Artificial intelligence and machine learning have become major buzzwords over the past few years. While the terms were popularized decades ago in science fiction movies, AI and machine learning are currently affecting the world every day.
Here are four examples of AI and machine learning in practice.
Imagine if explorers from the past had access to Google Maps when they were sailing around the world. They wouldn’t have gotten nearly as lost, thanks to the GPS telling them exactly when to adjust course. Those voyagers would have been mesmerized by the artificial intelligence technology that helps Google Maps and other products operate on such a high level today.
One of the most groundbreaking aspects of these apps is their ability to offer real-time directions and ETAs based on dynamic factors such as traffic or train arrival and departure times (including delays). These are revolutionary tools for the modern world, which help commuters avoid headaches and lower the overall traffic burden.
Plus, these models are continually improved.
Recently, the vast change in overall traffic due to Coronavirus necessitated a change to rely more heavily on historical data. This is an area where AI and machine learning are leading to great systemic improvements.
In the past, chat bots were more of a frustrating joke than something you would actually consider useful. That has all changed, thanks to advances in AI and machine learning. Today, chat bots are more effective than ever, especially for situations that repeat with little variation—such as entering preliminary info before speaking with a live human.
While there’s still some work to do in creating a fully functional chatbot. That can facilitate users just as well as a human. This idea isn’t science fiction so much as a matter of time. AI and machine learning are to thank for these developments.
Data Analytics Tools
You can only consistently make decisions as good as the information given to you. No one can intuitively know everything without some evidence-based direction. Data analytics is one of the most important tools available to enterprises because it vastly improves operating efficiencies across the board. Moreover, powered by Artificial Intelligence, it should be capable of finding insights before people even ask
AI and machine learning are now driving data analytics tools. This has introduced capabilities beyond the scope of human capacities. For instance, thanks to natural language processing, search analytics allows users without much data expertise to get immediate answers. This means employees empower to make actionable data-based decisions without having to send everything to the data team.
The speed and quality of data analysis are some of the most significant ways in which AI and machine learning will change the business world forever. Organizations that do the best job of taking advantage of this trend will have the best future outcomes.
Financial Security and Services Improvement
In the past, securing a bank meant having a big vault and a lot of security guards. Today, now that so much money stores and sends digitally. Financial security and services have taken on a whole new meaning.
It would be next to impossible for humans to keep up with the security threats and fraud bombarding financial institutions. These enterprises hold vast stores of wealth, so it only makes sense there will be armies of bad actors trying to steal some of it. Harnessing AI helps financial institutions flag and identify fraud, as well as security issues. These are both essential practices for protecting the assets of their clients.
Furthermore, AI helps with certain convenience features that have become commonplace for many banks, such as remote check uploads. Not long ago, it would have seemed futuristic to be able to take a photo of a check and have it automatically added to your account balance. Now, this is what we do at home in under a minute.
There’s no denying the utility of AI and machine learning in terms of how they make processes tangibly safer and more efficient. This trend is likely to only continue as more organizations incorporate these technologies into their products and services.
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