AI/ML is a recreation

 AI/ML is a high-end, introductory blog. It covers the precepts of machine learning through interactive tutorials and practical examples, which make it easier to see the useful applications to different businesses and industries.

AI/ML stands for artificial intelligence (AI) and machine learning (ML). Artificial intelligence (AI) is the mimicking of human intelligence by machines, especially computer systems. Machine learning helps in developing that learning to make machines capable of simulating human intelligence, so AI and ML both complement each other. AI and machine learning have ushered in a new era in computer science and data processing that is rapidly transforming a wide range of industries.

As businesses and other organizations undergo digital transformation, they’re faced with an increasing surge of data that is incredibly valuable and increasingly difficult to collect, process, and analyze.

Why is AI or ML decisive?

It’s very obvious nowadays that data is a business asset; data is increasing and being stored at an exponential rate. Almost every organization is collecting data, and of course, a flood of data is useless if we don’t manage it. It will be a waste of expensive assets. AI/ML has the potential to revolutionize all aspects of life by assisting people and achieving measurable results, such as:

• improving medical diagnosis.
• Optimizing business
• Automating business operations
• Increasing revenue
• Minimising costs
• Fraud Checking
• Increasing customer satisfaction
• Voice Assistant
• Automated Machinery.

 

AI/ML examples and use cases

It all sounds prominent, of course, but on the abstract, formal side of things, let’s take a look at a few use cases and examples of AI and ML being a big part of the game-changer.

Medical

AI and machine learning (ML) play an important role in the health sector, improving clinical efficiency, diagnosis speed, and patient data analysis.It is also helping in the analysis of new diseases. It is being used in the medical field to find cures and vaccines. COVID is a burning example of this, where there was no hope of survival. Again, AI and ML played a vital role in analyzing and predicting its symptoms. India developed Covishield and Covaxin. With this medical technology, a chatbot was created where patients and doctors could interact, and finally, the pandemic of 2020–2022 was managed with the help of this technology.

Telecommunications

The telecommunications industry is committed to the responsible use of AI and ML to gain insight into customer behaviour, enhance customer experiences, and optimize 5G network performance, among other things. Some telecom companies use a chatbot to look after customer complaints and try to reduce them by fixing them.

Insurance

The insurance organisation uses AI and machine learning for a variety of applications, including automating claims processing and providing consumption-based insurance services. It helps in designing models to predict significant issues like insurance clients' satisfaction.

Financial Services

Financial services are also taking an edge over this. The benefit of using AI and ML is that it minimises error and increases the chance of accuracy. To handle financial firms and enterprises, we need to tackle this problem with efficient solutions like the artificial intelligence model. Issues such as an increase or decrease in the repo rate and monitoring the inflammation rate will also aid in forecasting the country's economy. Recently, many countries have faced an economic crisis. We can use these data to develop a model and prevent an economic disaster like that in Sri Lanka.

Automotive

The automotive industry has seen significant change and turmoil in the past few years with the advent of electric and autonomous vehicles. Tesla cars in India have used the approach of "imitation learning," in which an algorithm learns from the decisions, reactions, and movements of millions of actual drivers around the world. Their tracking system is incredibly smart. Predictive maintenance models and a wide array of other disruptive trends across the industry have been developed using this technology.

Energy

Energy utilities around the world are also in the midst of an industrial transformation, with new ways of generating, storing, distributing, and using energy changing the competitive landscape. As the climate is changing dramatically and it is now a global concern to take some measures, AI and machine learning can also help in analysing the situation and making predictions so that we can reduce our carbon stock and increase the use of ethanol and hydrogen. It can be very helpful in managing the development of new energy resources. It can be helpful in the development of hydrogen and ethanol power plants and their automation. AI and ML will develop a predictive maintenance and optimised consumption cost model.

Future Project

Amazon and Google Search are deeply involved in it to develop products for customers in every field of life. The search results and recommended model show that the tremendous use of AI and ML has not only optimized costs but also improved customer and organizational relationships on a wide scale. Aside from automation, AI and ML have entered a new field such as space research, with scientists using AI and ML to develop models for new research such as finding water and oxygen on planets.

AI and ML aren’t new. However, the big data space is reviving this topic, with more and more organizations relying on ML models to scale their operations and help people work better and faster. This is creating widespread interest in related topics with the customer and across business lines and job roles as enterprises understand the value of AI and ML. To make a disruptive organizational impact, we should understand and trust AI and ML and help with recreation.

https://www.jimsgn.org/

 Sony Kumari

Assistant Professor

CSE Department