5 Original (And Creative) Uses for Machine Learning

5 Original (And Creative) Uses for Machine Learning

Although trends can’t be predicted, AI or Artificial Intelligence promises to influence today’s society. Machine learning is a sub-genre of Artificial Intelligence and has gathered a lot of attention for its impact on the most important industries in the world.

Due to the huge hype, massive amounts of resources and talent are entering this space. What is machine learning exactly and why should we care about it?

Machine learning models are an application of Artificial Intelligence which algorithms predict outcomes. These models can extract insights, process large data sets, and make accurate predictions without human intervention.

So many value-generating implications result from the development of this modern technology and many are predicted to simplify the world we live in.

I will share with you five of the most creative uses for machine learning. They will be coming into your business and personal life, sooner than you think.  Here some of the most popular articles that you can check: Robots in Healthcare: What’s In For the Future

1.Improved Retail-Management Systems

The retail sector has generated over $20 trillion in sales for the past few years. This figure comes with a huge amount of consumer-behavior data (trends, demographics, and tastes) compiled from consumer-shopping tendencies and patterns.

Still, many retail businesses are having trouble implementing these valuable insights since data usually comes from disconnected warehouses. There is a huge opportunity to implement machine learning models that allow retailers to better understand their customers and ensure a more personalized shopping experience.

By using previously gathered data, machine learning technology can predict everything from when to give out special promotions to which products to recommend, etc. Ecommerce retailers can combine behavior patterns to improve the entire customer journey, from the very first point of contact to the endpoint or purchase of the product.

Data Machine learning technology

2. Improved Cybersecurity

Did you know that cybercrime damage costs are predicted to overcome $6 trillion annually by 2021? Yes, and the experts predict that business companies will spend over $1 trillion in cybersecurity services from now to 2021 to outweigh this threat. We can all agree that cybersecurity is and will continue to be a major priority for small and large businesses alike.

Experts are creating better ways to implement machine learning models to prevent phishing, detect fraud, and defend against virtual attacks. Defense-mechanism software systems are being properly trained, using specific data, to spot and protect against insecure and suspicious activity. Unlike humans, the algorithms can work 24 hours a day, without any complications.

3. Wide Scale Utilization of Autonomous Vehicles

The wide-scale popularity of autonomous vehicles represents an efficient future for logistics and transportation. Some reports show that self-driving cars could reduce traffic-related accidents by as much as 90%.

Even though we are a few years away from producing these vehicles to consumers, the adoption of one such autonomous vehicle by the society is absolutely inevitable. The time scale for adoption and utilization of this technology depends upon regulatory action which usually lies outside of the technology world’s control.

Software engineers using these self-driving vehicles are relying upon machine-learning technologies to support and power the algorithms that allow these fleets of the future to operate autonomously. The models integrate data points from different sensors, for example, radar, lidar, cameras, etc. to operate the vehicle. The algorithms become smarter over time, leading to faster and safer driving.

4. Enhanced Moderating of Content

The process of content moderating is a huge problem for social media platforms like Twitter and Facebook as they focus on delivering more accurate information to their users. The failure to oversee content can have serious consequences.

When it comes to fake news, Facebook in response to the public announced it would hire 3000 employees specifically to look after the newsfeed content. However, this anxiety extends beyond social media. Tech conglomerates like Google are investing significant capital into creating content-monitoring teams to support their marketplaces.

AI platforms and machine learning such as Orions Systems are developing proprietary systems to grow and adapt the interactions between technology and humans for specific tasks such as moderating content.

These modern technologies are addressing the responsibility of moderating content with tools and resources so that employees can be more effective and work more productively. This is an advantage, as machine learning to deal with video is quite challenging.

Orions Systems Machine Learning

5. Efficient Healthcare Network

The healthcare industry operates on top of an inefficient legacy. One of the biggest points of concern is discovering ways to preserve important patient details while optimizing the system.

Luckily, today we can use innovative machine learning algorithms to process large sets of sensitive healthcare data without breaching any confidentiality contracts. Also, we can use these models to analyze diagnoses, understand opinions, risk factors, etc.

Dr. Ed Corbett said that “Machine learning puts another arrow in the quiver of clinical decision making”.

We can agree that machine learning has recently made some headlines. Google has created a machine learning algorithm to help find cancerous tumors on mammograms. Another example is Stanford. They use a deep learning algorithm to diagnose skin cancer.

All these five machine learning models become more and more accessible to business owners and developers. Soon, they will start to gain mass popularity and endorsements from enterprises and consumers. As that happens, it will be exciting to see which models come out as the best ones.

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