Machine learning is the engine behind the hood of artificial intelligence. It has become a household name after companies like OpenAI popularized the technology by making it more accessible to the public.
Despite its notoriety, machine learning is still in its infancy and brimming with untapped potential; its global valuation of $15.44 billion in 2021 is expected to grow to $209.91 billion by 2029. This growth is only matched by the technology’s potential applications in solving real-world problems, where it is set to revolutionize everything from the medical field to agriculture.
From improvements in medical diagnosis to completely overhauling modern-day transport and urban planning, machine learning can solve a wide range of real-world problems.
Medical Diagnosis
AI has revolutionized the medical industry, reducing instances of medical malpractice and misdiagnosis.
In the UK, for instance, machine learning has helped improve treatment for rheumatoid arthritis patients. By analyzing blood samples from affected patients, AI is able to predict how well medications will work for different patients since the effectiveness of antirheumatic medications varies from patient to patient.
Predictive Maintenance
The global maintenance industry was valued at $616.1 billion in 2020. A good chunk of this amount is from losses incurred by factories due to downtimes caused by faulty equipment, which costs $172 million per plant. Machine learning is poised to change this by analyzing data from sensors and instruments to predict the early signs of a failure before it happens. This is expected to reduce costs by up to 50%.
Fraud Detection
Fraud is a scourge that cost consumers $10 billion in 2023.
Machine learning is one of the most promising tools to combat this pertinent issue. It can learn and identify normal patterns in financial transactions, allowing it to identify possible fraudulent activity even in cases where there hasn’t been a chargeback yet.
Optomized Recommendation Systems
Technology has embedded itself in every sector of society, with business being no exception. This is why machine learning algorithms that identify patterns and relationships in purchasing data are invaluable to most stores. They enable the creation of personalized recommendation systems, which increase the likelihood of a purchase.
Image Recognition
Image recognition technologies can potentially revolutionize many industries, from autonomous robots and self-driving cars to labeling images with meta tags. Machine learning helps image recognition technologies autonomously analyze and identify objects within an image without human oversight.
Speech Recognition
Speech recognition technologies continue to blur the lines between man and machine. By leveraging the power of machine learning, human speech recognition is quickly approaching a level of sophistication comparable to human hearing. For these reasons, the two technologies have been combined to help improve studies on hearing loss.
Autonomous Vehicles
Inventions such as Leonardo Da Vinci’s ‘self-propelled cart’, which was invented in the 1500s, have positioned autonomous vehicles as the future of driving. Machine learning is perhaps the best tool we have to realize that future. Machine learning enables autonomous cars to maneuver through traffic in much the same way a person would.
Energy Consumption Optimization
Nothing underscores the dire severity of the modern-day energy crisis more than skyrocketing energy costs. As the finite resources that power the grid become harder and more expensive to extract, the costs of energy production rise, making energy costly and unreliable.
Machine learning can be used to optimize the energy consumption and generation of buildings by adjusting the settings of resource-intensive applications, thereby making them more efficient.
Customer Churn Prediction
Customer churn prediction is the lifeblood of most e-commerce stores. It involves identifying customers who are at risk of abandoning their subscriptions and closing their accounts.
Machine learning is used to identify customer churn in real time at a rate that no human could match.Â
Climate Change Prediction
Climate change is the pre-eminent threat of the 21st century; between 2030 and 2050, 250,000 will die as a direct consequence of climate change.
Machine learning is one of the best tools to prevent this catastrophe. AI can help optimize supply chains to be more energy efficient, accelerating the global transition to clean energy.
Supply Chain Optimization
Supply chains are vulnerable to disruptions brought on by global events such as pandemics, wars, and political instabilities. These problems exacerbate supply chain forecasting system flaws, resulting in delivery delays, a mismatch of supply and demand, and financial losses. Machine learning can generate more accurate recommendations that can cope with global uncertainties.
Personalized Healthcare
Modern medicine has greatly benefited from the realization that people are different and that the same treatment may not work for everyone. This has led to remarkable improvements in the overall effectiveness of medical treatments. None of this would be possible without machine learning, which analyzes patient data and recommends treatments based on their individual needs.
Cybersecurity
With the advent of technology, everybody has a digital footprint, as anything and everything that can be done in person has its equivalent online. This is why it is important that the footprint is protected from hackers who would use it maliciously. Machine learning in cybersecurity is used to identify network risks online and prevent possible ports of entry for hackers.
Smart Grid Management
A smart grid monitors and manages the transportation of electricity from power plants to end users such as businesses and homes. Smart grids are often prone to failure, as was the case when extreme colds hit Texas in 2021, causing the entire grid to fail. Machine learning helps grids become more efficient, preventing the likelihood of collapse.
Predictive Analytics in Marketing
Predictive analytics is employed in marketing to identify trends in user data such as online activity, location, and weather, increasing the effectiveness of marketing campaigns. Machine learning can enhance adverts’ efficacy by analyzing customer data and segmenting customers into groups that are more likely to respond to ads.
Human Resources Management
Human resource management presents a great challenge to most businesses as they try to navigate issues such as staffing and leadership development. Machine learning can be used to address some of these issues, such as identifying suitable job candidates and assisting in the job recruitment process.
Crop Disease Detection
The full potential of global crop production is stunted by the fact that 26% to 40% of global agricultural output is lost to disease. Machine learning has the potential to eradicate diseases in crops altogether. By using algorithms built on images of crop leaves, AI can detect disease and tell you what disease it is.
Urban Planning and Transportation
Urban planning and transportation face significant hurdles in terms of their environmental impact. In both its incarnations as carbon emissions and noise pollution from urban transportation, pollution has negative effects on urban populations. By enabling smart traffic control and driver modeling, machine learning can make urban planning and transportation more green.
Drug Discovery
The drug discovery process faces two primary challenges: clinical trials that identify dangerous drugs as safe and safe drugs as unsafe for humans. By predicting the biological activity of compounds, machine learning can help researchers work with only the most promising drug candidates.
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Caitriona Maria is an education writer and founder of TPR Teaching, crafting inspiring pieces that promote the importance of developing new skills. For 7 years, she has been committed to providing students with the best learning opportunities possible, both domestically and abroad. Dedicated to unlocking students' potential, Caitriona has taught English in several countries and continues to explore new cultures through her travels.