DataRobot announced a collaboration with Intel, an investor in DataRobot, to power the development and deployment of machine learning models and enable business users of all skill levels to easily harness the power of AI.
As part of the partnership, DataRobot will leverage Intel® technologies, including Intel® Xeon® Scalable processors, to power its automated machine learning platform. Intel Xeon Scalable processors provide the hardware foundation to deliver optimized performance boosts for organizations in pursuit of low latency and scalability – two key features to support the AI-driven enterprise. DataRobot automates machine learning to significantly improve productivity for organizations of all sizes and maximize value from data analytics initiatives.
“Across insurance, banking, manufacturing, life sciences, marketing, and countless additional industries, machine learning is systematically allowing organizations to solve business problems faster and more effectively than ever before,” said Phil Gurbacki, DataRobot VP, Product Management. “It has been our mission from day one to deliver a solution that empowers all business users to automate their data science initiatives and achieve immediate value from their data. Our work with Intel significantly enhances our platform by powering it with Intel Xeon Scalable processors that have the compute and memory to handle the widest range of machine learning workloads.”
“Enterprises are looking to gain deeper, more impactful data-driven insights without the exorbitant costs and time commitments accompanying traditional modeling methods,” said Lisa Davis, Vice President and General Manager of Digital Transformation for Enterprise & Government at Intel. “The combination of DataRobot’s automated technology and Intel Xeon Scalable processors helps alleviate these concerns, allowing organizations to quickly develop and utilize powerful machine learning capabilities through a ready-built solution for data science success based on the platforms enterprises know and trust. We recognize DataRobot as a transformational technology in today’s AI-driven business landscape.”
The combination of massive compute power and the unprecedented rate of data generation has created an opportunity for every organization to unlock value from their data and hone in on opportunities for growth and business process optimization. But organizations face significant barriers to AI adoption, led by a lack of data science expertise in the global workforce. DataRobot automates the entire data science and machine learning workflow, eliminating the need for organizations to assemble a large team of data scientists with advanced coding skills and augmenting the capabilities of those organizations that do have data science teams.
Archive
- October 2024(27)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)