Datameer Blog post

AI’s Potential and Challenges

by on Feb 27, 2018

Hear from Andrew Brust, blogger at ZDNet and Datameer’s Senior Director of Market Strategy and Intelligence, or skim through the transcripts to learn about AI’s potential today.

What Does AI’s Vast Potential Have in Store for Business?

If you talk to pundits in the industry, if you talk to analysts in the industry, you’ll have no shortage of cliches about how powerful AI is and how it’s going to revolutionize everything. The interesting thing about all of that kind of over-the-top praise is in fact, a lot of it’s true. But we’re not going to get to that huge potential until we get a little bit calmer about everything it can do and we really bring the technology mainstream.

At that point, what AI will have the power to do is to take data that we’ve been collecting anyway and instead of just leaving it stored in a database, we’ll be building predictive models on it and we’ll be using those models to our advantage. With that, we’ll be able to predict what will happen in the business and thereby have a very sophisticated decision support system available in a mainstream fashion.

What Are the Challenges Associated With Operationalizing AI and Machine Learning Technology?

Operationalizing AI actually isn’t that hard, but that hasn’t been the precedent. Most of the AI tooling and most of the AI work has been done by data scientists on their own machines, and it has been done in sort of an ad hoc fashion. As this moves more mainstream, the only real challenge is to realize it needs to be operationalized, it needs to be audited, it needs to move from the workstation to the server or to the cloud. That work is just beginning.

What is Datameer SmartAI™

SmartAI™ is Datameer’s technology for operationalizing AI. The way we do it is we take Google’s TensorFlow Deep Learning Library and we bring models from TensorFlow in as additional functions into our spreadsheet environment. So scoring data against a model is no more difficult than passing column references in as inputs or as feature values and then calling the model to get back a predicted value. In our environment, it looks like just another function. In fact, what we’re doing is operationalizing AI.

Posted in Big Data & Brews

At Datameer, we’re obsessed with making data the most valuable asset in any organization. We believe that when people have unconstrained access to explore massive amounts of data at the speed of thought, they can make data-driven decisions that can wholly impact the future of any business.

Back to Overview

Subscribe to the Datameer Blog