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Technology

5 Facts You Should Know About Machine Learning and AI

5 Facts You Should Know About Machine Learning and AI
timhinchliffe@gmail.com'

Over the years, computer-programming languages have been evolving, but the greatest milestone to date has been the removal of the complicated programming.

This has been achieved through a series of trial and errors to ensure computers learn for themselves also known as machine learning. Machine learning is currently viewed as the biggest technological leap, and it has been speculated that it will affect almost all businesses in future. Therefore, there is a need for everyone to know more about AI and machine learning to ensure they stay at par with the changing business world.

What exactly is machine learning?

Machine learning has become very common in artificial intelligence. Here, programmers teach computers how they can learn to solve problems by themselves instead of teaching them how to solve problems. Programmers use advanced statistics applications to teach computers how they can identify data patterns and make relevant predictions from the patterns.

A teaching data set is given to a learning algorithm whereby it is required to use the provided data to solve a problem. For instance, a programmer may provide some photograph sets to a computer and require it to identify other photograph sets using the data previously provided. A chatbot is used to add new teaching sets after every identification thus helping the program to become smarter over time.

Why is machine learning exciting?

It is now easy for computers to venture into areas that were initially considered to be human domains. Although technology is usually not that perfect every time, the idea that machines can tirelessly and continuously improve without any limit to their performance is very fulfilling.

Computers are now able to look at images and correctly recognize them. Additionally, they can recognize numbers and texts and easily identify places and people as well. Not only can they read texts, but they can also understand the context and differentiate between negative and positive sentiments. Moreover, computers are now able to listen to humans, understand them and provide relevant responses. Some virtual assistant that have shown exemplary performances include Google Now and Siri. Computers are also able to write. Presently, machine learning algorithms are being used in business intelligence to write basic news articles for businesses in fields that need a lot of data such as sports and financial reporting.

How is machine learning presently being used?

Presently, people are performing some exciting activities using machine learning algorithms. A recent Cancernetwork study viewed mammography women scans using computer-assisted diagnosis and the women later developed the dreaded breast cancer. The computer was able to spot approximately fifty-two percent of the cancers a year prior the official diagnosis.

Additionally, machine learning has been used to comprehend disease risk factors in large populations. Medicision is the company that was able to develop algorithms that successfully identified eight variables so as to predict some avoidable diabetes patients’ hospitalizations.

Read More: Machine learning for social good, saving lives, and emergency response

Natural language processing is currently being used in various exciting applications across different disciplines. Machine learning algorithms can now use natural language and replace customer service agents to provide customers with the relevant information they need quickly and efficiently. It is being used by attorneys to sort out large information volumes when preparing for cases.

The future for machine learning

The future possibilities for machine learning are limitless. Here are some exciting future possibilities for machine learning:

  • Data security plans that are in a position to detect attacks, viruses and malware using accuracies of high degrees.
  • Customized healthcare that is able to look at the lifestyle factors as well as the genetic makeup of an individual to create personalized treatment and healthcare plans for people.
  • Self-driven vehicles that can smoothly navigate by themselves and minimize accidents and traffic.
  • Computer-assisted security in areas such as stadiums and airports that are able to predict possible threats.
  • Advanced fraud detectors in the fields of insurance and finance to save money
  • Universal translators that will allow people to speak into their phones and have their languages translated instantly and accurately.

Why you should care about machine learning

All these advances in machine learning will completely reshape the workforce. Although the new technologies will ease many peoples’ jobs, they will as well take away jobs from people. This is because algorithms are now able to respond to emails, analyze data, and interprets medical images and so much more.

Read More: How AI as a Service will be imperative for business in the near future

People should focus on how machine learning is affecting their fields, businesses, and jobs and start preparing early to ensure that they are not found pants down the moment computers take up their jobs.

Conclusion

Today, if you visit an online store and view a particular product, which you do not buy, you are likely to see digital advertisements for the same product each time you surf the web for days afterward. This is a type of marketing personalization that companies are now using to personalize the emails received by customers, the offers they see, the recommended products as well as the coupons or mailings they see.


Vivian Michaels is a huge tech enthusiast, who likes to write articles on evolving technology. He is also a fitness coach with a sincere desire to help people achieve their individual fitness goals.

View Comments (1)

1 Comment

  1. proboy007@yahoo.com'

    PCT

    December 24, 2016 at 11:44 PM

    What if this machine learning AI gets in the hands of a hacker?
    Wouldn’t this nullify the benefits of detection of viruses and such?

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