Artificial intelligence and machine learning are two similar technologies that have dominated the headlines in recent months and years. Because they both can learn from experiences without constant input from programmers, businesses are increasingly looking for ways to use them to make their operations more efficient and cost-effective. Here is a shortlist of some ways that self-learning programs help businesses save time and money:
1. Making Internet Content More Relevant and Interesting
When users upload content to the internet, the results can be low-quality, filled with errors or otherwise not worthwhile. However, companies are trying to cut down on those problems to ensure that website viewers see content that engages them and relates to the surrounding material.
Yelp.com — the popular internet review site — uses a machine learning system to classify business photos. It can look for the images people like best and use them to enrich content. This is a time-saving practice that limits the amount of non-useful photos that could fall through the cracks and it helps assert Yelp as an authoritative website that includes reliable reviews as well as images.
2. Ensuring Safer Air Travel
Airlines invest significant amounts of time and money into air traffic operations at major airports. They know that failing to do so could result in delays or accidents, both of which could be costly and tarnish a company’s reputation.
Southwest Airlines teamed up with NASA and created algorithms that can analyze huge amounts of air traffic and pilot data. The machine learning technology can spot irregularities in the information that could pinpoint safety issues. Every year, aircrafts provide 2.5 million terabytes of data, which Southwest mines for pertinent details.
These efforts are intended to improve airline safety. The algorithms work faster than humans can, meaning Southwest can operate with greater efficiency. Plus, the information gained facilitates a proactive approach to keeping people safe, which could save money by preventing disasters and other unfortunate events.
3. Keeping Equipment and Accounts Safe From Hackers
Specialists who work in manufacturing industries that depend on programmable logic controllers, or PLCs, have to stay vigilant against potential hacking attempts. When successful, hackers can take control of PLCs to disable safety features, steal data or spread incorrect information — all of which are time-intensive and expensive problems to remedy.
However, artificial intelligence-driven systems are increasingly relied upon to stop hackers before they can do major damage. Also, machine learning algorithms can understand the typical characteristics of a locked-down network then alert users or equipment operators if something seems amiss.
Similarly, this technology learns the features of content that is potentially fraudulent and raises red flags when necessary. For example, Google’s Gmail application checks numerous factors in emails and tells users if messages they received could be phishing attempts. Users see warnings of suspicious content on their screens and can then decide how to handle it.
4. Finding the Best Candidates for Open Positions
Businesses often use chatbots to interact with customers outside of opening hours or let the bots relieve some of the burdens from swamped support representatives. These use cases will likely remain prevalent through the coming years.
However, this December, a company provided a glimpse of what to expect in the future. Tokio Marine Life — a Japanese insurance establishment — launched the first artificially intelligent, self-learning chatbot used by an insurer.
Designed for people who are interested in insurance careers, the chatbot can answer several hundred questions that candidates might have, plus give information that’s not typically available to the public. The chatbot has a quiz feature, too. It helps individuals who are feeling unsure about working in insurance determine whether they have the personality traits and skills that would equip them to excel.
This technology also provides information about upcoming recruitment events to people who show interest in learning more about available job opportunities. Plus, since the chatbot connects with Facebook Messenger, human representatives from Tokio Marine Life can swiftly reach out to potential applicants and provide supplementary information.
Besides reducing the necessary interactions with human employees, the chatbot acts as a screener. It could cut down on the number of applications from candidates who do not have the desired qualifications — and the likelihood of spending money, time and resources to train new hires who ultimately leave after a few months because they decide they aren’t good fits for the company or the work.
These exciting examples of companies using self-learning applications to support their workforces and bottom lines give a preview of what’s to come. In a few short years, intelligent technologies could drastically alter the way businesses interact with stakeholders and manage their establishments.
About the Author
Contributed by: Kayla Matthews, a technology writer and blogger covering big data topics for websites like Productivity Bytes, CloudTweaks, SandHill and VMblog.
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