Machine learning is powerful, and the results we see from deep-learning papers are typically impressive. But can we be confident enough in them to make business decisions that have real, monetary outcomes? For any type of isolated tasks, such as learning to detect a face in an image, or classify a credit card transaction as fraudulent or not, or classify a frequently rebooting device as defective, we can usually construct the relevant low-level features (e.g., pixels, filters, zip codes, vendors, reboots, URLs) and solve the problem using conventional machine learning techniques.
Are you blind to what's happening in your installed base? Would you like to get the real, hard data from your beta test community?
It's time to instantly know where your connected services and products are having problems that affect your users’ connected experiences. And you need the tools to pinpoint the issues, collaborate with your extended team, and resolve them quickly.
Stressful hours at the War Room.........OR...get ahead with Omny IQ.
It's 6:30pm, and you’re about to leave for the day. But messages start coming in, and Customer Support is scrambling with a sudden surge of end-user complaints. You come to know your flagship product has been failing to connect users and their applications to the Internet.
by Eric Schaeffer, senior managing director, and David Sovie, and senior managing director, Accenture
Is it sufficient to digitize business operations for higher efficiency? Or does the real – and much larger – business opportunity come with digitizing products, and with creating entirely new value propositions? Read on to find out why we recommend businesses shape their digital transformation by reinventing what they make.