decade. Data Science, Machine Learning, Deep Learning coupled with Artificial Intelligence are used for error reduction, difficult explorations (like exploring ocean floors), day to day applications like Cortana, Siri, GPS and many more, digital assistants, repetitive tasks, and medical applications. Changes are inevitable, and the kind of research happening in this field is what dragging most of the Data Scientists towards the AI companies.