Geoff Tudor, VP & GM, Vizion.ai, Panzura, talks with Stu Miniman & John Troyer at VMworld 2019 from Moscone North in San Francisco, CA.
#theCUBE #VMware #Panzura
https://siliconangle.com/2019/09/09/qa-data-give-insights-shall-receive-vmworld/
Q&A: The more data you give, the more insights you shall receive
Artificial-intelligence and machine-learning models go by the saying, “The more you give, the more you receive.” So, it is not about having the latest and best AI/ML prediction models, but about having a large and high-quality data set. Without enough data to feed an AI/ML model, they become pointless.
Acquiring data becomes one of the most important characteristics in building a solid AI strategy, according to Geoff Tudor (pictured), vice president and general manager, Vizion.ai, at Panzura Inc. Panzura helps users transfer large data sets in multicloud environments, reduce storage, and centralize management. Vision.ai a subdivision of Panzura, helps them make sense of all this data by allowing search, analysis and control capabilities. It uses AI prediction models to give large data sets a valuable meaning.
“In order to drive the value of machine data, especially when you’re looking at ML and AI … the larger the training data set, the better the prediction models,” Tudor said.
Tudor spoke with Stu Miniman (@stu), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, and guest host John Troyer (@jtroyer), chief reckoner at TechReckoning, during the VMworld event in San Francisco. They discussed Panzura’s services and differentiator, its intersection with VMware, and new announcements (see the full interview with transcript here). (* Disclosure below.)
[Editor’s note: The following answers have been condensed for clarity.]
Miniman: Set the table with us of Panzura today and the value of the sharing app.
Tudor: Panzura is known predominantly for its file services, of which we can provide a global collaborative namespace across multiple different locations. So … anything where you’re working with a lot of distributed groups that need access to the same kind of working set file. And big-data files have been using Panzura for file services for a number of years. We started to see that the growth of data is not only in user-generated content … but it’s the machine-generated data, and that’s what brought us to Vision.ai.
Miniman: So what’s the key [intellectual property] that differentiates from others in the marketplace?
Tudor: So, a couple of years ago, we took some of the core IP that we had … and said, “Let’s build a new cloud-native architecture to manage cloud-native digital machine-generated data.” And [to] be able to transfer that not only for the block storage, but to put in the object storage. So we created something called VBOS, Vizion.ai Block Object Storage, that allows us to index this data and then write it to object but, still, while it’s an object, have it still searchable. And that really unlocks the value of these very large data sets so you no longer have to push this off on a tape or push it off into object storage where it’s no longer available.
Troyer: Are we talking log files?
Tudor: We’ve created this [VBOS] as a service because in a multicloud world you need one platform where you can ingest these data feeds and these log feeds and then store and [be able to] search for them. People have been generating and deploying on-site log files for some time, but we’ve seen a large interest among our customer base in a hosted service that can securely store and make their logs accessible.
Miniman: What are some of the typical use cases, outcomes?
Tudor: So we went into this particular customer [with one of our key partners, phoenixNAP], on-boarded him in five minutes, created the dashboards for him, and now their logs are coming in a number of gigabytes per day. And that can visualize and find out any points of their operations that are creating problems and slow access time for their customers.
...
We’re kind of trying to turn machine-generated data and democratize it into “simple as a (* Disclosure: Panzura Inc. sponsored this segment of theCUBE. Neither Panzura nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
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Geoff Tudor, Panzura | VMworld 2019
Geoff Tudor, VP & GM, Vizion.ai, Panzura, talks with Stu Miniman & John Troyer at VMworld 2019 from Moscone North in San Francisco, CA.
#theCUBE #VMware #Panzura
https://siliconangle.com/2019/09/09/qa-data-give-insights-shall-receive-vmworld/
Q&A: The more data you give, the more insights you shall receive
Artificial-intelligence and machine-learning models go by the saying, “The more you give, the more you receive.” So, it is not about having the latest and best AI/ML prediction models, but about having a large and high-quality data set. Without enough data to feed an AI/ML model, they become pointless.
Acquiring data becomes one of the most important characteristics in building a solid AI strategy, according to Geoff Tudor (pictured), vice president and general manager, Vizion.ai, at Panzura Inc. Panzura helps users transfer large data sets in multicloud environments, reduce storage, and centralize management. Vision.ai a subdivision of Panzura, helps them make sense of all this data by allowing search, analysis and control capabilities. It uses AI prediction models to give large data sets a valuable meaning.
“In order to drive the value of machine data, especially when you’re looking at ML and AI … the larger the training data set, the better the prediction models,” Tudor said.
Tudor spoke with Stu Miniman (@stu), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, and guest host John Troyer (@jtroyer), chief reckoner at TechReckoning, during the VMworld event in San Francisco. They discussed Panzura’s services and differentiator, its intersection with VMware, and new announcements (see the full interview with transcript here). (* Disclosure below.)
[Editor’s note: The following answers have been condensed for clarity.]
Miniman: Set the table with us of Panzura today and the value of the sharing app.
Tudor: Panzura is known predominantly for its file services, of which we can provide a global collaborative namespace across multiple different locations. So … anything where you’re working with a lot of distributed groups that need access to the same kind of working set file. And big-data files have been using Panzura for file services for a number of years. We started to see that the growth of data is not only in user-generated content … but it’s the machine-generated data, and that’s what brought us to Vision.ai.
Miniman: So what’s the key [intellectual property] that differentiates from others in the marketplace?
Tudor: So, a couple of years ago, we took some of the core IP that we had … and said, “Let’s build a new cloud-native architecture to manage cloud-native digital machine-generated data.” And [to] be able to transfer that not only for the block storage, but to put in the object storage. So we created something called VBOS, Vizion.ai Block Object Storage, that allows us to index this data and then write it to object but, still, while it’s an object, have it still searchable. And that really unlocks the value of these very large data sets so you no longer have to push this off on a tape or push it off into object storage where it’s no longer available.
Troyer: Are we talking log files?
Tudor: We’ve created this [VBOS] as a service because in a multicloud world you need one platform where you can ingest these data feeds and these log feeds and then store and [be able to] search for them. People have been generating and deploying on-site log files for some time, but we’ve seen a large interest among our customer base in a hosted service that can securely store and make their logs accessible.
Miniman: What are some of the typical use cases, outcomes?
Tudor: So we went into this particular customer [with one of our key partners, phoenixNAP], on-boarded him in five minutes, created the dashboards for him, and now their logs are coming in a number of gigabytes per day. And that can visualize and find out any points of their operations that are creating problems and slow access time for their customers.
...
We’re kind of trying to turn machine-generated data and democratize it into “simple as a (* Disclosure: Panzura Inc. sponsored this segment of theCUBE. Neither Panzura nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
