By combining artificial intelligence (AI) and big data, organizations can see and predict upcoming trends in key sectors including business, technology, finance and healthcare.
AI is the simulation of human intelligence by computers. By applying machine learning algorithms, we can create “intelligent” machines, which can use cognitive reasoning to make decisions based on the data provided to them. Big Data, on the other hand, is an umbrella term for computational strategies and techniques applied to large sets of data to extract insights. Big Data technology includes capturing and storing data, then analyzing it to make strategic decisions and improve business results. Most companies deploy Big Data and AI in silos structure their existing datasets and develop machines capable of thinking for themselves. But big data is actually the raw material of AI. So when big data meets AI, it has the potential to transform both the way data is structured and the way machines learn.
What is artificial intelligence and its subsets?
Artificial intelligence (AI) harnesses computers and machines to mimic the problem-solving and decision-making abilities of the human mind.
It’s a constellation of many different technologies working together to enable machines to sense, understand, act and learn with human-like levels of intelligence.
Here are the subsets of artificial intelligence:
- Machine learning.
- Deep learning.
- Natural language processing.
- expert system.
- Industrial vision.
- Speech recognition.
What is Big Data and its 3Vs?
Big data is data that contains a greater variety, arriving in increasing volumes and with greater speed.
Although the concept of Big Data itself is relatively new, the origins of big data can be traced back to the 1960s and 1970s when the world of data was just beginning with the first data centers and the development of the database. relational.
Benefits of Big Data and Artificial Intelligence in the Digital Age
Businesses analyze and manage large sets of data on a daily basis. Customer information, employee details, business statistics all put together can be a huge collection of unstructured data that can be sorted and studied for business optimization. Big Data provides solutions to collect and store data in a robust way, while AI, with its machine learning techniques, learns from data sets to make better decisions in the future.
Here are the benefits of Big Data:
Big Data reduces business costs.
Big Data increases efficiency.
Big Data improves pricing.
Big Data provides more tools to compete with large companies.
Big data allows organizations to focus on local preferences.
Big Data helps increase sales and loyalty.
Big data allows you to hire the right employees.
Retail brand Walmart is already using big data with AI to overhaul its business structure. With more than millions of customers accessing their online and offline stores every day, Walmart collects petabytes of customer data. Big data analysts work on the vast dataset, helping their machine learning algorithms master decision-making skills. Studying trending products on the site, patterns of customer buying habits, and relationships between demand and supply of goods helped Walmart redesign its website and inventory to meet customer needs. , thus stimulating its activity.
AI algorithms usually work on sample datasets up to the early stages of machine learning. However, pairing the algorithms with live data allows machines to learn from real datasets rather than samples. Thus, we can effectively train our machines to make better decisions already in the learning phase.
A great example of this comes from the meteorology department. Meteorological observatory servers receive data in the form of text, images and video from satellites, weather stations and relay cards around the world. Big data coupled with AI is used in these fields to efficiently store data and then process it using image and video processing techniques for weather forecasting.
Here are the benefits of artificial intelligence:
1) Fewer human errors: There is less room for error with artificial intelligence.
2) Do more complex tasks: Artificial intelligence can accomplish a more laborious task with extra work and with greater responsibility.
3) Available 24/7: Educational institutions and help desks receive many questions and issues that can be addressed effectively using AI.
4) Provide digital assistance: Virtual assistants inside connected smartphones, PCs or home speakers, such as Apple’s Siri, Microsoft’s Cortana, Google’s Google Now, Samsung’s Galaxy S8’s Bixby and Amazon’s Alexa, provide information contextual.
5) Assist humans in repetitive tasks: In banks, one often sees many document checks to get a loan which is a repetitive task for the bank owner. By using AI Cognitive Automation, the owner can speed up the document verification process which will benefit both the customers and the owner.
6) More productive: Emotions are not associated with AI robots and therefore mood does not impede effectiveness. Thus, they are always productive.
7) Educate the next generation: Nowadays, healthcare professionals are trained with artificial surgery simulators. It uses apps that help detect and monitor neurological disorders and boost brain function.
8) Good Decision Making: The integration of AI tools in the business world has improved the efficiency of organizations.
Although computers cannot cognitively match human brains, they are essential for sorting and organizing the vast sets of data we process in the modern world. By merging AI and Big Data, we can get a real-time structured database, which can further be used in a variety of applications. Although the merging of these two fields is still ongoing, we can expect rapid breakthroughs in the way we deal with large sets of data in business and in daily life.