Empowering Enterprises with Intel's AI Portfolio

Table of Contents

1. Introduction
2. Efforts at Intel to Scale AI in Enterprise
   • Collaboration with Databricks
   • Optimizing Databricks Runtime and Photon Engine
   • Incorporating Intel AI Libraries in Databricks
3. Overview of Intel's AI Portfolio
   • Hardware Accelerators for AI
   • Intel's CPU Acceleration for AI
   • Intel's GPU Acceleration for AI
   • Habana AI Training Solutions
4. AI Software Tools by Intel
   • OpenVINO for Inferencing
   • SigOpt for Model Optimization
   • SkullConverge for ML Ops
   • BigDL for Scaling AI
5. Intel's Investments in AI
   • AI Builders Program
   • Intel Capital's Investment and Acquisitions
6. Conclusion

Scaling AI in Enterprise: Intel's Efforts and AI Portfolio

Artificial Intelligence (AI) has become an integral part of enterprise operations, driving innovation and efficiency. Intel, a global technology leader, has made significant strides in scaling AI solutions in the enterprise domain. In this article, we will delve into Intel's efforts to Scale AI in enterprise, their collaboration with Databricks, and their comprehensive AI portfolio comprising of hardware accelerators and software tools.

Introduction

AI has revolutionized various industries, enabling businesses to automate processes, make informed decisions, and deliver personalized experiences. As AI continues to gain Momentum, Intel recognizes the need to optimize workloads on the cloud and enhance AI capabilities for enterprises.

Efforts at Intel to Scale AI in Enterprise

Collaboration with Databricks

Intel has been collaborating closely with Databricks, a leading data and AI company, to optimize AI workloads. One significant area of collaboration is the optimization of Databricks Runtime and the Photon Engine. By incorporating Intel's expertise, Databricks has achieved improved performance and efficiency in executing AI workloads.

Optimizing Databricks Runtime and Photon Engine

Databricks Runtime, a cloud-native platform, allows users to analyze and process vast amounts of data for AI applications. Intel's collaboration with Databricks focuses on optimizing the runtime and the Photon Engine, which is a key component of Databricks Runtime. The optimization efforts aim to enhance the performance and scalability of AI workloads on the cloud.

Incorporating Intel AI Libraries in Databricks

To further bolster AI capabilities, Intel has been working on integrating optimized AI libraries into the Databricks platform. These libraries provide developers with access to highly optimized functions and algorithms, enabling them to accelerate AI workflows. By leveraging Intel's AI libraries within Databricks, enterprises can enhance the performance and efficiency of their AI applications.

Overview of Intel's AI Portfolio

Intel offers a comprehensive portfolio of hardware accelerators specifically designed to accelerate AI workloads. These hardware accelerators are integrated into Intel's CPUs, GPUs, and specialized AI training solutions. Let's explore these accelerators in detail.

Hardware Accelerators for AI

Intel's CPUs are equipped with AI accelerators that optimize the most commonly used mathematical operation in AI: matrix multiplication. Intel has introduced three generations of accelerators in their CPUs: Cascade Lake, Cooper Lake, and the upcoming Sapphire Rapids. Each generation has brought improved performance and sophistication to accelerate matrix multiplication.

Intel's CPU Acceleration for AI

Cascade Lake, the first AI accelerator from Intel, introduced AVX-512 VNNI, focusing on accelerating matrix multiplication. Cooper Lake, the Second-generation accelerator, introduced a new data type called bfloat16. By reducing the mantissa and precision, Cooper Lake improves AI performance while maintaining efficiency. The most advanced CPU acceleration, AMX, will be introduced with Sapphire Rapids, further enhancing AI workloads' performance and capabilities.

Intel's GPU Acceleration for AI

While Intel CPUs excel in CPU-Based ai workloads, Intel also offers GPUs for AI applications. Arctic Sound is a multi-purpose GPU suitable for inference tasks. It provides excellent performance for various workloads like VDI, media analytics, and cloud gaming. Additionally, Intel's upcoming GPU, Ponte Vecchio, will support AI model training, further expanding Intel's GPU offerings in the AI domain.

Habana AI Training Solutions

Intel's acquisition of Habana two years ago has enriched their AI portfolio. Habana's AI training solutions provide cost-effective alternatives for deep learning training. With superior performance and affordability, Habana's solutions have attracted customers like Supermicro and AWS. These solutions support various popular deep learning models, making them accessible and efficient for training AI models.

AI Software Tools by Intel

To complement their hardware offerings, Intel provides several AI software tools designed to streamline AI development and deployment. Let's explore these tools:

OpenVINO for Inferencing

OpenVINO is Intel's software tool designed for efficient inferencing. Developers can build models with optimized AI frameworks provided by Intel and deploy them on any hardware using OpenVINO. OpenVINO supports various AI applications like computer vision and natural language processing, enabling deployment on edge devices or data centers.

SigOpt for Model Optimization

SigOpt is an AI model optimization tool offered by Intel. With SigOpt's automatic optimization capabilities, developers can fine-tune their models effortlessly. The tool uses vision optimization techniques to speed up AI training, reducing training time significantly. SigOpt has proven to be a valuable asset for organizations like PayPal and Two Sigma, who have reported impressive reductions in training time and cost savings.

SkullConverge for ML Ops

SkullConverge, an end-to-end ML Ops platform, simplifies the training and deployment of AI models. With its user-friendly interface and integration with popular frameworks like Kubernetes, SkullConverge enables easy machine learning development, training, and deployment. This platform is particularly useful for users who are not experts in DevOps, streamlining their AI workflows.

BigDL for Scaling AI

Intel's open-source project, BigDL, facilitates the scaling of AI from individual laptops to data centers effortlessly. Users can develop and deploy models on any hardware using optimized CPU functions offered by BigDL. Many prominent companies like Mastercard, Burger King, and Alibaba have leveraged BigDL to deploy and scale their AI solutions, making it a robust and reliable tool for enterprises.

Intel's Investments in AI

Intel recognizes the power of collaboration and innovation in the AI space. Through their AI Builders program, Intel invests in various companies and partners with them to provide cutting-edge AI solutions to customers. Additionally, Intel Capital, the strategic investment arm of Intel, makes acquisitions and investments in AI startups to foster growth and expand their AI expertise.

Conclusion

Intel's relentless efforts to scale AI in enterprise have resulted in a comprehensive portfolio of AI hardware accelerators and software tools. With collaborations with industry leaders like Databricks and strategic acquisitions, Intel is well-positioned to drive AI innovation and enable organizations to harness the full potential of AI. Whether it's through optimized CPUs, GPUs, AI software tools, or strategic investments, Intel is committed to empowering enterprises to accelerate their AI journey and transform industries.