How Machine Learning is helping business grow in market?

The emerging technologies have significantly helped the businesses to enhance their capabilities and achieve better results. Especially the futuristic technologies like AI (Artificial Intelligence) and ML (Machine Learning) have been offering many benefits to the progressive businesses. While still in their initial stage the ML and AI have already started proactively supporting the businesses in terms of saving time and efforts and increasing productivity. One of the major difference between the traditional technology and new age technology like ML and AI is that the former works as per the human instructions while the latter (ML, AI and others) enjoy an extended independence, need much less human intervention and can learn and evolve over the period of time to improve their performance. Today we will concentrate on Machine learning and discuss the various ways in which it has already started benefiting the businesses.



Machine Learning VS Artificial Intelligence – What is the difference?

Many people still have a notion that AI and ML is the same thing. However, if we will analyze deeply we will observe that there is a clear difference between the two. Let us know the definition of AI and ML and then talk about the differences:

• In simple words the concept and method of imparting human-like intelligence to the computers is known as artificial intelligence. It includes the aspects like recognizing speech, taking crucial decisions, advanced visual perception, logical language translation capabilities etc.
• Machine learning is a branch of AI that empowers the system to evolve with time by learning constantly out of its own experiences and adopting tailors its functionalities to deliver better output/benefits.

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Here are the operational and key difference between Artificial Intelligence and Machine Learning:

• AI can work smartly to increase the opportunities of success while ML uses the data to learn from it and increase the accuracy of operations
• AI adopts the key qualities of natural intelligence to offer dynamic capabilities for solving complicated and tricky issues whereas ML enhances the overall machine performance for a specific task by utilizing the relevant data on that task.
• AI can learn to take independent decisions while ML offers capabilities to the machines to learn from the data??

Automating need-based solutions:

The progressive serious businesses are constantly seeking the precise ways to automate the specific parts of their operations by strategically implementing Machine Learning that will eventually help in focused development and purpose-specific implementation of ML thus stabilizing its position as a need-based solution.

• ML can help the insurance companies offer need-based dynamic suggestions to the targeted audience that auto updates with time-based on their current status information (age, health, income etc.) that precisely fits their contemporary requirements. It can increase conversion opportunities and also help clients with friendly insurance products.
• Instead of relying on the specific and static functionalities of ML, the companies can enjoy a better and improved functionality as their operations evolve in the future. It would be a great asset for the start-ups and growing businesses.

For instance, a company named Geico has integrated machine learning to enhance their production procedures with the help of Geico VA. The result is increased productivity and reduced time to market that translates to better business benefits.

Better environment for development of Machine Learning:

In the modern times the data capturing capabilities has been experiencing a keen growth. The computational power has developed manifolds to capture a massive volume of data from diverse media (audio, images, video etc.) and intelligently categorizing the same. It has offered a better option to the businesses to quickly store more data and further enhance its usefulness.

• The availability of high amount of quality data will also enhance the real-time efficiency of ML and increase its practical usage in day to day business operations while also ensuring its fast, healthy and sustainable evolution.

Better technology for supporting multiple analytical processes:

One of the major concerns of the businesses today is how to support the increasing workload of analytical processes that are required for developing the machine learning capabilities and offering real-time purpose specific benefits.

• Thanks to the innovations like Run time decision framework and analytics workbench the businesses are now technically capable to boost the development of machine learning, leverage best benefits out of analytical processing and take precise decisions.
• It will also help the professionals come up with innovative machine learning solutions that can be instantly used by the businesses to accelerate their efficiency.

Large scale deployment of Machine Learning:

The increase competency and pace of large scale ML deployment powered by latest developments in run time decision framework is another positive point that enhances the business value of machine learning.

It can help businesses in multiple ways:

• Efficiently entertaining multiple requests from diverse channels
• Prioritizing execution of tasks depending upon urgency, ease, and available bandwidth
• Better adoption of predictive models by choosing the best fit among multiple choices
• Helping business takes urgent decisions on critical matters in real time without compromising with logical accuracy
• Facebook’s re-targeting ads are excellent examples of ML’s importance in the field of marketing. Using the ML capabilities the Facebook displays the most relevant ads on users’ timeline based on the websites that they just browsed. It increases the conversion opportunities for the businesses.

Increased productivity and cost efficiency:

With the help of advanced learning capabilities the machines can dynamically increase there efficiency over a period of time by utilizing deep learning technology. It increases the cost efficiency by helping the businesses manufacture more products in less period of time.

• Additionally, it also saves the efforts and time of the production staff that they can utilize for other core objectives.
• It helps businesses to an enhance theory productivity increase the profitability by slashing costs and achieve a competitive market edge.

 

Conclusion:

Machine learning is an advanced technology that allows the machines to use the available data and instances for evolving and enhancing their performance with times. A good number of progressive companies have already adopted machine learning to augment their productivity and improve their performance over a period of time. In this blog, we have discussed various instances and capabilities of machine learning that are actively helping the businesses across the globe.

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