Four Ways AI And Machine Learning Will Drive Future Innovation And Change Posted on : Feb 18 - 2021

2020 was a year most of us want to forget. The pandemic brought on economic, logistical and technological challenges on a massive global scale, leaving businesses scrambling to adapt. Amidst the upheaval, businesses turned to video conferencing platforms like Zoom and Google Meet to stay connected. Technologies like artificial intelligence (AI) and machine learning (ML) helped augment human efforts to take on everything from health to cybersecurity. Equally, businesses looked toward strategic execution and technology to remain agile among industry shifts and provide a greater return on investments.

Businesses are now focused on what's next and preparing for an economic surge in the latter half of 2021 once more people globally are vaccinated and the world returns to a more "normal" way of life. Here are four ways AI and ML will continue to shape multiple industries and integrate with other technologies to drive further innovation and change in the year ahead:

1. Increased Commercial Applications For "Federated ML"

"Federated ML" or a "cloud-in-a-pocket" approach will play a more prominent role. The applied principles and techniques employed with federated ML means data doesn't need to be in the cloud anymore. Today's devices can store more data than ever before and likely more than a user could ever produce. As a result, AI models that help to improve personalized services no longer need to be centralized on company servers, but can instead exist on the device itself.

Equally, the techniques used by federated ML ensure user data is kept on the device and not on a server, while still providing access to predictive AI modeling. Data isn't shared in the same way either. The advanced ML models used in federated ML keep data in data owners' hands, leading to greater privacy. This approach is a new take on data privacy and a growing megatrend. A good example of this is Siri running on your iPhone, but not sending all of your data to Apple's servers.

Federated ML and its principles are currently in use, but greater commercial applications in this area are on the horizon. The introduction of Apple's M1 chip and the industry-leading neural engine, for example, was specifically designed for advanced ML processes. Federated ML will also provide increased use cases within the financial services sector in areas like loan risk prediction, while AI and ML applications will also advance many other industries. View More