Artificial intelligence, machine learning, and deep learning have become huge buzzwords in the business world. While many people use these terms interchangeably, they actually mean three different things, and it’s critical that business leaders understand the distinctions as we enter this new era of rapid AI development.
Kara Sherrer, writing for TechRepublic Premium, defines the three terms and compares them to each other to illuminate the similarities and differences. The feature also explores business use cases for all three kinds of technology to demonstrate how your company could (or already does) benefit from them.
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APPLICATIONS OF ML FOR BUSINESS
ML isn’t just helpful for recommending what TV show you should watch next. It also has many practical applications in the business world. In fact, many business tools and software already incorporate it — you just might not have realized it yet. Here are some additional use cases that we didn’t already cover in the AI section above:
Financial services: ML is used to detect suspicious activity and automatically alert the account holder of potential fraud.
Supply chain: It can analyze workflows to identify potential issues and bottlenecks before they become a serious problem.
Analytics: ML can help your business forecast future revenue and sales based on past performance and market conditions.
Sales: It can help the sales team predict lead conversions by learning what factors increase the likelihood of closing a sale.
Retail: Algorithms can automatically update prices based on supply and demand, as well as seasonal changes.
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TIME SAVED: Crafting this content required 20 hours of dedicated writing, editing, research, and design.
