- What can we do with AI?
- What exactly is AI from a software perspective?
- How can we infuse cognitive computing into our customer interactions and on the customer journey to create competitive advantage?
This flurry of inquiries led to a decision to team up with TM Forum to tackle the subject on a live webinar and in an upcoming Quick Insights paper. If you have some of the same questions, keep reading to learn where you can get the answers.
But first, a short tangent about me: this August marks 20 years that I've been at SAS. And believe it or not, in all those years, I have never done a live, global webinar to an external audience. I've done numerous face-to-face and WebEx presentations, and I've presented at large conferences. But I've never participated a live webinar without any immediate feedback from the viewers, where we are just talking and hoping folks on the other end are listening.
To prepare for the webinar, I did a lot of research on AI, machine learning and cognitive computing. One of the better reports I read was from Price Waterhouse Coopers on the promise of AI. The subject is really fascinating with promises to change the world as we know it – hopefully for the better! But we also have to remain realistic, and SAS CTO Oliver Schabenberger does a great job going beyond the AI hype in this recent post.
One of the amazing things about working at SAS is the quality, knowledge and willingness of people to help each other learn. As part of my research, I interviewed three of our top data scientists and learned a ton! How does AI work with other technolgoies, what are the components of AI, and what is needed to make it work. There are many definitions of AI but here are two that I thought were the best:
- AI is the simulation of human intelligence by machines, involving visual perception, speech recognition, decision-making, and translation between languages.
- AI is a series of capabilities that includes computer vision and natural language processing enabled by techniques such as machine learning, optimization and decision management.
As for cognitive computing, we settled on this definition:
- Cognitive computing systems are designed to intelligently ingest the information of our environments, understand what is observed and take the right action accordingly.
In its simplicity, cognitive systems look, hear and feel as humans look, hear and feel. And do this much faster and better than humans thanks to computing power and ability to process and analyze big data. With the goal being to compliment humans and help us do our jobs better, faster, smarter – NOT to replace us. Thank goodness!
If you're also trying to figure this out, or if you want understand what the Age of the Machines will bring – or if you just want to see how I did on my first webinar, Using AI and machine learning to drive customer centricity in a connected world, please check it out.
If you're more advanced, say a beginner to intermediate data scientist or an analyst interested in identifying and applying machine learning algorithms to address the problems of their interest, then here is a great blog post with a machine learning cheat sheet. Lastly, if you are very advanced and want to hear from one of the best at SAS, follow @Thompson_Wayne on Twitter.