Any company bringing out machine learning or artificial intelligence software better double check to see if someone else has already patented their idea.

“It’s a very competitive race,” said James Kobielus (@jameskobielus) (pictured, left), co-host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during Inforum 2017 in New York today. Kobielus sized up the horses on the track along with his co-hosts Dave Vellante (@dvellante) (pictured, right) and Rebecca Knight (@knightrm) (pictured, center). (* Disclosure below.)

SAP SE, Oracle Corp. and Microsoft Corp., to name a few, are heavily invested in AI. “Where does Coleman put Infor in the race?” Kobielus asked, referring to Infor Inc.’s new conversational AI robot for enterprise users.

Coleman is comparatively “productized” for out-of-the-box instant gratification compared to its competitors on the market, Kebielus argued. “None of them has the comprehensive framework or strategy to AI-enable their suites for human augmentation,” he said.

Infor is already working Coleman into its portfolio of business applications. (Recent acquisition Birst Inc. which makes business intelligence software, will put additional ML capabilities at Infor’s disposal.)

Coleman’s pull is the conversational interface that processes requests and gives advice with natural language, Vellante explained. Amazon Web Services Inc.’s Lex deep learning tool is no doubt a main ingredient.

“What I don’t know is how much of the [intellectual property] is OEM [original equipment manufacturer] essentially from Amazon and how much is actually Infor IP,” Vellante said.

If the magic is openly on sale from AWS, will it be so difficult for Infor’s competition to purchase some and catch up?

Big social could steal AI

Infor and its aforementioned competitors may have bigger things to worry about thanks to companies that don’t even deal directly in Enterprise Resource Planning, namely Facebook and Google. Companies like these could easily steal the AI market with models trained on their gargantuan data wealth, according to Kobielus.

“Training makes all the difference in the world between whether a predictive analytics ML algorithm actually predicts what it’s supposed to predict or doesn’t,” he said.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the Inforum 2017 event. (* Disclosure: TheCUBE is a paid media partner for Inforum 2017. Neither Infor Inc. nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE