When contemplating a new venture into AI or machine learning, companies need to take on a number of important considerations that relate to talent, existing data, and limitations. One way executives can judge how successful or appropriate and AI project would be for their company is to examine use-cases of businesses that have previously done something similar.
With AI and machine learning news increasing in tech media, a business leader may find it challenging to cut through the hype and identify valid, useful case studies.
We talked to Ben Lorica, PhD, Chief Data Scientist at O’Reilly Media, to get his insights on what key details executives should be looking for within a case study.
While a business leader does not need to become a technical expert in AI to understand case studies, Lorica says that it’s important for them to understand the basics of AI and what it takes to implement it.
“People focus a lot on the model, but when you get into the details, it’s about more than just building a cool model,” Lorica says.
“At a high-level people understand the basics of these technologies,” he adds. “So AI and analytics are often used to improve decision-making or automation.”
“At this stage in the revolution of these technologies, you have access to cloud computing services so you can go that rout if your comfortable using managed services — Which means you might need to have less people to maintain infrastructure particularly on these open source projects. … You could conceivably use machine learning services in the cloud. Then you’ll also need less people to maintain those machine learning libraries in house. “