Cincoze will showcase its full range of embedded computing solutions at Embedded World 2025 (Hall 1, Booth No.: 1-407) in Nuremberg, Germany, on March 11-13. Cincoze will display world-class industrial embedded computing products around the theme of "Edge AI, Smart Integration," encompassing the full spectrum of industrial application environments in four dedicated zones, including GPU embedded computers, DIN-Rail computers, rugged embedded computers, and industrial panel PCs and monitors.

GPU Embedded Computers: AI Application Solutions
The GPU Computing - GOLD product line combines powerful CPUs and GPUs to meet the ultimate performance requirements for edge AI applications. The three-series lineup covers Light, Medium, and Heavy AI use cases. The GJ series features an NVIDIA Jetson SoM GPU with a low-power design specially designed for Light AI applications. The GM series supports MXM GPUs and can meet mobile or Medium AI application requirements. The flagship GP series supports up to two 250 W full-length GPU cards and has patents for heat dissipation, scalability, and securing, making it the best choice for Heavy AI applications. The entire product line has passed EN50121-3-2, E-mark, and MIL-STD-810H to ensure reliability across applications in different industries.

Navigating AMD's various modern processor model naming schemes is tricky business, and another layer of complexity has been added this week; with newly revealed "Strix Point" and "Krackan Point" CPUs. Three previously unannounced SKUs have appeared on AMD's Chinese website: Ryzen AI 9 H 365, Ryzen AI 7 H 350, and Ryzen AI 5 H 340. At first glance, these models codes seem to be familiar—after a double take, we see a small difference in nomenclature. The addition of a middle-placed/detached "H" has press outlets and hardware enthusiasts scratching their collective heads. After discovering Team Red's Ryzen AI 9 H 365 APU listing, Lonely City Hardware posted a humorous observation on social media: "for the Chinese market. No one can remember the full name."

Frustratingly, Western search engines (at the time of writing) just point you to the non-H equivalents. The "H" designation denotes Chinese market exclusivity; TechPowerUp has covered previous-generation examples in the recent past. When comparing technical details and specification sheets to Western equivalents, VideoCardz noted that there were no apparent differences—platform and packaging are the same (FP8). A cross-reference—of clock speeds, thermal ratings, and core architecture (Zen 5/Zen 5C)—points to spec parity across East and West variants.

Lenovo Group Limited (HKSE: 992) (ADR: LNVGY), together with its subsidiaries ('the Group'), today announced Q3 results for fiscal year 2024/25, reporting significant increases in overall group revenue and profit. Revenue grew 20% year-on-year to US$18.8 billion, marking the third consecutive quarter of double-digit growth. Net income more than doubled year-on-year to US$693 million (including a non-recurring income tax credit of US$282 million) on a Hong Kong Financial Reporting Standards (HKFRS) basis. The Group's diversified growth engines continue to accelerate, with non-PC revenue mix up more than four points year-on-year to 46%. The quarter's results were driven by the Group's focused hybrid-AI strategy, the turnaround of the Infrastructure Solutions Group, as well as double-digit growth for both the Intelligent Devices Group and Solutions and Services Group.

Lenovo continues to invest in R&D, with R&D expenses up nearly 14% year-on-year to US$621 million. At the recent global technology event CES 2025, Lenovo launched a series of innovative products, including the world's first rollable AI laptop, the world's first handheld gaming device that allows gamers free choice of Windows OS or Steam OS, as well as Moto AI - winning 185 industry awards for its portfolio of innovation.

This new generation of PCs, introduced in December 2023 with the Intel Core Ultra processor family, combines the power of a central processing unit (CPU), graphics processing unit (GPU) and neural processing unit (NPU) to elevate user productivity, creativity, gaming, entertainment, security and more.

Powerful hardware that delivers the performance needed for modern-day artificial intelligence (AI) workloads is only part of what makes a great PC an AI PC. The big opportunity for the PC industry is clear: develop new AI software and new user experiences that take advantage of this modern hardware. Finding fast, efficient ways to create new AI assistants that help with everyday tasks is the next frontier for making AI PCs deliver the best AI experience. At CES Las Vegas in January, Intel unveiled Intel AI Assistant Builder (code-named Project SuperBuilder). It's a fuss-free solution that enables computer makers and software vendors to create tailored AI assistants for any use case in minutes.

Investment bank Morgan Stanley has estimated that an astonishing 77% of all globally produced silicon wafers dedicated to AI accelerators will be consumed by none other than NVIDIA. Often, investment research by large investment banks like Morgan Stanley includes information from the semiconductor supply chain, which is constantly expanding to meet NVIDIA's demands. When looking at wafer volume for AI accelerators, it is estimated that in 2024, NVIDIA captured nearly 51% of wafer consumption for its chips, more than half of all demand. With NVIDIA's volume projected to grow to 77%, this represents more than a 50% year-over-year increase, which is incredible for a company of NVIDIA's size. Right now, NVIDIA is phasing out its H100 accelerators in favor of Blackwell 100/200 and the upcoming 300 series of GPUs paired with Grace CPUs.

NVIDIA is accelerating its product deployment timeline and investing a lot in its internal research and development. Morgan Stanley also projects that NVIDIA will invest almost $16 billion in its R&D budget, enough to endure four to five years of development cycles running three design teams sequentially and still delivering new products on an 18-24 month cadence. The scale of this efficiency and development rivals everyone else in the industry. With all this praise, NVIDIA's Q4 revenue report is coming in exactly a week on February 26, so we have to see what its CEO, Jensen Huang, will deliver and show some estimates for the coming months.

The telecom industry's efforts to drive efficiencies with AI are beginning to show fruit. An increasing focus on deploying AI into radio access networks (RANs) was among the key findings of NVIDIA's third annual "State of AI in Telecommunications" survey, as more than a third of respondents indicated they're investing or planning to invest in AI-RAN.

The survey polled more than 450 telecommunications professionals worldwide, revealing continued momentum for AI adoption—including growth in generative AI use cases—and how the technology is helping optimize customer experiences and increase employee productivity. Of the telecommunications professionals surveyed, almost all stated that their company is actively deploying or assessing AI projects.

Microsoft has launched Majorana 1, the world's first quantum processor powered by a Topological Core architecture, marking a significant step toward fault-tolerant, utility-scale quantum computing. The chip leverages tetron qubits—topological qubits built on Majorana zero modes (MZMs)—to achieve stability and scalability, with a roadmap to one million qubits, a threshold critical for solving industrial challenges like microplastic degradation and self-healing materials. At the heart of Majorana 1 lies a superconductor-semiconductor heterostructure combining indium arsenide and aluminium. This "topoconductor" material enables precise control of MZMs, exotic quantum particles that encode information non-locally, inherently resisting noise and errors. The design, detailed in the latest paper, arranges MZMs in H-shaped nanowires, forming two-sided tetrons that suppress errors exponentially via three factors: topological gap-to-temperature ratio, wire length-to-coherence length, and high-fidelity microwave readout. Microsoft claims that thopoconductor can "create an entirely new state of matter - not a solid, liquid or gas but a topological state."

Unlike conventional qubits requiring analog tuning, Microsoft's architecture uses digital voltage pulses for error-resistant, measurement-based operations. This approach simplifies scaling, with the current chip housing eight tetrons and supporting protocols for quantum error detection, such as the Hastings-Haah Floquet codes and ladder codes outlined in Microsoft's technical roadmap. These codes rely on single- and two-qubit Pauli measurements, native to tetrons, to detect and correct errors without complex gate sequences. DARPA's US2QC program validated that Microsoft's topology-first strategy minimizes overhead, enabling a future million-qubit system compact enough to fit in Azure datacenters. The chip's quantum capacitance measurement system detects parity shifts in microseconds, achieving a signal-to-noise ratio critical for fault tolerance. Applications span designing catalysts to break down pollutants, optimizing enzymes for agriculture, and simulating novel materials. Microsoft aims to merge quantum, AI, and high-performance computing into Azure, accelerating discoveries once deemed decades away. Majorana 1 proves that topological qubits—once a high-risk bet—are now the cornerstone of scalable quantum systems.

The AI Pin - Humane's first, and last product - received an overwhelmingly negative reception at launch, and that's putting it mildly. The device was hindered by poor usability and an extremely laggy operating system that made even the simplest of tasks an absolute chore. The product, unsurprisingly, was criticized by almost every reviewer who touched it, and rumors regarding a potential acquisition of Humane soon began to circulate. Now, HP has seemingly finalized a $116-million acquisition offer for the startup that once raised over $230 million, and valued itself at $1 billion. It appears that HP wants almost all of Humane's assets - with the notable exception of one key product, the AI Pin.

As such, once the calendar reaches the 28th of February, the AI Pin will cease to function. The servers that the AI Pin utilized for communications will be shut down, rendering the AI Pin unable to access customer's cloud data, make phone calls, send AI queries, or text messages. Customers who bought the Pin in the last 90 days will be eligible for a full refund, whereas those who bought the ill-fated gadget before that will soon have an arguably good-looking fashion accessory that will probably still be able to tell them the time. After all, the product's build quality and design was the lone aspect of the AI Pin that received praise. It remains to be seen how HP puts Humane's R&D to use, although considering the AI hype that is engulfing the consumer tech industry, it wouldn't be surprising to see HP leverage Humane's tech to carve out its own niche in the AI-assisted personal computing space. Of course, that is contingent on HP's implementation being better than what Humane pulled off the last time around.

It's that time again! 3DExperience World 2025 kicks off on February 23 and runs through February 26 at the George R. Brown Convention Center in Houston, Texas. The show is hosted by Dassault Systèmes and highlights annual advances and improvements throughout its product ecosystem. It's a great opportunity to meet the engineers, students, and industry professionals who use SolidWorks and other Dassault Systèmes applications across browsers, local workstations, and the cloud.

One of the best parts of the event for me is showcasing how advances in silicon engineering can lead to transformational products - systems that offer performance, features, and efficiency that wasn't possible before. In 2024, the AMD Ryzen Threadripper PRO 7000 WX-Series processor stole the proverbial show with its excellent single-thread performance, support for multi-GPU configurations for AI training, and up to 96 cores and 2T B of memory for the largest and most demanding projects. This year, AMD has complemented these full-size tower systems with compact and mobile workstations based on the new AMD Ryzen AI Max PRO Series processors. Drop by booth #919 and see the array of systems and demos on exhibit.

Senao Networks Inc. (SNI), a global leader in AI computing and networking solutions, will be exhibiting at 2025 Mobile World Congress (MWC) in Barcelona. At the event, SNI will showcase its latest AI-driven innovations, including AI Servers, AI Cameras, AIPCs, Cloud Solutions, and Titanium Power Supply, reinforcing its vision of "AI Everywhere."

Senao Networks continues to advance AI computing with new products designed to enhance security, efficiency, and connectivity.

Advantech, a leader in edge computing solutions, is excited to announce the launch of the UBX-330M, a compact NUC-sized edge computer designed to power intelligent city services with advanced AI capabilities.

The UBX-330M is powered by Intel Core Ultra Processors (Meteor Lake H and U), which integrate a CPU, GPU, and NPU to deliver exceptional AI performance in a small form factor. Built as an AI-ready platform, the UBX-330M is perfect for applications requiring robust processing power across industries such as smart retail, hospitality, public spaces, education, entertainment, enterprise, and smart buildings.

ASUS Republic of Gamers (ROG) announced that the 2025 ROG Flow Z13 is now available for pre-order. This versatile gaming 2-in-1 can feature up to AMD's newest AMD Ryzen AI Max+ 395 Processor with Radeon 8060S Graphics and a unified memory structure, allowing for incredible performance and power efficiency. A new stainless steel and copper vapor chamber, larger intake vents, and 2nd Gen Arc Flow Fans offer 70% more airflow for quiet and efficient cooling.

This 13-inch tablet boasts a stunning ROG Nebula Display, a 2.5K resolution 180 Hz touchscreen with 500 nits of peak brightness, and Corning Gorilla Glass 5 protection. The Flow Z13 now also features a larger 70Wh battery, a larger touchpad and keycaps, and a convenient Command Center button for quick access to vital system functions. With dual USB-C ports, both of which support USB4 and power delivery, as well as a dedicated HDMI 2.1 port, the Flow Z13 lets gamers leave their dongles at home.

The global semiconductor manufacturing industry closed 2024 with strong fourth quarter results and solid year-on-year (YoY) growth across most of the key industry segments, SEMI announced today in its Q4 2024 publication of the Semiconductor Manufacturing Monitor (SMM) Report, prepared in partnership with TechInsights. The industry outlook is cautiously optimistic at the start of 2025 as seasonality and macroeconomic uncertainty may impede near-term growth despite momentum from strong investments related to AI applications.

After declining in the first half of 2024, electronics sales bounced back later in the year resulting in a 2% annual increase. Electronics sales grew 4% YoY in Q4 2024 and are expected to see a 1% YoY increase in Q1 2025 impacted by seasonality. Integrated circuit (IC) sales rose by 29% YoY in Q4 2024 and continued growth is expected in Q1 2025 with a 23% increase YoY as AI-fueled demand continues boosting shipments of high-performance computing (HPC) and datacenter memory chips.

Nexa AI, today, announced NexaQuants of two DeepSeek R1 Distills: The DeepSeek R1 Distill Qwen 1.5B and DeepSeek R1 Distill Llama 8B. Popular quantization methods like the llama.cpp based Q4 K M allow large language models to significantly reduce their memory footprint and typically offer low perplexity loss for dense models as a tradeoff. However, even low perplexity loss can result in a reasoning capability hit for (dense or MoE) models that use Chain of Thought traces. Nexa AI has stated that NexaQuants are able to recover this reasoning capability loss (compared to the full 16-bit precision) while keeping the 4-bit quantization and all the while retaining the performance advantage. Benchmarks provided by Nexa AI can be seen below.

We can see that the Q4 K M quantized DeepSeek R1 distills score slightly less (except for the AIME24 bench on Llama 3 8b distill, which scores significantly lower) in LLM benchmarks like GPQA and AIME24 compared to their full 16-bit counter parts. Moving to a Q6 or Q8 quantization would be one way to fix this problem - but would result in the model becoming slightly slower to run and requiring more memory. Nexa AI has stated that NexaQuants use a proprietary quantization method to recover the loss while keeping the quantization at 4-bits. This means users can theoretically get the best of both worlds: accuracy and speed.

Yesterday, the ASUS Chinese office announced a special event—on February 25—dedicated to launching a next-gen AMD APU-powered premium notebook model: "ROG Magic X (or Illusion X) is the first to be equipped with the Ryzen AI MAX+ three-in-one chip, which can efficiently coordinate multiple modes, provide combat power and computing power on demand, and can handle e-sports, creation and AI with one chip!" The manufacturer's Weibo post has generated plenty of buzz; industry insiders reckon that reviews could be published today (February 18)—HXL/9550pro informed VideoCardz with a not so cryptic message: "STX-Halo NDA: Feb 18th 2025."

Western press outlets point out that the ROG Magic X is a local variant of the familiar ROG Flow Z13 design; a 2025 refresh brings in AMD's much anticipated "Strix Halo" APU design. Team Red-authored marketing material and pre-release evaluation leaks have hinted about impressive integrated graphics solution performance; equalling or even exceeding that of previous-gen dGPUs. Well-known North American hardware review outlets have dropped hints (NDA permitting) about AMD's Ryzen Al Max+ 395 and Max 390 processors. Hardware Canucks could barely contain their excitement regarding the potent Zen 4 and RDNA 3.5 combo package; to the point of wish listing a potential direct successor: "Strix Halo is one of the most exciting things launched into the PC space in the last half decade. Full stop...AMD can't keep this as a one-off. If it's followed up with Zen 6 and RDNA 4 next year...watch out." Naturally, Team Red's cutting-edge mobile CPU technology is arriving in devices with high asking prices. The aforementioned ROG Flow Z13 2025 model—configured with top specs—is priced at $2699. Notebookcheck reckons that ASUS has tacked on an extra $500, since an announcement of initial pricing at CES 2025.

TrendForce's latest findings reveal that the NAND Flash market continues to be plagued by oversupply in the first quarter of 2025, leading to sustained price declines and financial strain for suppliers. However, TrendForce anticipates a significant improvement in the market's supply-demand balance in the second half of the year.

Key factors contributing to this shift include proactive production cuts by manufacturers, inventory reductions in the smartphone sector, and growing demand driven by AI and DeepSeek applications. These elements are expected to alleviate oversupply and support a price rebound for NAND Flash.

ASUS's Republic of Gamers China account on Weibo has teased the ROG Magic X mobile device that combines laptop/tablet form with a detachable keyboard. Inside, the device is powered by AMD Ryzen AI MAX+ SoC, which ASUS called a "three-in-one" chip, mainly due to its CPU, NPU, and iGPU combination. One possible SKU for ROG Magic X is AMD's top-end Ryzen AI MAX+ 395 processor. Carrying 16 "Zen 5" cores and 32 threads, the chip is designed for AI-enhanced laptops with 126 combined TOPS of AI processing power. The Ryzen AI MAX+ 395 features 64 MB of L3 cache and operates at a base clock of 3 GHz, with boost capabilities up to 5.1 GHz, depending on workload conditions. Manufactured on TSMC's 4 nm process node, the processor maintains a modest 55 W TDP, suitable for high-performance mobile systems. The chip includes support for ECC memory and PCIe Gen 5. It integrates the Radeon 8060S solution based on RDNA 3.5 architecture for graphics.

We are yet to see more details about the ROG Magic X, but with the arrival of AMD Ryzen AI MAX+, we assume this machine will result in a powerful gaming device for users on the go. More details are expected on February 25, when ASUS plans to showcase it. Pricing and availability are also expected to follow soon after.

According to a recent report, Apple has apparently finalized on a partner to bring Apple Intelligence features to its second-largest market, China. Of course, China has strict regulations in place, which have clearly turned out to be rather difficult to navigate for Apple. Previous leaks have revealed that a Deepseek partnership was on the cards for the Cupertino giant, although that did not lead to fruition, with Apple settling for Alibaba as its primary partner. As MacRumors notes, Alibaba will function as a censorship layer of sorts, thereby complying with government-directed filtering and information control. Basically, if the Chinese government deems a certain kind of information inappropriate in any way, it can simply direct Alibaba to have it removed and not served again.

Baidu, Safari's default search engine in China, will function as a secondary partner, aiding Apple Intelligence's 'Visual Intelligence' features. If things go to plan, the AI features should roll out in China sometime towards the middle of this year. Apple Intelligence has faced quite a contentious launch, having struggled with multiple delays and widespread criticism regarding not only the real-world efficacy and usefulness of its features, but also the multiple times that its AI-generated notifications have wildly misrepresented real-life events. The report further states that iPhones sold outside of China will not have access to the China-specific AI system, which is to be expected. It is yet to be seen how the Apple Intelligence launch plays out in China, although we should be able to find out soon enough.

The notion of designing tailor-made AI-crunching chips is nothing new; several major organizations—with access to big coffers—are engaged in the formulation of proprietary hardware. A new DigiTimes Asia report suggests that DeepSeek is the latest company to jump on the in-house design bandwagon. The publication's insider network believes that the open-source large language model development house has: "initiated a major recruitment drive for semiconductor design talent, signaling potential plans to develop its proprietary processors." The recent news cycle has highlighted DeepSeek's deep reliance on an NVIDIA ecosystem, despite alternative options emerging from local sources.

Industry watchdogs believe that DeepSeek has access to 10,000 of sanction-approved Team Green "Hopper" H800 AI chips, and (now banned) 10,000 H100 AI GPUs. Around late January, DeepSeek's Scale AI CEO—Alexandr Wang—claimed that the organization could utilize up to 50,000 H100 chips for model training purposes. This unsubstantiated declaration raised eyebrows; given current global political tensions. Press outlets have speculated that DeepSeek is in no rush to reveal its full deck of cards, but they appear to have a competitive volume of resources; when lined up against with Western competitors. The DigiTimes news article did not provide any detailed insight into the rumored in-house chip design. DeepSeek faces a major challenge; the Chinese semiconductor industry trails behind market leading regions. Will local foundries be able to provide an advanced enough node process for required purposes?

AMD and Nutanix have jointly developed virtualization/HCI solutions since 2019, working with major OEMs including Dell, HP and Lenovo, systems integrators and other resellers and partners. You can learn more about AMD-Nutanix solutions here.

AMD EPYC Processors
The EPYC 9004 family of high performance processors provide up to 128 cores per processor to help meet the demands of a wide range of workloads and use cases. High density core counts allow you to reduce the number of servers you need by as much as a five to one ratio when looking at retiring older, inefficient servers and replacing with a new one. Systems based on AMD processors can also be more energy efficient than many competitive processor based systems. For example, running 2000 VMs on 11 2P AMD EPYC 9654 processor-powered servers will use up to 29% less power annually than the 17 2P Intel Xeon Platinum 8490H processor-based servers required to deliver the same performance, while helping reduce CAPEX up to 46%.

Retailers are set to open up pre-order floodgates for upcoming GeForce RTX 50-series laptops on February 25, as we learned earlier this week. According to a new DigiTimes report, the launch of mobile devices—sporting Team Green "Blackwell" GPUs—is expected to be "significantly delayed." A loose March launch window was teased during Jensen Huang's keynote presentation at CES 2025, but supply chain insiders have claimed that high-end RTX 50 laptops were "originally planned to be launched in January 2025." Additionally, they surmise that mid-range and low-end offerings are postponed to April. DigiTimes believes that the rumored postponements have surprised supply chain moles; Team Green is not known to delay product launches. Extenuating circumstances are cited as the reason behind alleged deferred release windows, but insiders have not yet determined the extent of lengthened launch parameters.

An anonymous source stated: "NVIDIA, which has never been late in the past, also encountered this situation. It is probably related to NVIDIA's full sprint to AI servers. Even though there are differences in server and PC chip design and manufacturing processes, the company's resource allocation may still affect the debugging efficiency of new products." Other insiders have murmured about GeForce RTX 50-series mobile GPU performance not meeting expectations. Rumors have swirled about problems with early sample units; most notably the encountering of major screen issues when the "hardware is turned on." Laptop/notebook supply chain insiders reckon that manufacturers have anticipated a healthy level of growth in 2025—thanks to the emergence of new NVIDIA graphics cards—but targets have been reduced, due to anticipated delays. Optimistic industry chatter predicts higher education students and esport enthusiasts driving unit sales upward, following a stagnant 2024 market.

Thanks to a well-known industry leaker, Jaykihn, Intel's Panther Lake-H processor family, built on the 18A process node, features three distinct configurations, with several power profiles for each case. The flagship model combines four "Cougar Cove" P-cores, eight "Skymont" E-cores, and four LPE cores alongside a 12-core Xe3 "Celestial" GPU. This variant supports LPDDR5X memory exclusively and delivers 180 TOPS of computational power for local AI workloads, operating at 25 W PL1 (base) and 64 W PL2 (turbo) power levels. Secondary configurations include a 4P+8E+4LP+4Xe3 model and a 4P+0E+4LP+4Xe3 variant, both rated at 100 TOPS and supporting both LPDDR5X and DDR5 memory.

The entry-level model operates at 15 W PL1 with 44 W PL2 in baseline mode, scaling to 25 W PL1 and 55 W PL2 in performance mode. All variants feature Thunderbolt 4 connectivity, with high-end models incorporating expanded PCIe 5.0 lane configurations. The integrated Xe3 graphics architecture scales from four to 12 cores across the product stack, with the top SKU eliminating DDR5 compatibility in favor of LPDDR5X optimization. The Panther Lake processor family is slated for launch within the latter half of 2025, and it will be the company's leading 18A product. As a "Lunar Lake" successor, Panther Lake will deliver improved IPC and optimization for new cores in the same device form-factor like laptops, ultrabooks, and handhelds.

AMD's Radeon RX 9000 series GPUs are expected to come with up to 16 GB of GDDR6 memory. However, AMD is reportedly expanding its RX 9070 lineup with a new 32 GB variant, according to sources on Chiphell. The card, speculatively called the RX 9070 XT 32 GB, is slated for release at the end of Q2 2025. The current GDDR6 memory modules used in GPUs carry a capacity of 2 GB per module only, meaning that a design with 32 GB of VRAM would require as many as 16 memory modules on a single card. No 2 GB+ GDDR6 memory modules are available, meaning that the design would require memory module installation on both the front and back of the PCB. Consumers GPUs are not known for this, but it is a possibility with workstation/prosumer grade GPUs employing this engineering tactic to boost capacity,

While we don't have information on the GPU architecture, discussions point to potential modifications of the existing Navi 48 silicon. This release is positioned as a gaming card rather than a workstation-class Radeon PRO 9000 series product. AMD appears to be targeting gamers interested in running AI workloads, which typically require massive VRAM amounts to run locally. Additionally, investing in a GPU with a big VRAM capacity is essentially "future-proofing" for gamers who plan to keep their cards for longer, as recent games have been spiking VRAM usage by a large margin. The combination of gaming and AI workloads may have made AMD reconsider some of its product offerings, potentially giving us the Radeon RX 9070 XT 32 GB SKU. We have to wait for the Q2 to start, and we can expect more details by then.

Update 20:55 UTC: AMD's Frank Azor on X debunked rumors of the 32 GB SKU coming to gamers. So, this will not happen. Instead, we could be looking at prosumer oriented AMD Radeon Pro GPU with 32 GB of memory instead.

Hewlett Packard Enterprise announced today that it has shipped its first NVIDIA Blackwell family-based solution, the NVIDIA GB200 NVL72. This rack-scale system by HPE is designed to help service providers and large enterprises quickly deploy very large, complex AI clusters with advanced, direct liquid cooling solutions to optimize efficiency and performance. "AI service providers and large enterprise model builders are under tremendous pressure to offer scalability, extreme performance, and fast time-to-deployment," said Trish Damkroger, senior vice president and general manager of HPC & AI Infrastructure Solutions, HPE. "As builders of the world's top three fastest systems with direct liquid cooling, HPE offers customers lower cost per token training and best-in-class performance with industry-leading services expertise."

The NVIDIA GB200 NVL72 features shared-memory, low-latency architecture with the latest GPU technology designed for extremely large AI models of over a trillion parameters, in one memory space. GB200 NVL72 offers seamless integration of NVIDIA CPUs, GPUs, compute and switch trays, networking, and software, bringing together extreme performance to address heavily parallelizable workloads, like generative AI (GenAI) model training and inferencing, along with NVIDIA software applications. "Engineers, scientists and researchers need cutting-edge liquid cooling technology to keep up with increasing power and compute requirements," said Bob Pette, vice president of enterprise platforms at NVIDIA. "Building on continued collaboration between HPE and NVIDIA, HPE's first shipment of NVIDIA GB200 NVL72 will help service providers and large enterprises efficiently build, deploy and scale large AI clusters."

OnLogic, a leading provider of edge computing solutions, has launched the Axial AX300, a highly customizable and powerful edge server. The AX300 is engineered to help businesses of any size better leverage their on-site data and unlock the potential of AI by placing powerful computing capabilities on-site.

The Axial AX300 empowers organizations to seamlessly move computing resources closer to the data source, providing significant advantages in performance, latency, operational efficiency, and total cost of ownership over cloud-based data management. With its robust design, flexible configuration options, and advanced security features, the Axial AX300 is the ideal platform for a wide range of highly-impactful edge computing applications, including:

• AI/ML inference and training: Leveraging the power of AI/ML at the edge for real-time insights, predictive maintenance, and improved decision-making.
• Data analytics: Processing and analyzing data generated by IoT devices and sensors in real-time to improve operational efficiency.
• Virtualization: Consolidating multiple workloads onto a single server, optimizing resource utilization and simplifying deployment and management.