Harel Kodesh, CTO of GE Digital, sits down with host Jeff Frick at Predix Transform 2016, at the Cosmopolitan Hotel in Las Vegas, Nevada.
Will the Industrial Internet usher in a bigger, better algorithm? | #PredixTransform
https://siliconangle.com/2016/07/29/will-the-industrial-internet-usher-in-a-bigger-better-algorithm-predixtransform/
Most consumers’ experiences with algorithms do not go much further than Amazon’s product recommendations. Thus, they see algorithms as hit or miss — sometimes they work, sometimes they don’t, and it’s usually not a big deal. But as large companies with important missions are utilizing algorithms associated with Internet of Things (IoT) in their operations, they are demanding much greater accuracy. And GE Digital believes it will be the one to meet that demand.
Harel Kodesh, CTO of GE Digital, believes that we are seeing the development of a brand new ecosystem, which he calls the Industrial Internet. He told Jeff Frick, cohost of theCUBE, from the SiliconANGLE Media team, during the GE Predix Transform event that he believes GE Digital’s Predix is uniquely poised to be the cloud platform of choice for this new domain.
Kodesh explained that Predix focuses on assets, in some cases very expensive and high-maintenance ones, like aircraft. He said they will have to bring the incidence of false positives and false negatives down for use by big industries. “Our machine-learning algorithm will have to be of a different breed than what you have for consumers,” he said.
Building a better algorithm
Kodesh said that Predix wants to make optimizing IoT applications a priority. “We have to make sure the developers have the freedom to decide what to put in the cloud and what to put close to the edge,” he said.
He went on to talk about how the company is planning to take the accuracy of algorithms to a new level. He spoke about different types of machine learning, such as supervised learning where “you tell the system what are the basic things it has to look for, and you let it figure it out itself.” He added: “And on the extreme side, you have unsupervised learning where you define for the machine what is going to be the winning function, what it needs to do, and it figures it out.”
GE Digital doesn’t “like to make bets; we would like to aggregate all those pieces of machine-learning devices,” Kodesh said, adding that the company will be spending more on research and development than makers of consumer algorithms.
Watch the full interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of the GE Predix Transform 2016.
@General Electric #GE #PredixTransform @SiliconANGLE theCUBE @theCUBE #theCUBE
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Harel Kodesh, GE Digital - #PredixTransform 2016 #theCUBE
Harel Kodesh, CTO of GE Digital, sits down with host Jeff Frick at Predix Transform 2016, at the Cosmopolitan Hotel in Las Vegas, Nevada.
Will the Industrial Internet usher in a bigger, better algorithm? | #PredixTransform
https://siliconangle.com/2016/07/29/will-the-industrial-internet-usher-in-a-bigger-better-algorithm-predixtransform/
Most consumers’ experiences with algorithms do not go much further than Amazon’s product recommendations. Thus, they see algorithms as hit or miss — sometimes they work, sometimes they don’t, and it’s usually not a big deal. But as large companies with important missions are utilizing algorithms associated with Internet of Things (IoT) in their operations, they are demanding much greater accuracy. And GE Digital believes it will be the one to meet that demand.
Harel Kodesh, CTO of GE Digital, believes that we are seeing the development of a brand new ecosystem, which he calls the Industrial Internet. He told Jeff Frick, cohost of theCUBE, from the SiliconANGLE Media team, during the GE Predix Transform event that he believes GE Digital’s Predix is uniquely poised to be the cloud platform of choice for this new domain.
Kodesh explained that Predix focuses on assets, in some cases very expensive and high-maintenance ones, like aircraft. He said they will have to bring the incidence of false positives and false negatives down for use by big industries. “Our machine-learning algorithm will have to be of a different breed than what you have for consumers,” he said.
Building a better algorithm
Kodesh said that Predix wants to make optimizing IoT applications a priority. “We have to make sure the developers have the freedom to decide what to put in the cloud and what to put close to the edge,” he said.
He went on to talk about how the company is planning to take the accuracy of algorithms to a new level. He spoke about different types of machine learning, such as supervised learning where “you tell the system what are the basic things it has to look for, and you let it figure it out itself.” He added: “And on the extreme side, you have unsupervised learning where you define for the machine what is going to be the winning function, what it needs to do, and it figures it out.”
GE Digital doesn’t “like to make bets; we would like to aggregate all those pieces of machine-learning devices,” Kodesh said, adding that the company will be spending more on research and development than makers of consumer algorithms.
Watch the full interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of the GE Predix Transform 2016.
@General Electric #GE #PredixTransform @SiliconANGLE theCUBE @theCUBE #theCUBE
