AMD has released the new ROCm 6.3 version which introduces several new features and optimizations, including SGLang integration for accelerated AI inferencing, a re-engineered FlashAttention-2 for optimized AI training and inference, the introduction of multi-node Fast Fourier Transform (FFT), new Fortran compiler, and enhanced computer vision libraries like rocDecode, rocJPEG, and rocAL.

According to AMD, the SGLang, a runtime that is now supported by ROCm 6.3, is purpose-built for optimizing inference on models like LLMs and VLMs on AMD Instinct GPUs, and promises 6x higher throughput and much easier usage thanks to Python-integrated and pre-configured ROCm Docker containers. In addition, the AMD ROCm 6.3 also brings further transformer optimizations with FlashAttention-2, which should bring significant improvements in forward and backward pass compared to FlashAttention-1, a whole new AMD Fortran compiler with direct GPU offloading, backward compatibility, and integration with HIP Kernels and ROCm libraries, a whole new multi-node FFT support in rocFFT, which simplifies multi-node scaling and improved scalability, as well as enhanced computer vision libraries, rocDecode, rocJPEG, and rocAL, for AV1 codec support, GPU-accelerated JPEG decoding, and better audio augmentation.

The 64th edition of the TOP500 reveals that El Capitan has achieved the top spot and is officially the third system to reach exascale computing after Frontier and Aurora. Both systems have since moved down to No. 2 and No. 3 spots, respectively. Additionally, new systems have found their way onto the Top 10.

The new El Capitan system at the Lawrence Livermore National Laboratory in California, U.S.A., has debuted as the most powerful system on the list with an HPL score of 1.742 EFlop/s. It has 11,039,616 combined CPU and GPU cores and is based on AMD 4th generation EPYC processors with 24 cores at 1.8 GHz and AMD Instinct MI300A accelerators. El Capitan relies on a Cray Slingshot 11 network for data transfer and achieves an energy efficiency of 58.89 GigaFLOPS/watt. This power efficiency rating helped El Capitan achieve No. 18 on the GREEN500 list as well.

ASUS today announced its groundbreaking next-generation infrastructure solutions at SC24, featuring a comprehensive lineup powered by AMD and Intel, as well as liquid-cooling solutions designed to accelerate the future of AI. By continuously pushing the limits of innovation, ASUS simplifies the complexities of AI and high-performance computing (HPC) through adaptive server solutions paired with expert cooling and software-development services, tailored for the exascale era and beyond. As a total-solution provider with a distinguished history in pioneering AI supercomputing, ASUS is committed to delivering exceptional value to its customers.

Comprehensive line-up for AI and HPC success
To fuel enterprise digital transformation through HPC and AI-driven architecture, ASUS provides a full lineup of server systems that powered by AMD and Intel. Startups, research institutions, large enterprises or government organizations all could find the adaptive solutions to unlock value and accelerate business agility from the big data.

According to the market research firm Mercury Research, the desktop CPU market has witnessed a remarkable transformation, with AMD seizing a substantial 28.7% market share in Q3 of 2024—a giant leap since the launch of the original Zen architecture in 2017. This 5.7 percentage point surge from the previous quarter is a testament to the company's continuous innovation against the long-standing industry leader, Intel. Their year-over-year growth of nearly ten percentage points, fueled by the success of their Ryzen 7000 and 9000 series processors, starkly contrasts Intel's Raptor Lake processors, which encountered technical hurdles like stability issues. AMD's revenue share soared by 8.5 percentage points, indicating robust performance in premium processor segments. Intel, witnessing a decline in its desktop market share to 71.3%, attributes this shift to inventory adjustments rather than competitive pressure and still holds the majority.

AMD's success story extends beyond desktops, with the company claiming 22.3% of the laptop processor market and 24.2% of the server segment. A significant milestone was reached as AMD's data center division generated $3.549 billion in quarterly revenue, a new record for a company not even present in the data center in any considerable quantity just a decade ago. Stemming from strong EPYC processor sales to hyperscalers and cloud providers, along with Instinct MI300X for AI applications, AMD's acceleration of data center deployments is massive. Despite these shifts, Intel continues to hold its dominant position in client computing, with 76.1% of the overall PC market, held by its strong corporate relationships and extensive manufacturing infrastructure. OEM partners like Dell, HP, Lenovo, and others rely heavily on Intel for their CPU choice, equipping institutions like schools, universities, and government agencies.

AMD and Fujitsu Limited today announced that they have signed a memorandum of understanding (MOU) to form a strategic partnership to create computing platforms for AI and high-performance computing (HPC). The partnership, encompassing aspects from technology development to commercialization, will seek to facilitate the creation of open source and energy efficient platforms comprised of advanced processors with superior power performance and highly flexible AI/HPC software and aims to accelerate open-source AI and/or HPC initiatives.

Due to the rapid spread of AI, including generative AI, cloud service providers and end-users are seeking optimized architectures at various price and power per performance configurations. From end-to-end, AMD supports an open ecosystem, and strongly believes in giving customers choice. Fujitsu has worked to develop FUJITSU-MONAKA, a next-generation Arm-based processor that aims to achieve both high performance and low power consumption. With FUJITSU-MONAKA, together with AMD Instinct accelerators, customers have an additional choice to achieve large-scale AI workload processing to whilst attempting to reduce the data center total cost of ownership.

AMD today announced revenue for the third quarter of 2024 of $6.8 billion, gross margin of 50%, operating income of $724 million, net income of $771 million and diluted earnings per share of $0.47. On a non-GAAP basis, gross margin was 54%, operating income was $1.7 billion, net income was $1.5 billion and diluted earnings per share was $0.92.

"We delivered strong third quarter financial results with record revenue led by higher sales of EPYC and Instinct data center products and robust demand for our Ryzen PC processors," said AMD Chair and CEO Dr. Lisa Su. "Looking forward, we see significant growth opportunities across our data center, client and embedded businesses driven by the insatiable demand for more compute."

During the Open Compute Project (OCP) Summit 2024, Meta, one of the prime members of the OCP project, showed its NVIDIA "Blackwell" GB200 systems for its massive data centers. We previously covered Microsoft's Azure server rack with GB200 GPUs featuring one-third of the rack space for computing and two-thirds for cooling. A few days later, Google showed off its smaller GB200 system, and today, Meta is showing off its GB200 system—the smallest of the bunch. To train a dense transformer large language model with 405B parameters and a context window of up to 128k tokens, like the Llama 3.1 405B, Meta must redesign its data center infrastructure to run a distributed training job on two 24,000 GPU clusters. That is 48,000 GPUs used for training a single AI model.

Called "Catalina," it is built on the NVIDIA Blackwell platform, emphasizing modularity and adaptability while incorporating the latest NVIDIA GB200 Grace Blackwell Superchip. To address the escalating power requirements of GPUs, Catalina introduces the Orv3, a high-power rack capable of delivering up to 140kW. The comprehensive liquid-cooled setup encompasses a power shelf supporting various components, including a compute tray, switch tray, the Orv3 HPR, Wedge 400 fabric switch with 12.8 Tbps switching capacity, management switch, battery backup, and a rack management controller. Interestingly, Meta also upgraded its "Grand Teton" system for internal usage, such as deep learning recommendation models (DLRMs) and content understanding with AMD Instinct MI300X. Those are used to inference internal models, and MI300X appears to provide the best performance per Dollar for inference. According to Meta, the computational demand stemming from AI will continue to increase exponentially, so more NVIDIA and AMD GPUs is needed, and we can't wait to see what the company builds.

During its "Advancing AI" conference today, AMD has updated its AI accelerator portfolio with the Instinct MI325X accelerator, designed to succeed its MI300X predecessor. Built on the CDNA 3 architecture, Instinct MI325X brings a suite of improvements over the old SKU. Now, the MI325X features 256 GB of HBM3E memory running at 6 TB/s bandwidth. The capacity memory alone is a 1.8x improvement over the old MI300 SKU, which features 192 GB of regular HBM3 memory. Providing more memory capacity is crucial as upcoming AI workloads are training models with parameter counts measured in trillions, as opposed to billions with current models we have today. When it comes to compute resources, the Instinct MI325X provides 1.3 PetaFLOPS at FP16 and 2.6 PetaFLOPS at FP8 training and inference. This represents a 1.3x improvement over the Instinct MI300.

A chip alone is worthless without a good platform, and AMD decided to make the Instinct MI325X OAM modules a drop-in replacement for the current platform designed for MI300X, as they are both pin-compatible. In systems packing eight MI325X accelerators, there are 2 TB of HBM3E memory running at 48 TB/s memory bandwidth. Such a system achieves 10.4 PetaFLOPS of FP16 and 20.8 PetaFLOPS of FP8 compute performance. The company uses NVIDIA's H200 HGX as reference claims for its performance competitiveness, where the company claims that the Instinct MI325X outperforms NVIDIA H200 HGX system by 1.3x across the board in memory bandwidth, FP16 / FP8 compute performance and 1.8x in memory capacity.

AMD today announced that Oracle Cloud Infrastructure (OCI) has chosen AMD Instinct MI300X accelerators with ROCm open software to power its newest OCI Compute Supercluster instance called BM.GPU.MI300X.8. For AI models that can comprise hundreds of billions of parameters, the OCI Supercluster with AMD MI300X supports up to 16,384 GPUs in a single cluster by harnessing the same ultrafast network fabric technology used by other accelerators on OCI. Designed to run demanding AI workloads including large language model (LLM) inference and training that requires high throughput with leading memory capacity and bandwidth, these OCI bare metal instances have already been adopted by companies including Fireworks AI.

"AMD Instinct MI300X and ROCm open software continue to gain momentum as trusted solutions for powering the most critical OCI AI workloads," said Andrew Dieckmann, corporate vice president and general manager, Data Center GPU Business, AMD. "As these solutions expand further into growing AI-intensive markets, the combination will benefit OCI customers with high performance, efficiency, and greater system design flexibility."

Today, AMD announced "Advancing AI 2024," an in-person and livestreamed event on October 10, 2024 to showcase the next-generation AMD Instinct accelerators and 5th Gen AMD EPYC server processors, as well as Networking and AI PC updates, in addition to highlighting the Company's growing AI solutions ecosystem. AMD executives and AI ecosystems partners, customers and developers will join Chair and CEO Dr. Lisa Su to discuss how AMD products and software are reshaping the AI and high-performance computing landscape. The live stream will start at 9:00 a.m. PT/12:00 p.m. ET on Thursday, October 10

Today, AMD (NASDAQ: AMD) opened a new engineering design center in Serbia, with offices in Belgrade and Nis, strengthening its presence in the Balkans region. The new design center will employ highly skilled software engineers focused on the development of software technologies optimized for AMD leadership compute platforms, including the AMD ROCm software stack for AMD Instinct data center accelerators and AMD Radeon graphics cards. The center was established through an agreement with HTEC, a global technology services company.

"Software plays a critical role in unlocking the capabilities of our leadership AMD hardware. Our new design center will be instrumental in enabling both the design and deployment of future generations of AMD Instinct and Radeon accelerators to help make end-to-end AI solutions more accessible to customers around the world," said Andrej Zdravkovic, senior vice president and chief software officer at AMD. "Our investments in Serbia are a testament to the Balkan region's strong engineering talent, and we are excited to collaborate with HTEC, local universities and the vibrant ecosystem in Belgrade and Nis as we deepen our presence in the region over the coming years."

According to new information from Tom's Hardware, AMD has announced plans to unify its consumer-focused gaming RDNA and data center CDNA graphics architectures into a single, unified design called "UDNA." The announcement was made by AMD's Jack Huynh, Senior Vice President and General Manager of the Computing and Graphics Business Group, at IFA 2024 in Berlin. The goal of the new UDNA architecture is to provide a single focus point for developers so that each optimized application can run on consumer-grade GPU like Radeon RX 7900XTX as well as high-end data center GPU like Instinct MI300. This will create a unification similar to NVIDIA's CUDA, which enables CUDA-focused developers to run applications on everything ranging from laptops to data centers.

Jack HuynhSo, part of a big change at AMD is today we have a CDNA architecture for our Instinct data center GPUs and RDNA for the consumer stuff. It's forked. Going forward, we will call it UDNA. There'll be one unified architecture, both Instinct and client [consumer]. We'll unify it so that it will be so much easier for developers versus today, where they have to choose and value is not improving.

AMD reportedly plans to incorporate glass substrates into its high-performance system-in-packages (SiPs) sometimes between 2025 and 2026. Glass substrates offer several advantages over traditional organic substrates, including superior flatness, thermal properties, and mechanical strength. These characteristics make them well-suited for advanced SiPs containing multiple chiplets, especially in data center applications where performance and durability are critical. The adoption of glass substrates aligns with the industry's broader trend towards more complex chip designs. As leading-edge process technologies become increasingly expensive and yield gains diminish, manufacturers turn to multi-chiplet designs to improve performance. AMD's current EPYC server processors already incorporate up to 13 chiplets, while its Instinct AI accelerators feature 22 pieces of silicon. A more extreme testament is Intel's Ponte Vecchio, which utilized 63 tiles in a single package.

Glass substrates could enable AMD to create even more complex designs without relying on costly interposers, potentially reducing overall production expenses. This technology could further boost the performance of AI and HPC accelerators, which are a growing market and require constant innovation. The glass substrate market is heating up, with major players like Intel, Samsung, and LG Innotek also investing heavily in this technology. Market projections suggest explosive growth, from $23 million in 2024 to $4.2 billion by 2034. Last year, Intel committed to investing up to 1.3 trillion Won (almost one billion USD) to start applying glass substrates to its processors by 2028. Everything suggests that glass substrates are the future of chip design, and we await to see first high-volume production designs.

According to a report by KED Global, Korean chipmaking giant Samsung is ramping up its efforts to compete with global giants like TSMC and Intel. The latest partnership on the horizon is AMD's collaboration with Samsung. AMD is planning to utilize Samsung's cutting-edge 3 nm technology for its future chips. More specifically, AMD wants to utilize Samsung's gate-all-around FETs (GAAFETs). During ITF World 2024, AMD CEO Lisa Su noted that the company intends to use 3 nm GAA transistors for its future products. The only company offering GAAFETs on a 3 nm process is Samsung. Hence, this report from KED gains more credibility.

While we don't have any official information, AMD's utilization of a second foundry as a manufacturing partner would be a first for the company in years. This strategic move signifies a shift towards dual-sourcing, aiming to diversify its supply chain and reduce dependency on a single manufacturer, previously TSMC. We still don't know what specific AMD products will use GAAFETs. AMD could use them for CPUs, GPUs, DPUs, FPGAs, and even data center accelerators like Instinct MI series.

According to ServeTheHome, Intel has decided to discontinue its high-performance computing (HPC) product line, Ponte Vecchio, and shift its focus towards developing its next-generation data center GPU, codenamed Falcon Shores. This decision comes as Intel aims to streamline its operations and concentrate its resources on the most promising and competitive offerings. The Ponte Vecchio GPU, released in January of 2023, was intended to be Intel's flagship product for the HPC market, competing against the likes of NVIDIA's H100 and AMD's Instinct MI series. However, despite its impressive specifications and features, Ponte Vecchio faced significant delays and challenges in its development and production cycle. Intel's decision to abandon Ponte Vecchio is pragmatic, recognizing the intense competition and rapidly evolving landscape of the data center GPU market.

By pivoting its attention to Falcon Shores, Intel aims to deliver a more competitive and cutting-edge solution that can effectively challenge the dominance of its rivals. Falcon Shores, slated for release in 2025, is expected to leverage Intel's latest process node and architectural innovations. Currently, Intel has Gaudi 2 and Gaudi 3 accelerators for AI. However, the HPC segment is left without a clear leader in the company's product offerings. Intel's Ponte Vecchio is powering Aurora exascale supercomputer, which is the latest submission to the TOP500 supercomputer lists. This is also coming after the Rialto Bridge cancellation, which was supposed to be an HPC-focused card. In the future, the company will focus only on the Falcon Shores accelerator, which will unify HPC and AI needs for high-precision FP64 and lower-precision FP16/INT8.

AMD's Instinct family has welcomed a new addition—the MI388X AI accelerator—as discovered in a lengthy regulatory 10K filing (submitted to the SEC). The document reveals that the unannounced SKU—along with the MI250, MI300X and MI300A integrated circuits—cannot be sold to Chinese customers due to updated US trade regulations (new requirements were issued around October 2023). Versal VC2802 and VE2802 FPGA products are also mentioned in the same section. Earlier this month, AMD's Chinese market-specific Instinct MI309 package was deemed to be too powerful for purpose by the US Department of Commerce.

AMD has not published anything about the Instinct MI388X's official specification, and technical details have not emerged via leaks. The "X" tag likely implies that it has been designed for AI and HPC applications, akin to the recently launched MI300X accelerator. The designation of a higher model number could (naturally) point to a potentially more potent spec sheet, although Tom's Hardware posits that MI388X is a semi-custom spinoff of an existing model.

According to the latest report from Bloomberg, AMD has hit a roadblock in offering its top-of-the-line AI accelerator in the Chinese market. The newest AI chip is called Instinct MI309, a lower-performance Instinct MI300 variant tailored to meet the latest US export rules for selling advanced chips to China-based entities. However, the Instinct MI309 still appears too powerful to gain unconditional approval from the US Department of Commerce, leaving AMD in need of an export license. Originally, the US Department of Commerce made a rule: Total Processing Performance (TPP) score should not exceed 4800, effectively capping AI performance at 600 FP8 TFLOPS. This rule ensures that processors with slightly lower performance may still be sold to Chinese customers, provided their performance density (PD) is sufficiently low.

However, AMD's latest creation, Instinct MI309, is everything but slow. Based on the powerful Instinct MI300, AMD has not managed to bring it down to acceptable levels to acquire a US export license from the Department of Commerce. It is still unknown which Chinese customer was trying to acquire AMD's Instinct MI309; however, it could be one of the Chinese AI labs trying to get ahold of more training hardware for their domestic models. NVIDIA has employed a similar tactic, selling A800 and H800 chips to China, until the US also ended the export of these chips to China. AI labs located in China can only use domestic hardware, including accelerators from Alibaba, Huawei, and Baidu. Cloud services hosting GPUs in US can still be accessed by Chinese companies, but that is currently under US regulators watchlist.

AMD announced that Thomas Zacharia has joined AMD as senior vice president of strategic technology partnerships and public policy. Zacharia will lead the global expansion of AMD public/private relationships with governments, non-governmental organizations (NGOs) and other organizations to help fast-track the deployment of customized AMD-powered AI solutions to meet rapidly growing number of global projects and applications targeting the deployment of AI for the public good.

"Thomas is a distinguished leader with decades of experience successfully creating public/private partnerships that have resulted in consistently deploying the world's most powerful and advanced computing solutions, including the world's fastest supercomputer Frontier," said AMD Chair and CEO Lisa Su. "As the former Director of the U.S.'s largest multi-program science and energy research lab, Thomas is uniquely positioned to leverage his extensive experience advancing the frontiers of science and technology to help countries around the world deploy AMD-powered AI solutions for the public good."

LaminiAI appears to be one of AMD's first customers to receive a bulk order of Instinct MI300X GPUs—late last week, Sharon Zhou (CEO and co-founder) posted about the "next batch of LaminiAI LLM Pods" up and running with Team Red's cutting-edge CDNA 3 series accelerators inside. Her short post on social media stated: "rocm-smi...like freshly baked bread, 8x MI300X is online—if you're building on open LLMs and you're blocked on compute, lmk. Everyone should have access to this wizard technology called LLMs."

An attached screenshot of a ROCm System Management Interface (ROCm SMI) session showcases an individual Pod configuration sporting eight Instinct MI300X GPUs. According to official blog entries, LaminiAI has utilized bog-standard MI300 accelerators since 2023, so it is not surprising to see their partnership continue to grow with AMD. Industry predictions have the Instinct MI300X and MI300A models placed as great alternatives to NVIDIA's dominant H100 "Hopper" series—AMD stock is climbing due to encouraging financial analyst estimations.

AMD today announced the new Ryzen 8040 mobile processor series codenamed "Hawk Point." These chips are shipping to notebook manufacturers now, and the first notebooks powered by these should be available to consumers in Q1-2024. At the heart of this processor is a significantly faster neural processing unit (NPU), designed to accelerate AI applications that will become relevant next year, as Microsoft prepares to launch Windows 12, and software vendors make greater use of generative AI in consumer applications.

The Ryzen 8040 "Hawk Point" processor is almost identical in design and features to the Ryzen 7040 "Phoenix," except for a faster Ryzen AI NPU. While this is based on the same first-generation XDNA architecture, its NPU performance has been increased to 16 TOPS, compared to 10 TOPS of the NPU on the "Phoenix" silicon. AMD is taking a whole-of-silicon approach to AI acceleration, which includes not just the NPU, but also the "Zen 4" CPU cores that support the AVX-512 VNNI instruction set that's relevant to AI; and the iGPU based on the RDNA 3 graphics architecture, with each of its compute unit featuring two AI accelerators, components that make the SIMD cores crunch matrix math. The whole-of-silicon performance figures for "Phoenix" is 33 TOPS; while "Hawk Point" boasts of 39 TOPS. In benchmarks by AMD, "Hawk Point" is shown delivering a 40% improvement in vision models, and Llama 2, over the Ryzen 7040 "Phoenix" series.

GIGABYTE Technology: Giga Computing, a subsidiary of GIGABYTE and an industry leader in high-performance servers, and IT infrastructure, today announced the GIGABYTE G383-R80 for the AMD Instinct MI300A APU and two GIGABYTE G593 series servers for the AMD Instinct MI300X GPU and AMD EPYC 9004 Series processor. As a testament to the performance of AMD Instinct MI300 Series family of products, the El Capitan supercomputer at Lawrence Livermore National Laboratory uses the MI300A APU to power exascale computing. And these new GIGABYTE servers are the ideal platform to propel discoveries in HPC & AI at exascale.⁠

Marrying of a CPU & GPU: G383-R80
For incredible advancements in HPC there is the GIGABYTE G383-R80 that houses four LGA6096 sockets for MI300A APUs. This chip integrates a CPU that has twenty-four AMD Zen 4 cores with a powerful GPU built with AMD CDNA 3 GPU cores. And the chiplet design shares 128 GB of unified HBM3 memory for impressive performance for large AI models. The G383 server has lots of expansion slots for networking, storage, or other accelerators, with a total of twelve PCIe Gen 5 slots. And in the front of the chassis are eight 2.5" Gen 5 NVMe bays to handle heavy workloads such as real-time big data analytics and latency-sensitive workloads in finance and telecom. ⁠

AMD's lineup of Radeon and Instinct GPUs, including the flagship RX 7900 XTX/XT, the professional-grade PRO W7900, and the upcoming Instinct MI300, are facing sales prohibitions in China, according to an alleged sales advisory guide from Dell. This restriction mirrors the earlier ban on NVIDIA's RTX 4090, underscoring the increasing export limitations U.S.-based companies face for high-end semiconductor products that could be repurposed for military and strategic applications. Notably, Dell's report lists several AMD Instinct accelerators, which are integral to data center infrastructure, and Radeon GPUs, which are widely used in PCs, indicating the broad impact of the advisory.

The ban includes discrete GPUs like AMD's Radeon RX 7900 XTX and 7900 XT, which, despite their data-center potential, may still be sold under specific "NEC" eligibility. This status allows for continued sales in restricted regions like sales of NVIDIA's RTX 4090. However, the process to secure NEC eligibility is lengthy, potentially leading to supply shortages and increased GPU prices—a trend already observed with the RX 7900 XTX in China, where it's become a high-end alternative in light of the RTX 4090's scarcity and inflated pricing. The Dell sales advisory also lists that sales of the aforementioned products are banned in 22 countries, including Russia, Iran, Iraq, and others listed below.

Today at Microsoft Ignite, AMD and Microsoft featured how AMD products, including the upcoming AMD Instinct MI300X accelerator, AMD EPYC CPUs and AMD Ryzen CPUs with AI engines, are enabling new services and compute capabilities across cloud and generative AI, Confidential Computing, Cloud Computing and smarter, more intelligent PCs.

"AMD is fostering AI everywhere - from the cloud, to the enterprise and end point devices - all powered by our CPUs, GPUs, accelerators and AI engines," said Vamsi Boppana, Senior Vice President, AI, AMD. "Together with Microsoft and a rapidly growing ecosystem of software and hardware partners, AMD is accelerating innovation to bring the benefits of AI to a broad portfolio of compute engines, with expanding software capabilities."

AMD today announced the signing of a definitive agreement to acquire Nod.ai to expand the company's open AI software capabilities. The addition of Nod.ai will bring an experienced team that has developed an industry-leading software technology that accelerates the deployment of AI solutions optimized for AMD Instinct data center accelerators, Ryzen AI processors, EPYC processors, Versal SoCs and Radeon GPUs to AMD. The agreement strongly aligns with the AMD AI growth strategy centered on an open software ecosystem that lowers the barriers of entry for customers through developer tools, libraries and models.

"The acquisition of Nod.ai is expected to significantly enhance our ability to provide AI customers with open software that allows them to easily deploy highly performant AI models tuned for AMD hardware," said Vamsi Boppana, senior vice president, Artificial Intelligence Group at AMD. "The addition of the talented Nod.ai team accelerates our ability to advance open-source compiler technology and enable portable, high-performance AI solutions across the AMD product portfolio. Nod.ai's technologies are already widely deployed in the cloud, at the edge and across a broad range of end point devices today."

Today, AMD released the findings from a new survey of global IT leaders which found that 3 in 4 IT leaders are optimistic about the potential benefits of AI—from increased employee efficiency to automated cybersecurity solutions—and more than 2 in 3 are increasing investments in AI technologies. However, while AI presents clear opportunities for organizations to become more productive, efficient, and secure, IT leaders expressed uncertainty on their AI adoption timeliness due to their lack of implementation roadmaps and the overall readiness of their existing hardware and technology stack.

AMD commissioned the survey of 2,500 IT leaders across the United States, United Kingdom, Germany, France, and Japan to understand how AI technologies are re-shaping the workplace, how IT leaders are planning their AI technology and related Client hardware roadmaps, and what their biggest challenges are for adoption. Despite some hesitations around security and a perception that training the workforce would be burdensome, it became clear that organizations that have already implemented AI solutions are seeing a positive impact and organizations that delay risk being left behind. Of the organizations prioritizing AI deployments, 90% report already seeing increased workplace efficiency.