IBM and AMD agree to tackle cloud privacy and artificial intelligence together

IBM and AMD agree to tackle cloud privacy and artificial intelligence together

IBM and AMD today announced a multi-year agreement to work together on security and artificial intelligence. As stated in the related press release, the partners intend to “rely on open source software, open standards and open system architectures to manage sensitive computing in hybrid cloud environments and support a wide range of accelerators in high performance computing (HPC) and mission-critical enterprise opportunities – such as virtualization and encryption. “

“AMD’s commitment to technology innovation is aligned with our mission to develop and accelerate hybrid cloud adoption to help connect, protect and support our digital world,” said Dario Gil, director of research, IBM. “IBM is focused on providing our customers with choice, flexibility and security in our hybrid cloud offerings through cutting edge research, development and scaling of new technologies.”

“This agreement between AMD and IBM aligns well with our longstanding commitment to partnering with industry leaders,” said Mark Papermaster, executive vice president and chief technology officer, AMD. “AMD is excited to expand our work with IBM on AI, accelerating data center workloads and improving security in the cloud.”

For many companies, securing highly sensitive data remains a challenge: according to the IBM Institute for Business Value, cybersecurity is currently a major obstacle to adoption, as well as a primary criterion for choosing cloud providers.

Confidential Computing is a hardware-assisted technology that encrypts data associated with a virtual machine, including while running workloads. This feature helps prevent attackers from gaining access to confidential information even if compromised. Hybrid cloud private computing is unlocking new potential for enterprise adoption of hybrid cloud computing.

IBM and AMD agree to tackle cloud privacy and artificial intelligence together

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