Flash storage vendor NetApp and real-time data science platform developer Iguazio Monday said they have teamed up to bring channel partners and business customers a joint offering aimed at improving the efficiency of artificial intelligence applications.
The joint offering is aimed at building the high-speed pipeline between the storage and analysis of data to improve the performance of AI and improve governance around the applications, said Asaf Somekh, CEO of the New York and Israel company.
“In the enterprise, there’s a lot of hype around AI, but a lot in inefficiencies,” Somekh told CRN. “You see data scientists building models and showing efficiencies in the lab getting the green light to launch products. But 85 percent of successful projects in the lab never see the light of day, according to Gartner. We have partnered with NetApp to change how AI is brought into the enterprise.”
[Related: NetApp Introduces Keystone: Simplifying Storage For Hybrid, Multi-Cloud World]
The joint AI platform combines NetApp storage and its Ontap AI software and NetApp Cloud Volumes for hybrid cloud capabilities, Iguazio’s data science platform for end-to-end machine learning pipeline automation, and Nvidia DGX GPUs which can be used on an as-a-service basis.
It ties closely to a new trend, machine learning operations, or MLops, aimed at operationalizing machine learning, Somekh said.
“A lot of ‘unicorns’ have built technology on the first step of AI, which is the lab,” he said. “Our Ignazio Data Science Platform is all about bringing the work from the lab and propagating it through the business. It runs in real-time to collect the different data pieces from live, real-time, and historical data on storage to do the processing.”
Hoseb Dermanlian, senior manager of AI go to market at Sunnyvale, Calif.-based NetApp, told CRN the joint offering is very much a channel play for NetApp.
NetApp has been building a Nvidia-NetApp channel in the last year, but has not been selling it direct to enterprises, Dermanlian said. The company already has five channel partners in the U.S. working with NetApp’s AI-focused offerings, he said.
“We will grow our partner base,” he said. “We won’t boil the ocean, but we will build the base.”
Coming up with a high-performance data pipeline for AI and machine learning has been a challenge for data scientists and data architects, said Juan Orlandini, chief architect at Insight, a Tempe, Ariz.-based solution provider and partner to both NetApp and Iguazio.
“It has been done for the cloud, but it’s harder for on-prem,” Orlandini told CRN. “Everyone thinks the data scientists are doing the hard stuff, and data science is hard. They need PhDs. But the other hard part is getting the data from the disparate services.”
Orlandini said this is because of the need to normalize the data from multiple sources and make it all look the same before an experiment on the data can be run.
“Then you’ll want to run another experiment on a different slice of the data, or use a different model, and then will need to put in into production and take it to the field,” he said. “Having a pipeline so the data architect can do his job and the data scientist can do his job is key. Iguazio handles the pipeline.”
The storage part is also really hard because of the need for performance, repeatability, and efficiency, Orlandini said.
“That’s what’s really good about the two companies working together,” he said. “On one side, you have the consumer of data, and the other side the infrastructure. Data architects and data scientists don’t want to be experts in storage. But in the past they were forced to be experts in storage and compute, and were really working two jobs, working with the data and making sure the data is available fast enough.”
The joint offering brings together the best of both sides, Orlandini said.
“With Ignazio and NetApp, if I’m an infrastructure person, I can provide the APIs to the software side and let them do their jobs,” he said. “And we at Insight can do this for our clients.”
The joint offering will be sold as a meet-in-the-channel solution, Dermanlian said.
Credit: Google News