While everyone has been focused on shipping an AI-enhanced product recently, one tech giant didn't appear to be bothered- Apple. However, according to Mark Gurman from Bloomberg, Apple is readying an overhaul of its Apple Silicon M-series chips to embed AI processing capabilities at the processor level. As the report indicates, Apple is preparing an update for late 2024 and early 2025 with the M4 series of chips, which will reportedly feature AI processing units similar to those found in other commercial chips. There should be three levels of the M4 series, with the entry-level M4 codenamed Donan, the mid-level M4 chip codenamed Brava, and the high-end M4 chip codenamed Hydra.

Sales of Apple Macs peaked in 2022; the following year was a sharp decline, and sales have continued to be flat since. The new AI PCs for Windows-based systems have been generating hype from all major vendors, hoping to introduce AI features to end users. However, Apple wants to be part of the revolution, and the company has already scheduled the World Wide Developer Conference for June 10th. At WWDC this year, Apple is supposed to show a suite of AI-powered solutions to enable better user experience and increase productivity. With M4 chips getting AI enhancement, the WWDC announcements will get extra hardware accelerations. However, we must wait for the exact announcements before making further assumptions.

Meta has announced the next generation of its Meta Training and Inference Accelerator (MTIA) chip, which is designed to train and infer AI models at scale. The newest MTIA chip is a second-generation design of Meta's custom silicon for AI, and it is being built on TSMC's 5 nm technology. Running at the frequency of 1.35 GHz, the new chip is getting a boost to 90 Watts of TDP per package compared to just 25 Watts for the first-generation design. Basic Linear Algebra Subprograms (BLAS) processing is where the chip shines, and it includes matrix multiplication and vector/SIMD processing. At GEMM matrix processing, each chip can process 708 TeraFLOPS at INT8 (presumably meant FP8 in the spec) with sparsity, 354 TeraFLOPS without, 354 TeraFLOPS at FP16/BF16 with sparsity, and 177 TeraFLOPS without.

Classical vector and processing is a bit slower at 11.06 TeraFLOPS at INT8 (FP8), 5.53 TeraFLOPS at FP16/BF16, and 2.76 TFLOPS single-precision FP32. The MTIA chip is specifically designed to run AI training and inference on Meta's PyTorch AI framework, with an open-source Triton backend that produces compiler code for optimal performance. Meta uses this for all its Llama models, and with Llama3 just around the corner, it could be trained on these chips. To package it into a system, Meta puts two of these chips onto a board and pairs them with 128 GB of LPDDR5 memory. The board is connected via PCIe Gen 5 to a system where 12 boards are stacked densely. This process is repeated six times in a single rack for 72 boards and 144 chips in a single rack for a total of 101.95 PetaFLOPS, assuming linear scaling at INT8 (FP8) precision. Of course, linear scaling is not quite possible in scale-out systems, which could bring it down to under 100 PetaFLOPS per rack.Below, you can see images of the chip floorplan, specifications compared to the prior version, as well as the system.

ASUS IoT, the global AIoT solution provider, today announced PE8000G at Embedded World 2024, a powerful edge AI computer that supports multiple GPU cards for high performance—and is expertly engineered to handle rugged conditions with resistance to extreme temperatures, vibration and variable voltage. PE8000G is powered by formidable Intel Core processors (13th and 12th gen) and the Intel R680E chipset to deliver high-octane processing power and efficiency.

With its advanced architecture, PE8000G excels at running multiple neural network modules simultaneously in real-time—and represents a significant leap forward in edge AI computing. With its robust design, exceptional performance and wide range of features, PE8000G series is poised to revolutionize AI-driven applications across multiple industries, elevating edge AI computing to new heights and enabling organizations to tackle mission-critical tasks with confidence and to achieve unprecedented levels of productivity and innovation.

After two years of decline, the worldwide traditional PC market returned to growth during the first quarter of 2024 (1Q24) with 59.8 million shipments, growing 1.5% year over year, according to preliminary results from the International Data Corporation (IDC) Worldwide Quarterly Personal Computing Device Tracker. Growth was largely achieved due to easy year-over-year comparisons as the market declined 28.7% during the first quarter of 2023, which was the lowest point in PC history. In addition, global PC shipments finally returned to pre-pandemic levels as 1Q24 volumes rivaled those seen in 1Q19 when 60.5 million units were shipped.

With inflation numbers trending down, PC shipments have begun to recover in most regions, leading to growth in the Americas as well as Europe, the Middle East, and Africa (EMEA). However, the deflationary pressures in China directly impacted the global PC market. As the largest consumer of desktop PCs, weak demand in China led to yet another quarter of declines for global desktop shipments, which already faced pressure from notebooks as the preferred form factor.

Google has officially joined the club of custom Arm-based, in-house-developed CPUs. As of today, Google's in-house semiconductor development team has launched the "Axion" CPU based on Arm instruction set architecture. Using the Arm Neoverse V2 cores, Google claims that the Axion CPU outperforms general-purpose Arm chips by 30% and Intel's processors by a staggering 50% in terms of performance. This custom silicon will fuel various Google Cloud offerings, including Compute Engine, Kubernetes Engine, Dataproc, Dataflow, and Cloud Batch. The Axion CPU, designed from the ground up, will initially support Google's AI-driven services like YouTube ads and Google Earth Engine. According to Mark Lohmeyer, Google Cloud's VP and GM of compute and machine learning infrastructure, Axion will soon be available to cloud customers, enabling them to leverage its performance without overhauling their existing applications.

Google's foray into custom silicon aligns with the strategies of its cloud rivals, Microsoft and Amazon. Microsoft recently unveiled its own AI chip for training large language models and an Arm-based CPU called Cobalt 100 for cloud and AI workloads. Amazon, on the other hand, has been offering Arm-based servers through its custom Graviton CPUs for several years. While Google won't sell these chips directly to customers, it plans to make them available through its cloud services, enabling businesses to rent and leverage their capabilities. As Amin Vahdat, the executive overseeing Google's in-house chip operations, stated, "Becoming a great hardware company is very different from becoming a great cloud company or a great organizer of the world's information."

Micron Technology, Inc., today announced it is sampling the automotive-grade Micron 4150AT SSD, the world's first quad-port SSD, capable of interfacing with up to four systems on chips (SoCs) to centralize storage for software-defined intelligent vehicles. The Micron 4150AT SSD combines market-leading features such as single-root input/output virtualization (SR-IOV), a PCIe Generation 4 interface and ruggedized automotive design. With these features, the automotive-grade SSD provides the ecosystem with data center-level flexibility and power.

"As storage requirements race to keep up with rich in-vehicle experiences featuring AI and advanced algorithms for higher levels of autonomous safety, this era demands a new paradigm for automotive storage to match," said Michael Basca, Micron vice president of embedded products and systems. "Building on our collaboration with the innovators redefining next-generation automotive architectures, Micron has reimagined storage from the ground up to deliver the world's first quad-port SSD - the Micron 4150AT - which provides the industry flexibility and horsepower to roll out the transformative technologies on the horizon."

During the Vision 2024 event, Intel announced its latest Gaudi 3 AI accelerator, promising significant improvements over its predecessor. Intel claims the Gaudi 3 offers up to 70% improvement in training performance, 50% better inference, and 40% better efficiency than Nvidia's H100 processors. The new AI accelerator is presented as a PCIe Gen 5 dual-slot add-in card with a 600 W TDP or an OAM module with 900 W. The PCIe card has the same peak 1,835 TeraFLOPS of FP8 performance as the OAM module despite a 300 W lower TDP. The PCIe version works as a group of four per system, while the OAM HL-325L modules can be run in an eight-accelerator configuration per server. This likely will result in a lower sustained performance, given the lower TDP, but it confirms that the same silicon is used, just finetuned with a lower frequency. Built on TSMC's N5 5 nm node, the AI accelerator features 64 Tensor Cores, delivering double the FP8 and quadruple FP16 performance over the previous generation Gaudi 2.

The Gaudi 3 AI chip comes with 128 GB of HBM2E with 3.7 TB/s of bandwidth and 24 200 Gbps Ethernet NICs, with dual 400 Gbps NICs used for scale-out. All of that is laid out on 10 tiles that make up the Gaudi 3 accelerator, which you can see pictured below. There is 96 MB of SRAM split between two compute tiles, which acts as a low-level cache that bridges data communication between Tensor Cores and HBM memory. Intel also announced support for the new performance-boosting standardized MXFP4 data format and is developing an AI NIC ASIC for Ultra Ethernet Consortium-compliant networking. The Gaudi 3 supports clusters of up to 8192 cards, coming from 1024 nodes comprised of systems with eight accelerators. It is on track for volume production in Q3, offering a cost-effective alternative to NVIDIA accelerators with the additional promise of a more open ecosystem. More information and a deeper dive can be found in the Gaudi 3 Whitepaper.

At the Intel Vision 2024 customer and partner conference, Intel introduced the Intel Gaudi 3 accelerator to bring performance, openness and choice to enterprise generative AI (GenAI), and unveiled a suite of new open scalable systems, next-gen products and strategic collaborations to accelerate GenAI adoption. With only 10% of enterprises successfully moving GenAI projects into production last year, Intel's latest offerings address the challenges businesses face in scaling AI initiatives.

"Innovation is advancing at an unprecedented pace, all enabled by silicon - and every company is quickly becoming an AI company," said Intel CEO Pat Gelsinger. "Intel is bringing AI everywhere across the enterprise, from the PC to the data center to the edge. Our latest Gaudi, Xeon and Core Ultra platforms are delivering a cohesive set of flexible solutions tailored to meet the changing needs of our customers and partners and capitalize on the immense opportunities ahead."

Acer unveiled the latest addition to its gaming line with the new Predator Helios Neo 14, a portable powerhouse equipped with the latest Intel Core Ultra processors, unlocking AI experiences on the PC. In addition, the Acer Nitro 16 gaming laptop has been refreshed with Intel Core 14th gen processors, allowing users to do more when gaming or creating. Players of all levels will be amazed by the pristine visuals and AI-driven graphics shown when gaming or streaming thanks to the devices' NVIDIA GeForce RTX 40[1] Series Laptop GPUs, which support the latest AI-powered DLSS 3.5 technology and other AI accelerations across creative applications. Brilliant colors and pixels stand out on the laptops' WQXGA display options, combined with 100% support for sRGB color gamut and NVIDIA G-SYNC compatibility.

To further complement creativity and capabilities on the gaming laptops, these feature Microsoft Copilot in Windows (with a dedicated Copilot key), providing faster access to the everyday AI assistant and Acer's suite of AI-enhanced videoconferencing features. With one month of Xbox Game Pass Ultimate included in every device, players can enjoy hundreds of high-quality PC games. Plus, dual fans, exhaust cooling systems, and liquid metal thermal on the CPUs ensure the gaming laptops' interiors run on full speed even in the most heated gaming sessions.

Acer today announced the new Nitro 14 and Nitro 16 gaming laptops, powered by AMD Ryzen 8040 Series processors with Ryzen AI[1]. With up to NVIDIA GeForce RTX 4060[2] Laptop GPUs supported by DLSS 3.5 technology, both are backed by NVIDIA's RTX AI platform, providing an array of capabilities in over 500 games and applications, enhanced by AI. Gamers are immersed in their 14- and 16-inch NVIDIA G-SYNC compatible panels with up to WQXGA (2560x1600) resolution.

Whether in call or streaming in-game, Acer PurifiedVoice 2.0 harnesses the power of AI to block out external noises, while Acer PurifiedView keeps users always front and center of all the action. Microsoft Copilot in Windows (with a dedicated Copilot key) helps accelerate everyday tasks on these AI laptops, and with one month of Xbox Game Pass Ultimate included with every device, players will enjoy hundreds of high-quality PC games. To seamlessly take command of device performance and customizations, one click of the NitroSense key directs users to the control center and the library of available AI-related functions through the new Experience Zone.

AMD today announced the expansion of the AMD Versal adaptive system on chip (SoC) portfolio with the new Versal AI Edge Series Gen 2 and Versal Prime Series Gen 2 adaptive SoCs, which bring preprocessing, AI inference, and postprocessing together in a single device for end-to-end acceleration of AI-driven embedded systems.

These initial devices in the Versal Series Gen 2 portfolio build on the first generation with powerful new AI Engines expected to deliver up to 3x higher TOPs-per-watt than first generation Versal AI Edge Series devicesi, while new high-performance integrated Arm CPUs are expected to offer up to 10x more scalar compute than first gen Versal AI Edge and Prime series devicesii.

Advantech (2395.TW), a global leader in intelligent IoT systems and embedded platforms, is excited to announce the EAI-3101, a brand-new industrial PCIe GPU card powered by the Intel Arc A380E, built for 5-year longevity. Featuring 128 Intel Xe matrix AI engines, this GPU card delivers outstanding AI computing power of 5.018 TFLOPS, surpassing the capabilities of the NVIDIA T1000, 2 times over. With ray tracing technology and Intel XeSS AI-upscaling, the EAI-3101 supports up to 8K UHD resolution and achieves a 50% enhancement in graphics performance over the NVIDIA T1000.

To aid in quickly realizing Vision AI, Advantech provides the Edge AI SDK, a rapid AI development toolkit compatible with Intel OpenVINO, which can process the same workload in 40% less time. This groundbreaking graphics solution, with optimized thermal design and an auto smart fan, is specially engineered for image processing and AI acceleration across gaming, medical analysis, and video surveillance. Advantech will demonstrate the EAI-3101 GPU card from April 9th to 11th at the Embedded World 2024 (Hall 3, booth no. 339) in Nuremberg, Germany.

All-in-one computers are often traditionally seen as lower-powered alternatives to traditional desktop workstations. However, a new offering from Alafia AI, a startup focused on medical imaging appliances, aims to shatter that perception. The company's upcoming Alafia Aivas SuperWorkstation packs serious hardware muscle, demonstrating that all-in-one systems can match the performance of their more modular counterparts. At the heart of the Aivas SuperWorkstation lies a 128-core Ampere Altra processor, running at 3.0 GHz clock speed. This CPU is complemented by not one but three NVIDIA L4 GPUs for compute, and a single NVIDIA RTX 4000 Ada GPU for video output, delivering a combined 28,416 CUDA cores for accelerated parallel computing tasks. The system doesn't skimp on other components, either. It features a 4K touch display with up to 360 nits of brightness, an extensive 2 TB of DDR4 RAM, and storage options up to an 8 TB solid-state drive. This combination of cutting-edge CPU, GPU, memory, and storage is squarely aimed at the demands of medical imaging and AI development workloads.

The all-in-one form factor packs this incredible hardware into a sleek, purposefully designed clinical research appliance. While initially targeting software developers, Alafia AI hopes that institutions that can optimize their applications for the Arm architecture can eventually deploy the Aivas SuperWorkstation for production medical imaging workloads. The company is aiming for application integration in Q3 2024 and full ecosystem device integration by Q4 2024. With this powerful new offering, Alafia AI is challenging long-held assumptions about the performance limitations of all-in-one systems. The Aivas SuperWorkstation demonstrates that the right hardware choices can transform these compact form factors into true powerhouse workstations. Especially with a combined total output of three NVIDIA L4 compute units, alongside RTX 4000 Ada graphics card, the AIO is more powerful than some of the high-end desktop workstations.

While we are all used to having a system with a CPU, GPU, and, recently, NPU—X-Silicon Inc. (XSi), a startup founded by former Silicon Valley veterans—has unveiled an interesting RISC-V processor that can simultaneously handle CPU, GPU, and NPU workloads in a chip. This innovative chip architecture, which will be open-source, aims to provide a flexible and efficient solution for a wide range of applications, including artificial intelligence, virtual reality, automotive systems, and IoT devices. The new microprocessor combines a RISC-V CPU core with vector capabilities and GPU acceleration into a single chip, creating a versatile all-in-one processor. By integrating the functionality of a CPU and GPU into a single core, X-Silicon's design offers several advantages over traditional architectures. The chip utilizes the open-source RISC-V instruction set architecture (ISA) for both CPU and GPU operations, running a single instruction stream. This approach promises lower memory footprint execution and improved efficiency, as there is no need to copy data between separate CPU and GPU memory spaces.

Called the C-GPU architecture, X-Silicon uses RISC-V Vector Core, which has 16 32-bit FPUs and a Scaler ALU for processing regular integers as well as floating point instructions. A unified instruction decoder feeds the cores, which are connected to a thread scheduler, texture unit, rasterizer, clipping engine, neural engine, and pixel processors. All is fed into a frame buffer, which feeds the video engine for video output. The setup of the cores allows the users to program each core individually for HPC, AI, video, or graphics workloads. Without software, there is no usable chip, which prompts X-Silicon to work on OpenGL ES, Vulkan, Mesa, and OpenCL APIs. Additionally, the company plans to release a hardware abstraction layer (HAL) for direct chip programming. According to Jon Peddie Research (JPR), the industry has been seeking an open-standard GPU that is flexible and scalable enough to support various markets. X-Silicon's CPU/GPU hybrid chip aims to address this need by providing manufacturers with a single, open-chip design that can handle any desired workload. The XSi gave no timeline, but it has plans to distribute the IP to OEMs and hyperscalers, so the first silicon is still away.

AMD "Zen 5" CPU microarchitecture will introduce a significant performance increase for AVX-512 workloads, with some sources reported as high as 40% performance increases over "Zen 4" in benchmarks that use AVX-512. A Moore's Law is Dead report detailing the execution engine of "Zen 5" holds the answer to how the company managed this—using a true 512-bit FPU. Currently, AMD uses a dual-pumped 256-bit FPU to execute AVX-512 workloads on "Zen 4." The updated FPU should significantly improve the core's performance in workloads that take advantage of 512-bit AVX or VNNI instructions, such as AI.

Giving "Zen 5" a 512-bit FPU meant that AMD also had to scale up the ancillaries—all the components that keep the FPU fed with data and instructions. The company therefore increased the capacity of the L1 DTLB. The load-store queues have been widened to meet the needs of the new FPU. The L1 Data cache has been doubled in bandwidth, and increased in size by 50%. The L1D is now 48 KB in size, up from 32 KB in "Zen 4." FPU MADD latency has been reduced by 1 cycle. Besides the FPU, AMD also increased the number of Integer execution pipes to 10, from 8 on "Zen 4." The exclusive L2 cache per core remains 1 MB in size.Update 07:02 UTC: Moore's Law is Dead reached out to us and said that the slide previously posted by them, which we had used in an earlier version of this article, is fake, but said that the information contained in that slide is correct, and that they stand by the information.

SK hynix Inc., the world's leading producer of High-Bandwidth Memory (HBM) chips, announced today that it will invest an estimated $3.87 billion in West Lafayette, Indiana to build an advanced packaging fabrication and R&D facility for AI products. The project, the first of its kind in the United States, is expected to drive innovation in the nation's AI supply chain, while bringing more than a thousand new jobs to the region.

The company held an investment agreement ceremony with officials from Indiana State, Purdue University, and the U.S. government at Purdue University in West Lafayette on the 3rd and officially announced the plan. At the event, officials from each party including Governor of Indiana Eric Holcomb, Senator Todd Young, Director of the White House Office of Science and Technology Policy Arati Prabhakar, Assistant Secretary of Commerce Arun Venkataraman, Secretary of Commerce State of Indiana David Rosenberg, Purdue University President Mung Chiang, Chairman of Purdue Research Foundation Mitch Daniels, Mayor of city of West Lafayette Erin Easter, Ambassador of the Republic of Korea to the United States Hyundong Cho, Consul General of the Republic of Korea in Chicago Junghan Kim, SK vice chairman Jeong Joon Yu, SK hynix CEO Kwak Noh-Jung and SK hynix Head of Package & Test Choi Woojin, participated.

According to the latest report from The Verge, Microsoft is currently testing a new AI-driven chatbot designed to automate support tasks for its Xbox gaming platform. As the report notes, Microsoft is experimenting with an animated AI character that will assist in answering Xbox support inquiries. The Xbox AI chatbot is connected to Microsoft's Xbox network and ecosystem support documentation. It can answer questions and process game refunds from the Microsoft support website, all aiming to provide users with simple and quick assistance on support topics using natural language, drawing information from existing Xbox support pages. Training on Microsoft's enterprise data will help Microsoft reduce the AI model's hallucinations and instruct it to do only as intended.

As a result, the chatbot's responses closely resemble the information Microsoft provides to its customers to automate support tasks. Recently, Microsoft has expanded the test pool for its new Xbox chatbot, suggesting that the "Xbox Support Virtual Agent" may soon handle support inquiries for all Xbox customers. The development of the Xbox chatbot prototype is part of a broader initiative within Microsoft Gaming to introduce AI-powered features and tools for the Xbox platform and developer tools. The company is also reportedly working on providing AI capabilities for game content creation, gameplay, and the Xbox platform and devices. However, Xbox employees have yet to publicly confirm these more extensive AI efforts for Microsoft Gaming, likely due to the company's cautious approach to presenting AI in gaming. Nevertheless, AI will soon become an integral part of gaming consoles.

Intel Corporation today outlined a new financial reporting structure that is aligned with the company's previously announced foundry operating model for 2024 and beyond. This new structure is designed to drive increased cost discipline and higher returns by providing greater transparency, accountability and incentives across the business. To support the new structure, Intel provided recast operating segment financial results for the years 2023, 2022 and 2021. The company also shared a targeted path toward long-term growth and profitability of Intel Foundry, as well as clear goals for driving financial performance improvement and shareholder value creation.

"Intel's differentiated position as both a world-class semiconductor manufacturer and a fabless technology leader creates significant opportunities to drive long-term sustainable growth across these two complementary businesses," said Pat Gelsinger, Intel CEO. "Implementing this new model marks a key achievement in our IDM 2.0 transformation as we hone our execution engine, stand up the industry's first and only systems foundry with geographically diverse leading-edge manufacturing capacity, and advance our mission to bring AI Everywhere."

AMD has introduced the Ryzen Embedded 8000 Series processors, the first AMD embedded devices to combine NPUs based on the AMD XDNA architecture with traditional CPU and GPU elements, optimized for workload versatility and adaptability targeting industrial AI applications. Embedded solution engineers and developers can harness the processing power and leadership features for a variety of industrial AI applications including machine vision, robotics, and industrial automation. AI is widely used in machine vision applications today to enhance quality control and inspection processes.

AI can also help robots make real-time, route-planning decisions and adapt to dynamic environments. In industrial automation, AI processing helps intelligent edge devices perform complex analysis and decision-making without relying on cloud connectivity. This allows for real-time monitoring, predictive maintenance, and autonomous control of industrial processes, enhancing operational efficiency and reducing downtime.

The expansion of AI technology affects not only the production and demand for graphics cards but also the electricity grid that powers them. Data centers hosting thousands of GPUs are becoming more common, and the industry has been building new facilities for GPU-enhanced servers to serve the need for more AI. However, these powerful GPUs often consume over 500 Watts per single card, and NVIDIA's latest Blackwell B200 GPU has a TGP of 1000 Watts or a single kilowatt. These kilowatt GPUs will be present in data centers with 10s of thousands of cards, resulting in multi-megawatt facilities. To combat the load on the national electricity grid, US President Joe Biden's administration has been discussing with big tech to re-evaluate their power sources, possibly using smaller nuclear plants. According to an Axios interview with Energy Secretary Jennifer Granholm, she has noted that "AI itself isn't a problem because AI could help to solve the problem." However, the problem is the load-bearing of the national electricity grid, which can't sustain the rapid expansion of the AI data centers.

The Department of Energy (DOE) has been reportedly talking with firms, most notably hyperscalers like Microsoft, Google, and Amazon, to start considering nuclear fusion and fission power plants to satisfy the need for AI expansion. We have already discussed the plan by Microsoft to embed a nuclear reactor near its data center facility and help manage the load of thousands of GPUs running AI training/inference. However, this time, it is not just Microsoft. Other tech giants are reportedly thinking about nuclear as well. They all need to offload their AI expansion from the US national power grid and develop a nuclear solution. Nuclear power is a mere 20% of the US power sourcing, and DOE is currently financing a Holtec Palisades 800-MW electric nuclear generating station with $1.52 billion in funds for restoration and resumption of service. Microsoft is investing in a Small Modular Reactors (SMRs) microreactor energy strategy, which could be an example for other big tech companies to follow.

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.

Arm China is making strides in the AI accelerator market with its new neural processing unit (NPU) called Zhouyi. The company aims to integrate the NPU into low-cost domestic CPUs, potentially giving it an edge over competitors like AMD and Intel. Initially a part of Arm Holdings, which licensed IP in China, Arm China took on a new strategy of developing its own IP specifically for Chinese customers a few years ago. While the company does not develop high-performance general-purpose cores, its Zhouyi NPU could become a fundamental building block for affordable processors. A significant step forward is the upcoming addition of an open-source driver for Zhouyi to the Linux kernel. This will make the IP easy to program for software developers, increasing its appeal to chip designers.

Being an open-source driver, the integration in the Linux kernel brings assurance to developers that Zhouyi NPU could be the first in many generations from Arm China. While Zhouyi may not directly compete with offerings from AMD or Intel, its potential for widespread adoption in millions of devices could help Arm China acquire local customers with their IP. The project, which began three years ago with a kernel-only driver, has since evolved into a full driver stack. There is even a development kit board called EAIDK310, powered by Rockwell SoC and Zhouyi NPU, which is available on Aliexpress and Amazon. The integration of AI accelerator technology into the Linux ecosystem is a significant development, though there is still work to be done. Nonetheless, Arm China's Zhouyi NPU and open-source driver are essential to making AI capabilities more accessible and widely available in the domestic Chinese market.

Leading global motherboard manufacturer, ASRock, has successively released software based on Microsoft Windows 10/11 and Canonical Ubuntu Linux platforms since the end of last year, which can help users quickly download, install and configure artificial intelligence software. After receiving great response from the market, ASRock has revealed the 2024 Q1 update of AI QuickSet today, adding two new artificial intelligence (AI) tools, Whisper Desktop and AudioCraft, allowing users of ASRock AMD Radeon RX 7000 series graphics cards to experience more diverse artificial intelligence (AI) applications!

ASRock AI QuickSet software tool 1.2.4 Windows version supports Microsoft Windows 10/11 64-bit operating system, while Linux version 1.1.6 supports Canonical Ubuntu 22.04.4 Desktop (64-bit) operating system, through ASRock AMD Radeon RX 7000 series graphics cards and AMD ROCm software platform provide powerful computing capabilities to support a variety of well-known artificial intelligence (AI) applications. The 1.2.4 Windows version supports image generation tools such as DirectML Shark and Stable Diffusion web UI, as well as the newly added Whisper Desktop speech recognition tool; and the 1.1.6 Linux version supports Image/Manga Translator, Stable Diffusion CLI & web UI image generation tool, and Text generation web UI Llama 2 text generation tool using Meta Llama 2 language model, Ultralytics YOLOv8 object recognition tool, and the newly added AudioCraft audio generation tool.

Ryan McCurdy, President of Lenovo North America, revealed ambitious forward-thinking product roadmap during an interview with CRN magazine. A hybrid strategic approach will create an anticipated AI fast lane on future hardware—McCurdy, a former Intel veteran, stated: "there will be a steady stream of product development to add (AI PC) hardware capabilities in a chicken-and-egg scenario for the OS and for the (independent software vendor) community to develop their latest AI capabilities on top of that hardware...So we are really paving the AI autobahn from a hardware perspective so that we can get the AI software cars to go faster on them." Lenovo—as expected—is jumping on the AI-on-device train, but it will be diversifying its range of AI server systems with new AMD and Intel-powered options. The company has reacted to recent Team Green AI GPU supply issues—alternative units are now in the picture: "with NVIDIA, I think there's obviously lead times associated with it, and there's some end customer identification, to make sure that the products are going to certain identified end customers. As we showcased at Tech World with NVIDIA on stage, AMD on stage, Intel on stage and Microsoft on stage, those industry partnerships are critical to not only how we operate on a tactical supply chain question but also on a strategic what's our value proposition."

McCurdy did not go into detail about upcoming Intel-based server equipment, but seemed excited about AMD's Instinct MI300X accelerator—Lenovo was (previously) announced as one of the early OEM takers of Team Red's latest CDNA 3.0 tech. CRN asked about the firm's outlook for upcoming MI300X-based inventory—McCurdy responded with: "I won't comment on an unreleased product, but the partnership I think illustrates the larger point, which is the industry is looking for a broad array of options. Obviously, when you have any sort of lead times, especially six-month, nine-month and 12-month lead times, there is interest in this incredible technology to be more broadly available. I think you could say in a very generic sense, demand is as high as we've ever seen for the product. And then it comes down to getting the infrastructure launched, getting testing done, and getting workloads validated, and all that work is underway. So I think there is a very hungry end customer-partner user base when it comes to alternatives and a more broad, diverse set of solutions."

The Taiwanese Ministry of Economic Affairs (MOEA) managed to herd government representatives and leading Information and Communication Technology (ICT) industry figures together for an important meeting, according to DigiTimes Asia. The report suggests that the main topic of discussion focused on an anticipated growth of Taiwan's ICT industry—current market trends were analyzed, revealing that the nation absolutely dominates in the AI server segment. The MOEA has (allegedly) determined that Taiwan has shipped 90% of global AI server equipment—DigiTimes claims (based on insider info) that: "American brand vendors are expected to source their AI servers from Taiwanese partners." North American customers could be (presently) 100% reliant on supplies of Taiwanese-produced equipment—a scenario that potentially complicates ongoing international tensions.

The report posits that involved parties have formed plans to seize opportunities within an evergrowing global demand for AI hardware—a 90% market dominance is clearly not enough for some very ambitious industry bosses—although manufacturers will need to jump over several (rising) cost hurdles. Key components for AI servers are reported to be much higher than vanilla server parts—DigiTimes believes that AI processor/accelerator chips are priced close to ten times higher than general purpose server CPUs. Similar price hikes have reportedly affected AI adjacent component supply chains—notably cooling, power supplies and passive parts. Taiwanese manufacturers have spread operations around the world, but industry watchdogs (largely) believe that the best stuff gets produced on home ground—global expansions are underway, perhaps inching closer to better balanced supply conditions.