15 Entrepreneurs Explain the Impact of Machine Learning on Business
04 March 2018
Originally Posted on CEO Blog Nation
Machine learning is taking over the running of many industries. To some, it’s a sound of rather bad news while to other businesses, it’s a sign of better days to come. We know some entrepreneurs have embraced or had experience with machine learning thus we asked them what they think will be the impact of it on business. AJ Abdallat, CEO of Beyond Limits an artificial intelligence company out of Glendale, CA, shares his take:
Meeting of more complex demands
The machine learning and big data-based AI that currently pervade are powerful tools for identifying associations in large quantities of data, but don’t have much on humans in terms of working out the complex phenomena of cause and effect, or to identify modifiable factors that can engender desired outcomes.
So how does AI make the leap to the next step?
The first step is to enhance the big data and machine learning with another layer of AI functionality – that of cognitive intelligence. What is missing in the AI learning simply from crunching the data at hand is an AI that can reason through and incorporate missing information, reason abstractly, plan and problem solve. Mapping out scenarios and searching for potential outcomes to weed out confounders or even fill in missing data gaps through hypothetical scenarios.
In real-world applications, it is substantially more complicated than reasoning through an opponent’s potential moves in a complicated game and altering gameplay to reach the desired outcome. But the foundation is there, and the technology is certainly there as well.
While machine learning and big data have dominated for years, a new breed of commercial AI has begun to emerge to meet the more complex demands of modern human-machine interactions. The aim of cognitive intelligence AI platforms isn’t to supplant big data or machine learning. Rather, it’s there as a supervisor of sorts, monitoring how traditional AI processes data, filling in gaps and identifying misinterpretations.
Ultimately, the goal of a cognitive AI platform is to be able to complete tasks without the need for human supervision, to be able to quickly process unexpected or unfamiliar external input and adjust its response accordingly.