Ryan Hemphill, Founder @ Madison Park Capital, On AI in Business

It is no secret that artificial intelligence has swept the world at large in recent years, sparking the interest of some and deeply concerning others. However, the development of this technology and its associated moving parts are not going to slow down any time soon — especially not at the people’s request. Therefore, we ought to brace ourselves for all of the rapid change to come.

For instance, machine learning is projected to become all the more ingrained in business models in the near future, especially as more organizations find value in all this technology has to offer — from sifting through and sorting data to sharing the knowledge they gained with other devices within the company’s closed network.

With that in mind, let us explore the ways in which machine learning will gain popularity in the future.

Machine learning will lower the need for training data

As we all know, artificial intelligence is not inherently intelligent. Instead, it requires human programmers to teach and train it in the tasks it is expected to complete and understand. However, such training requires countless data elements and, most importantly, time.

Companies could eliminate such extensive and expensive ventures by adopting transfer learning, a newer method that employs pre-trained machines to “teach” the newer additions all of the imperative data sets they already comprehend.

Machine learning will efficiently explain results

A number of industries find it difficult to integrate artificial intelligence into their business models because they do not have the means to interpret the trends and predictions they provide after analyzing data sets. However, as technology continues to develop, more and more interpretable machine learning models are being released, therefore lowering the proverbial barrier and making such devices all the more accessible to the general business population.

Machine learning will soon be deployed on smaller, more local scales

The Internet of Things has already expanded to encompass our smartphones, appliances, thermostats, and even our alarm clocks. However, as machine learning models are consistently refined, they will become all the more integral to the design and software in our everyday devices. Therefore, machine learning’s reach will extend far beyond the business world, impacting the productivity and daily habits of the average, working consumer.

As we can now see, artificial intelligence and machine learning are forces that are growing at an unstoppable rate. Whether we like it or not, these technologies will likely become core proponents in our everyday lives, though it will certainly be interesting to see how long such a widespread adoption may take.

Ryan Hemphill is an experienced private equity and venture capital executive based in New York City. Outside of his career, Ryan is deeply passionate about philanthropy, giving back to his community in tangible ways, and gleaning further insight into the rapidly changing realm of artificial intelligence and technology. To learn more about Ryan Hemphill and his professional pursuits, please be sure to visit his website.