Intel’s Gaudi 3 Empowers Enterprise AI, Embracing Open Systems and Securing New Customers

At the Intel Vision 2024 conference, Intel launched its latest products aimed at addressing the challenges faced by businesses in scaling AI initiatives. The highlight of the event was the introduction of the Intel Gaudi 3 accelerator, which promises to bring performance, openness, and choice to enterprise generative AI (GenAI). With only 10% of enterprises successfully moving GenAI projects into production last year, Intel aims to provide readily available solutions that address complexity, fragmentation, data security, and compliance requirements.

Intel CEO Pat Gelsinger emphasized the company’s commitment to bringing AI everywhere across the enterprise, from the PC to the data center to the edge. The latest Gaudi, Xeon, and Core Ultra platforms offer flexible solutions tailored to meet the changing needs of customers and partners.

The Intel Gaudi 3 AI accelerator is designed to power AI systems with tens of thousands of accelerators connected through Ethernet. It promises 4x more AI compute for BF16 and a 1.5x increase in memory bandwidth compared to its predecessor. The Gaudi 3 accelerator is expected to deliver faster time-to-train and superior inference throughput compared to nVidia H100.

The Gaudi 3 accelerator provides open, community-based software and industry-standard Ethernet networking, allowing enterprises to scale from a single node to clusters, super-clusters, and mega-clusters. It supports inference, fine-tuning, and training at the largest scale. The Gaudi 3 accelerator will be available to OEMs in the second quarter of 2024.

Intel also outlined its strategy for open scalable AI systems, which includes hardware, software, frameworks, and tools. The approach enables a broad ecosystem of AI players to offer solutions that meet enterprise-specific GenAI needs. This includes equipment manufacturers, database providers, systems integrators, software and service providers, and others.

Intel showcased its collaborations with various enterprise customers and partners across industries. These collaborations involve deploying Intel Gaudi accelerator solutions for new and innovative generative AI applications. Partners include NAVER, Bosch, IBM, Ola/Krutrim, NielsenIQ, Seekr, IFF, CtrlS Group, Bharti Airtel, Landing AI, Roboflow, Infosys, and more.

Intel also announced collaborations with Google Cloud, Thales, and Cohesity to leverage Intel’s confidential computing capabilities in their cloud instances. This enables customers to run their AI models and algorithms in a trusted execution environment and leverage Intel’s trust services for independently verifying the trustworthiness of these environments.

In collaboration with a range of industry players, Intel announced its intention to create an open platform for enterprise AI. The goal is to develop open, multivendor GenAI systems that deliver ease-of-deployment, performance, and value. The effort aims to accelerate the use of GenAI in enterprises and broaden solution coverage.

Intel provided updates on its next-generation products and services across all segments of enterprise AI. This includes the introduction of the new Intel Xeon 6 processors with E-Cores and P-Cores. The E-core processors offer a 4x performance per watt improvement and 2.7x better rack density compared to the previous generation. The P-core processors incorporate software support for the MXFP4 data format, reducing Latency and enabling improved AI performance.

Intel also announced updates to its client, edge, and connectivity roadmap. The Intel Core Ultra processors are powering new capabilities for productivity, security, and content creation. Intel expects to ship 40 million AI PCs in 2024 with over 230 designs. The company also launched new edge silicon across its product families, targeting key markets such as retail, industrial manufacturing, and healthcare.

To streamline the deployment of enterprise software and services, Intel introduced the Intel Tiber portfolio of business solutions. This unified experience aims to make it easier for customers and developers to find solutions that fit their needs while ensuring security, compliance, and performance.

Overall, Intel’s announcements at Vision 2024 demonstrate the company’s commitment to making AI accessible, open, and secure for enterprises worldwide. With its latest products and collaborations, Intel is poised to lead the way in the AI revolution and unlock unprecedented value for businesses.

Background Information

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About Google: Google, founded by Larry Page and Sergey Brin in 1998, is a multinational technology company known for its internet-related services and products. Initially for its search engine, Google has since expanded into various domains including online advertising, cloud computing, software development, and hardware devices. With its innovative approach, Google has introduced influential products such as Google Search, Android OS, Google Maps, and Google Drive. The company's commitment to research and development has led to advancements in artificial intelligence and machine learning.

  

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About IBM: IBM, or International Business Machines Corporation, is a globally American multinational technology company with a storied history dating back to its founding in 1911. Over the decades, IBM has consistently been at the forefront of innovation in the field of information technology. The company is known for its pioneering work in computer hardware, software, and services, with breakthroughs like the IBM System/360 and the invention of the relational database.

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About Intel: Intel Corporation, a global technology leader, is for its semiconductor innovations that power computing and communication devices worldwide. As a pioneer in microprocessor technology, Intel has left an indelible mark on the evolution of computing with its processors that drive everything from PCs to data centers and beyond. With a history of advancements, Intel's relentless pursuit of innovation continues to shape the digital landscape, offering solutions that empower businesses and individuals to achieve new levels of productivity and connectivity.

  

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About nVidia: NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.

  

Technology Explained

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E-Cores: E-Cores (Efficiency Cores) are a type of technology used in the computer industry to provide a more efficient and reliable way of powering and cooling computer components. They are made up of a combination of copper and aluminum, and are designed to be more efficient than traditional copper cores. E-Cores are used in a variety of applications, such as in CPUs, GPUs, and other computer components. They are also used in servers, laptops, and other electronic devices. The technology is designed to reduce heat and power consumption, while also providing a more reliable and efficient way of powering and cooling computer components.

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Latency: Technology latency is the time it takes for a computer system to respond to a request. It is an important factor in the performance of computer systems, as it affects the speed and efficiency of data processing. In the computer industry, latency is a major factor in the performance of computer networks, storage systems, and other computer systems. Low latency is essential for applications that require fast response times, such as online gaming, streaming media, and real-time data processing. High latency can cause delays in data processing, resulting in slow response times and poor performance. To reduce latency, computer systems use various techniques such as caching, load balancing, and parallel processing. By reducing latency, computer systems can provide faster response times and improved performance.

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P-Cores: P-Cores (Performance Cores) are a type of processor technology developed by Intel that is designed to improve the performance of computer systems. This technology is based on the concept of multi-core processors, which are processors that contain multiple cores or processing units. P-Cores are designed to increase the speed and efficiency of computer systems by allowing multiple cores to work together in parallel. This technology is used in a variety of applications, including gaming, video editing, and data analysis. P-Cores are also used in servers and other high-performance computing systems. The technology is also used in mobile devices, such as smartphones and tablets, to improve battery life and performance. P-Cores are an important part of the computer industry, as they allow for faster and more efficient computing.

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Xeon: The Intel Xeon processor is a powerful and reliable processor used in many computer systems. It is a multi-core processor that is designed to handle multiple tasks simultaneously. It is used in servers, workstations, and high-end desktop computers. It is also used in many embedded systems, such as routers and switches. The Xeon processor is known for its high performance and scalability, making it a popular choice for many computer applications. It is also used in many cloud computing applications, as it is capable of handling large amounts of data and providing high levels of performance. The Xeon processor is also used in many scientific and engineering applications, as it is capable of handling complex calculations and simulations.