“The progress we’ve made from a 26% error in 2011 to a 3% error in 2016 is hugely impactful. The way I like to think is, computers have now evolved eyes that work.” — Jeff Dean
These words from prominent computer scientist and the head of Google’s AI division, Jeff Dean, symbolize the technological behemoth that Machine Learning has become in the current computing world.
From a concept that was perceived to be other-worldly, today, Machine Learning has become widespread in its usage and elementary in understanding by millions of computer-savvy technologists who are raving no end about it and are placing the usage of Machine Learning at the heart of their business and technological processes for now and the foreseeable future.
Machine Learning is a subset of Artificial intelligence and has been constantly proving itself to be an advantage to companies. Even if it’s a startup or a multinational company, Machine learning is helping companies become efficient, smart, and grow successfully.
This gives us the idea of how Machine Learning is going to be one of the necessities in every industry around the world in the near future. There has been a breakthrough in the field of Artificial Intelligence that has been made by harnessing the likes of Machine Learning and Deep Learning.
In this article, we will be focusing on what’s the potential future of Machine Learning is and where its effects are going to be felt more. By the end of this blog, you will be learning about it.
- Future scope of machine learning
- Applications of machine learning in various industries
- Career opportunities in machine learning
Future of Machine Learning in various industries:
Machine Learning has a wide range of applications and can be used in any field or industry in one way or the other. The pace at which machine learning is developing and the future possibilities it beholds are immense.
Down below, we have listed and explained how machine learning will impact the future of various industries:
1. Future in Healthcare
Machine learning is helping the Healthcare industry in major ways today. It has changed a lot of things in the industry.
From giving accurate prescriptions to patients according to their health condition to bringing a change in the surgeries and treatments for some critical health conditions, Machine learning is changing the healthcare industry in every possible way.
Machine learning has now enabled doctors to collect large amounts of data and analyze to predict the right treatment for the patients. This was not possible earlier in the day.
Using Machine learning, a patient’s private health records are saved, which are easily accessible whenever in need by the doctors. These records might include the patient’s previous disease, family history, blood test reports, etc. These records help in future analytics of the patient’s health history whenever in need.
Some applications in Healthcare use Machine learning are,
- Disease Identification and Diagnosis
- Image Analytics
- Drug Discovery/Manufacturing
- Personalized Treatment
- Clinical trial research
- Epidemic outbreak prediction
The future scope of machine learning in healthcare is disease prediction, drug discovery, and electronic health records.
Future applications of machine learning are expecting various advancements. One might be able to treat its disease even before it’s grown or spread inside us, which means the treatment will not be done after diagnosis but before.
If we start automating the drug discovery process, it would reduce 70% of the cost. The drug discovery process, if automated, would benefit a lot of factors in the pharmaceutical industry. It would take less time to get through the discovery process, would reach the market faster, and result in cost reduction.
If all the data is stored in a uniform process using the various aspects of Machine learning such as image recognition and natural image processing, we can find all the medical and health records in one place being collected from different sources.
These data would be beneficial to doctors, medical observers, and others as they would provide huge data sets, which could be accessed anytime and anywhere and used to improve the analytics and come up with better treatments.
2. Future in Business
Companies have started adapting to machine learning technology at quite a pace now. Multinational companies are hiring machine learning professionals to up their game and cut costs.
These are using machine learning to analyze huge data sets and come up with patterns and analytics which could be of great help in the growth of their businesses. Approximately 90% of the world’s data was generated in the past two years. All this data is helping companies to build and visualize important projections for the future. These big sets of data could provide new analytics that would be very useful for businesses to grow.
Data handling and modeling is just one aspect where ml will impact the future of business.
Some of the other future application areas of ML are:
- Inventory Planning
- Upsell and Cross Channel Marketing
- Segmentation and Targeting
- Recommendation engines
- Customer ROI and lifetime value
- Customization management
A few major innovations that will be the next big things in the future are IBM Watson, Kafka, and Spark.
We expect to see all these points in the future of machine learning in business.
With future aspects of machine learning, we can expect the majority of customer interaction to be done using virtual assistance on the websites of the companies. Advertisements and recommendations have taken a top-notch in machine learning applications used by businesses.
The recommendations and advertisements could achieve that perfect point where you would be able to buy products and get recommendations of exactly what you need.
As machine learning develops, we expect to see more user-friendly data visualizations in the future. Market growth and acceleration in the growth of businesses are what we can see in the future of machine learning.
3. Future in the military
With machine learning, we can have robots and machines that can take tasks up on their own and complete them. This might and might not be the best decision for human welfare, but can we trust machines when it comes to human lives in the military?
Applications in the Military:
- Threat Intelligence
- Autonomous Defense system
- Operational analytics
The markets for air and ground autonomous machines/robots might arise in the future for the military. But this depends on if the engineer can design autonomous models that have their sense of knowledge.
Given the development in other areas of machine learning, there has been little advancement in the military sector. The UAVs are also in the process of developing to become autonomous, just like ground vehicles are in development, for example, unmanned tanks.
The future in the military might be a slow development process as automation is a bit more complex in this field but they are still being controlled by some humans behind it. To turn into autonomous systems still has a long way to go.
4. Future in Banking
Machine learning has enabled banks to get rid of the old mathematical ways. Big data has helped Banking and financial institutions avoid huge risks, get better stock investments and have a strong financial sector.
Even before customer service chat boxes or any other advanced AI application was used, Machine learning had stepped a very strong step in the banking industry.
Portfolio management, algorithmic trading, fraud detection, and loan insurance underwriting are some of the many applications being already used in the banking sector.
Applications in the Banking sector:
- Fraud and Risk Management
- Investment Prediction
- Sales and Marketing Campaign Management
- Customer Segmentation
- Digital Assistance
- Compliance management
- Credit underwriting
The future of banking and financial services in terms of machine learning development is expected to be very bright.
Enhanced customer service is one of the aspects we can see growing in the banking sector.
By using machine learning, customers spending patterns can be analyzed and services can be personalized using those analytics. This would provide better customer service and a strong relationship between the customer and the bank.
Chat Boxes are already being used by companies to assist customers, but in due time these chat boxes will be so ahead that they’ll be offering more personalized services to the customers.
They would be able to tell how many EMIs are left, what offers customers should check out, and loan schemes that might be suitable for different customers.
Intelligent character recognition might also advance in the industry, this will be able to detect after analyzing old transactions, loans, EMI payments, etc., if the customer is eligible for any kind of loan and if yes, then which kind of loan with which interest rate is to be given. Risk levels and fraud will be less likely to occur using this system.
5. Future in Education
The future of education is going to change drastically in the coming years. Machine learning will make education fun and interactive for students and teachers.
As we have already stepped towards virtual and more interactive learning, machine learning will elevate both methods in newer ways, such as more personalized learning in schools. This will let the teachers examine how students are learning and understanding particular concepts in their studies.
Significant growth factors would be present in the future because of machine learning in terms of education. All these methods for interactive learning would make education more participative for the students enabling them to understand the concepts easily.
Machine learning future trends in education include matching students and teachers according to their personalized schedules and performances. Students’ performance will suggest ways to go about their subjects.
They will suggest which learning path to take. Teachers would know which areas need to be paid attention to when teaching a particular batch of students based on the analyzed performance.
Biased grading will decrease using machine learning. Better and rich content will be provided and included in the curriculum for students with a better management system.
Now that we know how machine learning will impact various industries in the future, it’s important to understand some other future aspects of machine learning.
Let’s see what the predicted future market growth in machine learning and what career options are there for a machine learning enthusiast.
Market Growth in Machine Learning
Organisations worldwide are already incorporating machine learning solutions in their day-to-day operations. They are also using it to enhance customer experience and ROI and gain a competitive advantage over other businesses.
In the coming years, applications of machine learning are expected to rise at an exponential rate. This makes it important to understand that with this exponential rise in ML applications, the amount of spending on building ML solutions will also rise.
According to Marketsandmarkets.com, the Machine Learning market is expected to grow from US$ 1.41 Billion in 2017 to US$ 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1%.
Now, it is obvious that as the machine learning market grows, the requirement for skilled professionals in this field will also increase.
So, let’s discuss some of the future career opportunities in machine learning.
Future Career Opportunities in Machine Learning
In the coming years, the banking, insurance, and financial sector is going to be the highest contributors to the Machine Learning job market.
Next to the Banking and finance sector, the Healthcare sector is also expected to grow during the forecast period at the Highest CAGR.
To lower the costs and increase the efficiency in complex business management, you can expect to see exponential investment in Machine Learning.
Some of the lucrative career options in Machine Learning include:
- Machine Learning Engineer
- Data Scientist
- Human-Centred Machine Learning Designer
- Software Developer/Engineer (AI/ML)
- Natural Language Processing Scientist
The target audience for machine learning includes:
- Machine learning solutions and service providers
- Analytics service provider
- Training and education service providers
- End-users/consumers/enterprise users
- Telecommunication providers
- Cloud service providers
- Datacenter software vendors
- IoT device/wearable device manufacturers
- Artificial Intelligence (AI) technology experts/providers
All these different aspects and trends of Machine Learning can be seen in the future. If you are interested in shaping your career in sync with the thriving industry, Machine Learning is just for you.
We hope our blog has helped you in getting a better idea about the future of Machine Learning. We bet you don’t want to miss out on such a lucrative platform and domain that is ready for disruption.
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Frequently Asked Questions ( FAQs )
1. What is machine learning?
Machine learning is typically a type of Artificial Intelligence (AI). It analyzes the previous data to give a new output. It utilizes statistical data to produce innovative software applications.
2. How many types of learning do machine learning consist of?
Machine learning consists of three types of learning:
1. Supervised learning
2. Unsupervised learning
3. Reinforcement learning
3. Who is known as the father of machine learning?
Geoffrey Everest Hinton CC FRS FRSC is the father of machine learning. He was born on 6 December 1947 and is renowned for his work on artificial neural networks.
4. Which language is best for machine learning?
The best language for machine learning is Python.