AI (Artificial Intelligence) Projects: Where To Start?
By Tom Taulli – Artificial Intelligence (AI) is clearly a must-have when it comes to being competitive in today’s markets. But implementing this technology has been challenging, even for some of the world’s top companies. There are issues with data, finding the right talent and creating models that generate sufficient ROI.
As a result, many AI projects fail. According to IDC, only abut 35% of organizations succeed in getting models into production successfully.
“While we see AI technologies performing a swath of incredible feats such as Google Translate, AlphaGo, and solving a rubik’s cube, it can be hard to tell which business problems AI is apt to solve,” said Ankur Goyal, who is the CEO at Impira. “This has led to a lot of confusion—and a vendor community that has taken advantage of it by labeling things as AI when they aren’t. It’s very reminiscent of early last decade when cloud technologies took off and we had a lot of cloud washing going on. We had vendors marketing themselves as cloud players when their offerings were vaporware. Similarly, we are going through a period of AI washing now.” Read On:
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