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Published On: Tue, Feb 12th, 2019

Using Artificial Intelligence and Machine Learning to Innovate Business

Advancements in modern technology, especially those pertaining to synthetic intelligence, have sparked a profound global discussion that is bound to grow over time.

That’s why it’s not surprising to see articles, news pieces and information lists that talk about Artificial Intelligence AI and machine learning ML every other day–and the two terms are often used interchangeably, but their underlying mechanisms are not quite the same.

Here are the differences between AI and ML which will help you tell these disruptive technologies apart. While machine learning (ML) is a component of artificial intelligence (AI), the two are slightly different.

photo/ Gerd Altmann

What is AI? ,

Artificial intelligence, or AI as it is usually referred to, is a concept that helps a computer program or algorithm to work, react, and think like it possesses human intelligence.

Artificial intelligence AI allows the respective computers or machines to function and navigate their way through data, processes, and programs that would otherwise require human involvement.

Since the disruptive mechanism of possessing human-like intelligence allows these programs to think on their virtual feet, they are able to react to these scenarios with artificial intelligence and achieve the same results as a human would likely have.

If you want to move the needle in your company, “Understand your key organization and business challenges and what actions to take to able to innovate effectively and systemically, says CEO and founder of Pivot Factory, Michael Leadbetter.

Leadbetter continued: “All companies need to innovate and to get serious about their digital transformation journey.  70% attempt and fail this journey, Digital transformation is typically focused on (1) creating new business models (2) adding technology to an existing product (3) using technology to make the core business more efficient.”

This streamlines processes, eradicates the need for humans to allocate their time to redundant procedures, and opens doors to an array of possibilities where machines could perform tasks that humans would normally have to do. At the current moment, they are not able to trust a computer program to conduct these tasks.

Google Search’s identification of images and telling them apart, or Siri’s actions on voice commands and setting alarms on your phone are all part of broader AI concepts.

AI achieves this unprecedented functionality through a variety of processes, which are subsets of its overall tech. ML is a part of those subsets.

What is ML?

Machine learning, or ML as it is known to most people, (refers to the subset under AI) allows AI to learn human like behavior.

ML learns human behavior through repeated observations, and contribute to any machine’s broader AI.

ML can also learn pre-set data by placed humans, called “supervised learning”. This pre-set data can help ML to make the AI better. While supervised learning is not always used and “unsupervised learning” gives free rein to AI, both of these methods are a big part of ML.

This is equivalent to how a child moves around in the world by learning new information as they grow. While they couldn’t recite the theory of relativity at the age of 3 (if your child can, then Kudos to them), they most likely can do so a few years later. And if helped by a teacher, that makes their learning that much easier.

This clarifies that ML is not interchangeable with AI, but it is a part of AI. Calling AI the equivalent of ML is similar to calling a car the equivalent of its engine. You simply cannot compare the components of an overall mechanism to the mechanism itself – it is not unfair, but it is also confusing to everyone involved.

ML helps AI to be better over time. With ML, AI can streamline its own thinking, which once again is similar to humans learning new information.

One of the prime examples of ML at work in conjunction AI is the Google Duplex, which last year took everyone by surprise with its exceptional skills to act and talk like a human over the phone. The AI was able to converse so naturally, listeners couldn’t tell if they were talking to a machine. The tech is still under development but it should be available for everyday use within a short while.

Learning These Differences is Important

AI and ML have progressed into a variety of areas such as finance, medicine, and science among many others, and as such, it is important for you to understand the difference between the two technologies.

Keep up with the technology and learn how it can help you have an edge in your organization.

Pivot Factory and its CEO Michael Leadbetter have been devoted to the cause of bringing innovative and disruptive solutions to their clients. Leadbetter’s regular Podcast is one of the many examples of such initiatives.

Pivot Factory strives to be one of the few business/management consultant firms that pushes AI forward to increase the effectiveness and optimization of its clients.

We believe that artificial intelligence AI is not just here to stay; it is here to change the game.

Author: Nicole Blair

About the Author

- Outside contributors to the Dispatch are always welcome to offer their unique voices, contradictory opinions or presentation of information not included on the site.

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