Intel Chip Chat

Microsoft SQL Server is one of the most deployed databases on the planet, with millions of customers worldwide. So it’s important to understand how customers will be affected by emerging technologies, particularly in this era of digital transformation. Ken LeTourneau, Enterprise Solutions Architect in the Data Center Group at Intel, explains what impact data center technologies like Intel® OptaneTM DC Persistent Memory will have for customers deploying SQL Server 2019.

What worked, even a few years ago, in the data center won’t support the demands of today. As Ken says, "It's no longer about hindsight, it's about insight.” SQL Server 2019 provides industry-leading performance and security, with intelligence over all of an enterprise’s data -- structured or unstructured. SQL Server 2019 with new big data features provides an easier path to acting on data, and with support for Intel Optane DC Persistent Memory, it can deliver larger memory-optimized databases for scale-up and scale-out system landscapes. As Ken explains, SQL Server is no longer simply a way to run queries. It's an intelligent data platform that enables advanced data work such as prescriptive analytics. Distributed data bases, intelligence at the edge, and beefing up analytics and insights capabilities are changing the way customers should think about building data bases.

Learn more about how Intel and Microsoft are enabling this intelligence from the edge to the cloud here.

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Academic research and theoretical work on deep learning have predicted an exciting future for deep learning, and now real-world technology is catching up with some of the most exciting potential of AI. Inference is a particularly fascinating part of AI, as it’s what powers the ability of neural networks to “predict” what certain data looks or sounds like. The Intel Nervana Neural Network Processor for Inference (NNP-I) is purpose-built for intensive inference workloads, and accelerating this crucial part of artificial intelligence.

Gadi Singer is the VP and General Manager of the Artificial Intelligence Products Group at Intel, and a 29-year veteran of the company. In this interview, Gadi holds forth on both the high-level design philosophy informing the NNP-I’s structure, and the finer details of its design, such as power efficiency, optimizing data movement, and software support. He also talks about which industries and areas can potentially be transformed by better inference, such as image analysis, automated recommendation systems, and natural language processing.

To learn more about the Intel Nervana Neural Network Processor for Inference go to: https://www.intel.ai/nervana-nnp/

Intel and the Intel logo are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries. © Intel Corporation

Deep learning workloads have evolved considerably over the last few years. Today’s models are larger, deeper, and more complex than neural networks from even a few years ago, with an explosion in size in the number of parameters per model. The Intel Nervana Neural Network Processor for Training (NNP-T) is a purpose-built deep learning accelerator to speed up the training and deployment of distributed learning algorithms.

Carey Kloss is the VP and General Manager of the AI Training Products Group at Intel. In this interview, Kloss outlines the architecture and potential of the Intel Nervana NNP-T. He gets into major issues like memory and how the architecture was designed to avoid problems like becoming memory-locked, how the accelerator supports existing software frameworks like PaddlePaddle and TensorFlow, and what the NNP-T means for customers who want to keep on eye on power usage and lower TCO.

To learn more about the Intel Nervana Neural Network Processor for Training go to: https://www.intel.ai/nervana-nnp/

Intel and the Intel logo are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries. © Intel Corporation

Deep learning workloads have evolved considerably over the last few years. Today’s models are larger, deeper, and more complex than neural networks from even a few years ago, with an explosion in size in the number of parameters per model. The Intel Nervana Neural Network Processor for Training (NNP-T) is a purpose-built deep learning accelerator to speed up the training and deployment of distributed learning algorithms.

Carey Kloss is the VP and General Manager of the AI Training Products Group at Intel. In this interview, Kloss outlines the architecture and potential of the Intel Nervana NNP-T. He gets into major issues like memory and how the architecture was designed to avoid problems like becoming memory-locked, how the accelerator supports existing software frameworks like PaddlePaddle and TensorFlow, and what the NNP-T means for customers who want to keep on eye on power usage and lower TCO.

To learn more about the Intel Nervana Neural Network Processor for Training go to: https://www.intel.ai/nervana-nnp/

Intel and the Intel logo are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries. © Intel Corporation

Deep learning workloads have evolved considerably over the last few years. Today’s models are larger, deeper, and more complex than neural networks from even a few years ago, with an explosion in size in the number of parameters per model. The Intel Nervana Neural Network Processor for Training (NNP-T) is a purpose-built deep learning accelerator to speed up the training and deployment of distributed learning algorithms.

Carey Kloss is the VP and General Manager of the AI Training Products Group at Intel. In this interview, Kloss outlines the architecture and potential of the Intel Nervana NNP-T. He gets into major issues like memory and how the architecture was designed to avoid problems like becoming memory-locked, how the accelerator supports existing software frameworks like PaddlePaddle and TensorFlow, and what the NNP-T means for customers who want to keep on eye on power usage and lower TCO.

To learn more about the Intel Nervana Neural Network Processor for Training go to: https://www.intel.ai/nervana-nnp/

Intel and the Intel logo are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries. © Intel Corporation

Academic research and theoretical work on deep learning have predicted an exciting future for deep learning, and now real-world technology is catching up with some of the most exciting potential of AI. Inference is a particularly fascinating part of AI, as it’s what powers the ability of neural networks to “predict” what certain data looks or sounds like. The Intel Nervana Neural Network Processor for Inference (NNP-I) is purpose-built for intensive inference workloads, and accelerating this crucial part of artificial intelligence.

Gadi Singer is the VP and General Manager of the Artificial Intelligence Products Group at Intel, and a 29-year veteran of the company. In this interview, Gadi holds forth on both the high-level design philosophy informing the NNP-I’s structure, and the finer details of its design, such as power efficiency, optimizing data movement, and software support. He also talks about which industries and areas can potentially be transformed by better inference, such as image analysis, automated recommendation systems, and natural language processing.

To learn more about the Intel Nervana Neural Network Processor for Inference go to: https://www.intel.ai/nervana-nnp/

Intel and the Intel logo are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries. © Intel Corporation

In this episode, Rick Cnossen talks with Allyson about a joint solution created by Intel and VMware to make the experience of operationalizing enterprise analytics and AI simpler and more cost effective. Rick is Senior Director of Global AI Sector Solutions with the Enterprise and Government team at Intel. He explains that operationalizing analytics and AI is a goal for many companies, but there are still barriers. It's complicated and can be expensive and must be done in the context of hybrid cloud transformation with continued support for legacy workloads. Intel and VMware have created an "easy button" of sorts with the new Hybrid Cloud Data Analytics Solution. It’s an end-to-end solution that provides comprehensive analytics; it’s also easy to manage and can run in the cloud.

For more information, visit intel.com/vmware and download the solution brief.

Intel technologies' features and benefits depend on system configuration and may require enabled hardware, software or service activation. Performance varies depending on system configuration.

No product or component can be absolutely secure. Check with your system manufacturer or retailer or learn more at intel.com.

Intel, the Intel logo, [List the Intel trademarks in your document] are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries.

*Other names and brands may be claimed as the property of others.

© Intel Corporation

In this episode of Intel Chip Chat, Jim Gordon, GM of Ecosystem Business Development, Strategy and Communication for Intel, joins us to talk about Intel’s next generation Intel® Xeon E processors and Intel® Software Guard Extensions (Intel® SGX). Jim talks about how Intel delivers the building blocks for security to CSPs, ISVs and other ecosystem partners that enable them to improve the security capabilities they offer to their customers, both in hardware and software. Intel now has general availability of the new Intel® Xeon E-2200 processors for server with double the Intel SGX enclave size – now 256MB. Take a listen to learn how this is leading to even more possibilities for new security use cases and developer innovation in HW based security.

To learn more about developing solutions with Intel SGX, visit https://software.intel.com/sgx.

In this episode of Intel Chip Chat, Jim Gordon, GM of Ecosystem Business Development, Strategy and Communication for Intel, joins us to talk about Intel’s next generation Intel® Xeon E processors and Intel® Software Guard Extensions (Intel® SGX). Jim talks about how Intel delivers the building blocks for security to CSPs, ISVs and other ecosystem partners that enable them to improve the security capabilities they offer to their customers, both in hardware and software. Intel now has general availability of the new Intel® Xeon E-2200 processors for server with double the Intel SGX enclave size – now 256MB. Take a listen to learn how this is leading to even more possibilities for new security use cases and developer innovation in HW based security.

To learn more about developing solutions with Intel SGX, visit https://software.intel.com/sgx.

In this episode of Intel Chip Chat, Jim Gordon, GM of Ecosystem Business Development, Strategy and Communication for Intel, joins us to talk about Intel’s next generation Intel® Xeon E processors and Intel® Software Guard Extensions (Intel® SGX). Jim talks about how Intel delivers the building blocks for security to CSPs, ISVs and other ecosystem partners that enable them to improve the security capabilities they offer to their customers, both in hardware and software. Intel now has general availability of the new Intel® Xeon E-2200 processors for server with double the Intel SGX enclave size – now 256MB. Take a listen to learn how this is leading to even more possibilities for new security use cases and developer innovation in HW based security.

To learn more about developing solutions with Intel SGX, visit https://software.intel.com/sgx.