CLOUDERA, INC. ORLANDO, Fla., Oct. 17, 2018 /PRNewswire/ -- Gartner Symposium ITxpo -- Cloudera, Inc., (NYSE: CLDR), the modern platform for machine learning and analytics optimized for the cloud, today announced its strategic vision to accelerate the industrialization of enterprise machine learning (ML) and artificial intelligence (AI)—making the process of building, scaling, and deploying enterprise machine learning automated, repeatable and predictable. Through Cloudera's platform for ML, Cloudera Data Science Workbench development environment and applied AI advising and research offerings, Cloudera has enabled hundreds of enterprises to gain greater insight from their data, detect anomalous activity and predict events. Now, Cloudera intends to expand its customers' success in these areas with a vision for industrializing AI. Cloudera customers will be able to automate decisions at enterprise scale. Building, deploying and scaling ML/AI applications will become repeatable with what Cloudera calls an 'AI Factory' for turning data into decisions, at any scale, anywhere.
Click to Tweet: Hear @hmason talk about @Cloudera's vision for industrializing #AI and the radical changes in store for the future. Unveiling details: http://bit.ly/2PDOf0I #IndustrializeAI #AIFactory #MachineLearning
"The modern enterprise will be a network of intelligent applications powered by machine learning and AI. Right now the effort that goes into building ML and AI solutions is heavily skewed towards allocating and maintaining underlying infrastructure, instead of building a compounding set of capabilities that can deliver increased business values," said Hilary Mason, general manager, Machine Learning at Cloudera. "AI deployments should be boring, meaning the process for deploying and scaling these types of applications should be routine. We should be paying attention to the value generated, not to the technology. This is why Cloudera is evolving its products and platform to industrialize the process of delivering AI solutions at enterprise scale."
Today, no single platform unifies and powers all ML and AI workflows. Isolated ML and AI projects that employ disparate technology stacks result in duplicated efforts across the enterprise. Siloed infrastructure introduces quality issues and risk associated with security, governance, and compliance. Reliance on bespoke solutions comes at the cost of internal skill building and differentiation. Lock-in to single vendor environments can limit the flexibility and agility needed to innovate and capitalize on new business opportunities. These common challenges present barriers to successfully operationalizing and scaling ML/AI capabilities at enterprise scale.
Industrialized enterprise ML and AI resolves these challenges, empowering businesses to build a repeatable AI Factory for turning data into decisions, at any scale, anywhere. Such an AI Factory requires a modern technical foundation; a platform for managing connected data workflows across multiple cloud and on-premise environments. An AI Factory enables businesses to own and protect their data and intellectual property, maintaining control of their future and injecting AI into every part of the business that can be automated—reliably, predictably and securely.
Building on deep experience in machine learning, analytics and cloud, Cloudera plans to accelerate its roadmap to help customers more rapidly capitalize on the value of their data with ML and AI capabilities. Cloudera will deliver seamless, elastic, end-to-end machine learning workflows spanning public and private clouds as part of its recently announced enterprise data cloud strategy. Cloudera will also expand support for the latest open data science tools, from Python and R to Spark and Tensorflow, to streamline unified data pipeline and AI model management at scale while minimizing cost and risk.
Unveiling of Industrialized AI with Enterprise Scale Machine Learning Vision at Gartner Symposium
On October 17 at 3:15 - 4:00 pm ET, Mason will present her vision of Industrialized AI with Enterprise Scale Machine Learning at the Gartner Symposium ITxpo. If unable to make the event in Orlando, register for Mason's live webinar on November 7, "Industrialized AI with Enterprise Scale Machine Learning" and available on-demand after.
Additional Resources
- Watch an on-demand webinar Demystifying ML & AI on how to identify and execute on practical machine learning opportunities, presented by Hilary Mason
- Get practical guidance and clarity with Cloudera Fast Forward Labs Research
- Learn more about Cloudera's Machine Learning Advisory Services
Connect with Cloudera
About Cloudera: cloudera.com/more/about.html
Read our VISION blog: vision.cloudera.com/ and Engineering blog: blog.cloudera.com/
Follow us on Twitter: twitter.com/cloudera and LinkedIn: linkedin.com/cloudera/
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See us on YouTube: youtube.com/user/clouderahadoop/featured
Join the Cloudera Community: community.cloudera.com/
Read about our customers' successes: cloudera.com/more/customers.html
For information on Cloudera Enterprise and SDX: cloudera.com/products/sdx.html
Cloudera and associated marks and trademarks are registered trademarks of Cloudera, Inc. All other company and product names may be trademarks of their respective owners.
This press release contains forward-looking statements including, among other things, statements regarding the expected performance and benefits of Cloudera's offerings. The words "believe," "may," "will," "plan," "expect," and similar expressions are intended to identify forward-looking statements. These forward-looking statements are subject to risks, uncertainties, and assumptions. If the risks materialize or assumptions prove incorrect, actual results could differ materially from the results implied by these forward-looking statements. Risks include, but are not limited to, risks described in our filings with the Securities and Exchange Commission (SEC), including our Form S-1 Registration Statement, and our future reports that we may file with the SEC from time to time, which could cause actual results to vary from expectations. Cloudera assumes no obligation to, and does not currently intend to, update any such forward-looking statements after the date of this release.
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SOURCE Cloudera, Inc.
