Karel van der Poel, GM Performance Analytics Business Unit, ServiceNow & Allan Leinwand, Chief Technical Officer, ServiceNow sit down with Dave Vellante & Jeff Frick at ServiceNow Knowledge 2017 at Orlando, FL
https://siliconangle.com/2017/05/15/servicenow-addresses-fears-about-oversharing-machine-learning-data-cloud-knowledge17/ #theCUBE #ServiceNow #Know17 #Knowledge #SiliconANGLE
ServiceNow addresses fears about oversharing machine learning data in the cloud
Cloud providers can assure customers their data is theirs alone, but if they bake it into a machine learning model they then serve to their competitors, aren’t they giving away their intellectual property by proxy?
“Trying to disseminate that information when you aggregate that and you commingle that data — it has IP implications; it also has just relevancy implications,” said Allan Leinwand (pictured, right), chief technical officer of ServiceNow Inc.
Leinwald and Karel van der Poel (pictured, left), general manager of the Performance Analytics Business Unit, spoke about the controversy in an interview with Dave Vellante (@dvellante) and Jeff Frick (@JeffFrick), co-hosts of theCUBE, SiliconANGLE Media’s mobile live streaming studio, during the ServiceNow Knowledge17 event in Orlando, Florida. (* Disclosure below.)
Is ServiceNow the most ambitious company in big data today? Perhaps not, but it appears its security-minded customers don’t mind. Customers keep their proprietary data in a secluded database and instance; as a rule, ServiceNow does not commingle customers’ data, according to Van Der Poel.
“We only do that if you ask us to for benchmarking, for instance, and then we anonymize it. But for machine learning and building that training set, it really is training on the data of that customer and that customer only,” he said.
Ultimately, this results in a more accurate prediction model optimized for a specific organization, its processes and workflows, he added.
Consumer vs. enterprise ML
Admittedly, “bigger is better” might hold true for certain consumer applications’ data models, Van Der Poel explained. “If you’re Facebook or Twitter, you probably want to apply machine learning across all the tweets and all the posts,” he said.
The smaller datasets ServiceNow uses to trains models may appear a limitation at first, but individual enterprises benefit from zeroing in on the data that matters in their day-to-day operations, according to Leinwand.
“We’re not building a data lake and then trying to pick the droplets out that are relevant to you,” he said.
(* Disclosure: ServiceNow Inc. sponsored this Knowledge17 segment on SiliconANGLE Media’s theCUBE. Neither ServiceNow nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
@ServiceNow @SiliconANGLE theCUBE
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Karel van der Poel & Allan Leinwand, ServiceNow | ServiceNow Knowledge17
Karel van der Poel, GM Performance Analytics Business Unit, ServiceNow & Allan Leinwand, Chief Technical Officer, ServiceNow sit down with Dave Vellante & Jeff Frick at ServiceNow Knowledge 2017 at Orlando, FL
https://siliconangle.com/2017/05/15/servicenow-addresses-fears-about-oversharing-machine-learning-data-cloud-knowledge17/ #theCUBE #ServiceNow #Know17 #Knowledge #SiliconANGLE
ServiceNow addresses fears about oversharing machine learning data in the cloud
Cloud providers can assure customers their data is theirs alone, but if they bake it into a machine learning model they then serve to their competitors, aren’t they giving away their intellectual property by proxy?
“Trying to disseminate that information when you aggregate that and you commingle that data — it has IP implications; it also has just relevancy implications,” said Allan Leinwand (pictured, right), chief technical officer of ServiceNow Inc.
Leinwald and Karel van der Poel (pictured, left), general manager of the Performance Analytics Business Unit, spoke about the controversy in an interview with Dave Vellante (@dvellante) and Jeff Frick (@JeffFrick), co-hosts of theCUBE, SiliconANGLE Media’s mobile live streaming studio, during the ServiceNow Knowledge17 event in Orlando, Florida. (* Disclosure below.)
Is ServiceNow the most ambitious company in big data today? Perhaps not, but it appears its security-minded customers don’t mind. Customers keep their proprietary data in a secluded database and instance; as a rule, ServiceNow does not commingle customers’ data, according to Van Der Poel.
“We only do that if you ask us to for benchmarking, for instance, and then we anonymize it. But for machine learning and building that training set, it really is training on the data of that customer and that customer only,” he said.
Ultimately, this results in a more accurate prediction model optimized for a specific organization, its processes and workflows, he added.
Consumer vs. enterprise ML
Admittedly, “bigger is better” might hold true for certain consumer applications’ data models, Van Der Poel explained. “If you’re Facebook or Twitter, you probably want to apply machine learning across all the tweets and all the posts,” he said.
The smaller datasets ServiceNow uses to trains models may appear a limitation at first, but individual enterprises benefit from zeroing in on the data that matters in their day-to-day operations, according to Leinwand.
“We’re not building a data lake and then trying to pick the droplets out that are relevant to you,” he said.
(* Disclosure: ServiceNow Inc. sponsored this Knowledge17 segment on SiliconANGLE Media’s theCUBE. Neither ServiceNow nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
@ServiceNow @SiliconANGLE theCUBE
