This Week in Analytics & AI News

  • Learn how Intel plans to deliver “supercomputing for all”
  • Catch up on sessions from Intel oneAPI DevFest
  • Train more while spending less with a new AI training solution
  • Register for instructor-led training on the OpenVINO™ toolkit
  • Stream the latest episode of the “Intel on AI” podcast

Supercomputing for All Is Closer Than You Think

Kicking things off for Intel at SC21, VP and GM of the Super Compute Group Jeff McVeigh took the virtual stage to talk about Intel’s strategy for democratizing HPC and delivering “supercomputing for all.” The foundation for that strategy? Exponential improvements in HPC performance, openness, and scale.

Replay Sessions From Intel oneAPI DevFest

Miss out on last month’s Intel oneAPI DevFest, part of the inaugural Intel Innovation virtual event? Catch up with sessions and in-depth tutorials, including technical and lightning talks on parallel programming models, AI analytics, tools, performance libraries, rendering toolkits, and FPGA​s.

Intel’s Habana Labs Announces Turnkey AI Training Solution

Habana Labs has announced a new enterprise-class AI training solution featuring the Supermicro X12 Gaudi AI training server and DDN AI400X2 storage system. Featuring eight purpose-built Habana® Gaudi® AI processors, the turnkey solution empowers customers to train more while spending less.

Get Trained on the Intel Distribution of OpenVINO Toolkit

Want to learn how to develop high-performance applications and enable DL inference from edge to cloud? Register for a two-day online training where Intel instructors will take you through the workflow using the OpenVINO™ toolkit, including support for accelerating DL algorithm deployment in your apps.

Intel on AI: Biological Intelligence and the Limitations of Deep Neural Networks

In case you missed it, the “Intel on AI” podcast is back for a third season. In episode two, Intel’s Amir Khosrowshahi speaks with Melanie Mitchell, Davis Professor of Complexity at the Santa Fe Institute, about the paradox of studying human intelligence and the limitations of deep neural networks.