AI (Artificial Intelligence), ML(Machine learning) and Data Science. These are under the same umbrella. Because everything is interlinked. There is a mutual dependency between the three of them.
Coming to data science we need to give a solution for complex business problems. Data Science is a multifaceted area of work that includes processes to collect, prepare, analyze, visualize and model data that generate useful knowledge to understand complex problems and help in decision making. These data are often unstructured and miscellaneous. Many cases set of data in large volumes. Depends on the complexity of the business problem it requires artificial intelligence techniques and innovative architecture to extract relevant knowledge.
The hypothesis of AI – Data science:
knowledge >planning>operation>outcome for perception
Data Science uses different concepts for defining the patterns to solve business problems. For instance, in the first step, i.e. Knowledge(perception), data scientist need to getting knowledge on given data to predict patterns with the help of the data. Similarly, in the next step, i.e. planning, there are two aspects:
a) Finding all possible solutions
the initial step is to determine all possible metrics which are suitable forgive business problem. We Need to solve the problem in all possible metrics. Finally, choose one of the best solutions among all solutions
b) Finding the best solution among all solutions
Generally finding a solution is very complicated without AI. AI has some predefined functions. We can call the functions when it is in need. And AI reduces time complexity to solve the particular business problems.
I collected a few of the expert opinions on how AI & Data science is interlinked
Selva perumal Pragasam studied Computer Science at Ph.D. Degrees in Computer Science
1) The main aim of AI is to infuse intelligence to machines. This includes Computer Vision (to help agents to view the world around it), Language Processing (Speech and text processing) to help the agent to understand human text and speech and also to respond to them more naturally. Machine Learning helps the agents to learn and improve their performance just like how humans do.
All these fields together constitute Artificial Intelligence whose aim is to mimic human intelligence or in other words, to infuse intelligence to agents(robots) so that it will replace humans in every aspect.
Data Mining, Data Engineering, Data Science all use statistical learning algorithms (Machine learning) to extract intelligence from the data. For an agent’s perspective, this intelligence may help in improving its performance.
Paul King, computer science at Harvard, the tech industry Data science is the use of statistical methods to find patterns in data.
Statistical machine learning uses the same math as data science but integrates it into algorithms that get better on their own.
Artificial intelligence is the general field of “intelligent-seeming algorithms” of which machine learning is the leading frontier at the moment.
Rahul Baxi Human intelligence builds upon what we read, observe, learn, sense and experience. It’s our ability to store a large amount of data, accumulated over years and co-relating a few data points to answer a certain question, that makes us intelligent. You, for instance, figured out quora would be a good place to get your answer.
For machines to replicate human intelligence, they’ll need to absorb a large amount of data and access certain co-relating data points at a given point of time to make an intelligent decision.
Data science helps with the “co-relation” of data, combining multiple data points to get meaningful information from a vast amount of data. A machine, with such capabilities, will make for a good starting point for artificial intelligence.
Google’s self-driving cars gather a large amount of data by monitoring the surrounding environment through an array of sensors: infrared cameras, proximity sensors, to name a few. The machine driving the car, co-relates information gathered from this large amount of data to make an intelligent decision.