MiTAC Computing Technology Corp., a global leader in high-performance, energy-efficient server solutions and a subsidiary of MiTAC Holdings Corporation (TWSE:3706), is highlighting its latest agentic AI infrastructure at AMD Advancing AI. MiTAC's showcase focuses on its premier exhibition lineup, featuring its latest liquid-cooled and air-cooled AI servers and next-generation multi-node platforms built on the new 6th Gen AMD EPYC Server CPUs. As part of the launch, MiTAC is introducing a portfolio of next-generation platforms designed to help customers scale AI, cloud, HPC and enterprise workloads with greater performance, efficiency and flexibility.

The new MiTAC M2810Z6 and M2610Z6 systems, powered by 6th Gen EPYC Server CPUs, reflect MiTAC's commitment to delivering infrastructure choices that align compute density, memory bandwidth, and I/O capability with evolving data center requirements. With support for AMD's Venice "Zen 6" architecture, PCIe Gen 6 I/O subsystem, and CXL 3.1, these platforms are engineered to meet the demands of modern AI-driven environments while optimizing power and system density.

ASRock Rack Inc., a leading innovative server company, today announced support for the newly-launched 6th Gen AMD EPYC 9006 Series processors, unveiled this week at AMD Advancing AI 2026 in San Francisco. ASRock Rack will showcase its upcoming server platforms optimized for the new processor generation at the event, demonstrating its commitment to delivering advanced infrastructure for enterprise AI, cloud, and HPC workloads.

Delivering Leadership Performance for the Agentic AI Era
As agentic AI enters enterprise-scale deployment, the 6th Gen AMD EPYC 9006 Series processors deliver the performance, efficiency, and scalability required to support increasingly complex AI services and applications. Featuring up to 256 cores, industry-leading 5 GHz frequencies, and PCIe Gen 6 connectivity, 6th Gen EPYC Server CPUs enable organizations to scale AI agents, maximize AI host-node throughput and GPU utilization, and power the general-purpose workloads essential to modern data centers.

In its MLPerf Inference 6.0 submission, AMD did not simply revisit familiar benchmarks with a faster GPU. It expanded into first-time workloads, crossed the 1-million-tokens-per-second threshold at multinode scale and showed that partners can reproduce the results across a broader ecosystem. That combination matters because our customers no longer evaluate inference platforms on one metric alone. They want competitive single-node performance, efficient scale-out, faster bring-up on new models, reproducible results across partner systems and confidence that the software stack can keep pace. MLPerf Inference 6.0 let us show all of that in one submission.

Just as important, we showed that these results are not isolated. A broad partner ecosystem submitted across four AMD Instinct GPU types that closely reproduced numbers submitted by AMD and the first three-GPU heterogeneous MLPerf submission demonstrated that AMD hardware and AMD ROCm software can orchestrate meaningful inference throughput even across systems in different geographies.

Samsung Electronics Co., Ltd. today announced it has signed a Memorandum of Understanding (MOU) with AMD to expand their strategic collaboration on next-generation AI memory and computing technologies. The signing ceremony was held at Samsung's most advanced chip manufacturing complex in Pyeongtaek, Korea, attended by Dr. Lisa Su, Chair and CEO of AMD, and Young Hyun Jun, Vice Chairman & CEO of Samsung Electronics.

"Samsung and AMD share a commitment to advancing AI computing, and this agreement reflects the growing scope of our collaboration," said Young Hyun Jun, Vice Chairman & CEO of Samsung Electronics. "From industry-leading HBM4 and next-generation memory architectures to cutting-edge foundry and advanced packaging, Samsung is uniquely positioned to deliver unrivaled turnkey capabilities that support AMD's evolving AI roadmap."

GIGABYTE Technology, a global leader known for its engineering excellence in high-performance computing and AI servers, extends its comprehensive end-to-end AI infrastructure portfolio designed specifically for the telecommunications industry at MWC 2026. GIGABYTE's end-to-end product solutions enable operators to convert massive volumes of network data into intelligence, automation, and new revenue streams, as telecommunications networks evolve from data carriers into AI-powered digital platforms.

At the core of the telco-to-AI transformation is the AI Factory, where network and subscriber data are converted into operational intelligence and commercialized AI services. GIGABYTE addresses this need with GB300 NVL72, a liquid-cooled rack-scale platform integrating 72 NVIDIA Blackwell Ultra GPUs and 36 NVIDIA Grace CPUs in a single system. Connected via NVIDIA Quantum-X800 InfiniBand or NVIDIA Spectrum-X Ethernet and NVIDIA ConnectX -8 SuperNIC s, GB300 NVL72 is optimized for large-scale AI training and inference workloads, enabling operators to automate operations, optimize network planning, and deploy AI-driven services at telecom scale.

AMD is excited to announce Day 0 support for Alibaba's latest generation of Large Language Models, Qwen 3.5, on AMD Instinct MI300X, MI325X, and MI355X GPU accelerators, in close collaboration with Alibaba Qwen team. Leveraging the optimized ROCm software stack, SGLang and vLLM inference serving framework, developers can immediately deploy these state-of-the-art models.

The Strategic Value of Qwen 3.5 on AMD Instinct
Empowering Next-Generation AI Agents—This Day 0 enablement is designed for AI developers, system architects, and DevOps professionals building the next wave of AI agents and enterprise platforms. While previous models required trade-offs between parameter depth and reasoning speed, the Qwen 3.5 family on AMD Instinct GPUs allows teams to deploy massive 256K context windows and complex multimodal workflows with unprecedented efficiency.

Modern AI workloads demand more than raw compute—they require a tightly integrated software stack that can extract maximum performance, scale efficiently across systems, and operate reliably in production environments. With the latest ROCm 7.2 release, we're delivering a broad set of optimizations and software enhancements designed to improve developer productivity, runtime performance, and enterprise readiness.

In this blog, we highlight the latest ROCm 7.2 enhancements for AMD Instinct GPUs, designed to boost AI and HPC performance. Learn how hipBLASLt and GEMM optimizations, FP8/FP4 support in rocMLIR and MIGraphX, and topology-aware communication with GDA and RCCL deliver higher throughput and lower latency. We also cover AI model tuning for AMD Instinct MI300X and MI350 GPUs and Node Power Management (NPM) for efficient multi-GPU operation—together enabling faster, more scalable, and reliable AI workloads.

The rapid growth of GenAI and LLM workloads, from agentic workflows and multi-step tool use to retrieval-augmented reasoning, demands inference infrastructure that is fast, adaptable, and highly optimized. While AMD continues to invest in general-purpose inference frameworks such as vLLM and SGLang, ATOM provides the most direct path to peak Instinct MI355X GPU performance for modern reasoning and MoE-heavy workloads, which increasingly dominate frontier LLM architectures.

Over the past months, AMD have implemented numerous optimizations to improve both single-node performance and multi-node distributed inference for DeepSeek-R1 on the MI355X GPU.

AI training workloads are pushing the limits of modern GPU architectures. With the release of AMD ROCm 7.0 software, AMD is raising the bar for high-performance training by delivering optimized support for LLM workloads across the JAX and PyTorch frameworks. The latest v25.9 Training Dockers demonstrate exceptional scaling efficiency for both single-node and multi-node setups, empowering researchers and developers to push model sizes and complexity further than ever.

By integrating Primus, a unified and flexible LLM training framework, the PyTorch training docker streamlines LLM development on AMD Instinct GPUs. Primus now supports both TorchTitan and Megatron-LM backends, while Primus-Turbo accelerates Transformer models, further boosting training throughput on AMD Instinct MI355X GPUs. Try Primus-Repo here.

Vultr, the world's largest privately-held cloud infrastructure company, today announced a major milestone in its long-standing strategic collaboration with AMD (NASDAQ: AMD) to advance and scale AI workloads worldwide. Vultr will launch an AI supercluster, powered by AMD Instinct MI355X GPUs deployed in its new Springfield, Ohio cloud data center location. This 50 MW expansion delivers unprecedented performance per dollar for AI training and inference.

Vultr was among the first cloud providers to deploy AMD Instinct MI325X and AMD Instinct MI355X GPUs, and is now expanding its AI infrastructure with an additional 24,000 AMD Instinct MI355X GPUs in its new Springfield, Ohio campus. This significant deployment reinforces the collaboration between AMD and Vultr to deliver high-performance, energy-efficient AI infrastructure for customers worldwide. Looking ahead, Vultr will extend its adoption of AMD Instinct GPUs by integrating the next generation AMD Instinct MI450 series GPUs and the "Helios" rack-scale infrastructure, further advancing its commitment to the AMD AI platform roadmap.

Super Micro Computer, Inc. (SMCI), a Total IT Solution Provider for AI, Cloud, Storage, and 5G/Edge, is announcing the latest addition to the AMD-based Instinct MI350 series GPU optimized solutions, delivering unparalleled performance, maximum scalability, and power efficiency. Supermicro has designed this new system for organizations that need the high-end performance of AMD Instinct MI355X GPUs but require an air-cooled environment.

"Supermicro leads the industry with the most experience in delivering high-performance solutions in AI and HPC for our customers," said Vik Malyala, SVP Technology and AI at Supermicro. "Supermicro's DCBBS enables us to quickly incorporate AMD solutions by deploying advanced technology with proven data center solutions to market. The addition of the new air-cooled AMD Instinct MI355X GPU systems expands and strengthens our portfolio of AI solutions and gives customers more choices as they build next-generation data centers."

MiTAC Computing Technology, a global leader in high-performance and energy-efficient server solutions, is proud to announce its participation at the Supercomputing (SC) 2025 (November 18-20, St. Louis, Missouri), booth 3916. Under the theme "AI Cluster Power - Cool Fast. Scale Faster.", MiTAC Computing will showcase its modular, highly scalable rack infrastructure designed for demanding AI and HPC workloads. The exhibition will demonstrate the company's full spectrum of capabilities, ranging from single AI servers to complete cluster-level integration, with a focus on cutting-edge liquid cooling and energy-efficient designs to maximize performance and sustainability.

Collaborating with key industry players such as AMD, Broadcom, CoolIT, Intel, KIOXIA, Micron, NVIDIA, Samsung, and Solidigm, MiTAC Computing is dedicated to accelerating the development of advanced computing and high-efficiency data centers.

ASUS today announced an all-new lineup of enterprise and AI/HPC-optimized storage and infrastructure solutions at Supercomputing 2025 (SC25). Recognizing the escalating demands of scaling AI models and memory-intensive workloads, ASUS storage solutions are now a strategic imperative, critical for sustaining efficient AI data processing and managing rapidly expanding datasets. This launch further solidifies the company's position as a total infrastructure provider, delivering an integrated ecosystem spanning compute, storage, networking, and services. ASUS, through its robust global supply chain and logistical capabilities, ensures consistent, reliable product delivery, establishing itself as a trusted partner for organizations deploying resilient and scalable AI environments.

ASUS delivers a full spectrum of storage solutions across block, file, object, and software-defined systems—ensuring flexibility from edge to cloud, and from enterprise applications to AI and HPC workloads. The portfolio supports storage for Enterprise and AI/HPC needs, providing resilient data foundations and scalable performance for data-driven environments.

The latest MLPerf 5.1 Training results mark an important milestone—the first MLPerf training submission using AMD Instinct MI350 Series GPUs. These new benchmarks demonstrate breakthrough generational performance gains and highlight broad ecosystem participation across some of today's most demanding AI training workloads.

Building on the strong MLPerf 5.1 Inference results released earlier this year, this submission represents the first time the AMD Instinct MI350 Series—including both the MI355X and MI350X GPUs—have been publicly benchmarked for AI training. The results show clear progress in scalability, efficiency, and compute performance, underscoring how the AMD Instinct MI350 Series is accelerating the development of next-generation generative AI models.

AMD's expertise in the supercomputers sector seems to pay off as the company secured a $1 billion partnership with the U.S. Department of Energy (DoE) to build two next-generation supercomputers aimed at scientific and national security challenges, from nuclear fusion research to cancer treatments. Energy Secretary Chris Wright said the initiative will "supercharge" progress in nuclear energy, defense technologies and drug discovery, accelerating breakthroughs that traditionally take decades. The first system, Lux, is set to go online within six months. Co-developed by AMD, Hewlett Packard Enterprise, Oracle Cloud Infrastructure, and Oak Ridge National Laboratory (ORNL), Lux will be powered by AMD's Instinct MI355X AI accelerators alongside AMD CPUs and networking chips. ORNL Director Stephen Streiffer noted that Lux will deliver roughly three times the AI performance of today's top supercomputers, while AMD CEO Lisa Su called it "the fastest deployment of this scale we've ever seen." A second system, dubbed Discovery, will follow later in the decade. Built on AMD's upcoming MI430 AI chips, the more advanced machine is expected to be completed by 2028 and operational by 2029. Both systems are part of a broader U.S. effort to maintain leadership in high-performance computing and artificial intelligence.

According to Reuters, the DoE's choice of AMD reflects confidence in the company's proven HPC track record, particularly with Frontier and El Capitan, the world's fastest supercomputers, which also runs on AMD hardware. Wright added that these new systems will help simulate complex processes like plasma dynamics for fusion energy and molecular interactions for drug development. "We're going to see massively faster progress toward harnessing fusion and treating diseases that are still death sentences today," he said. Together, Lux and Discovery mark a milestone for both AMD and U.S. scientific computing and build momentum for AMD's upcoming MI400 accelerators series.

MiTAC Computing Technology, a global leader in high-performance and energy-efficient server solutions, is proud to announce its participation at the 2025 OCP Global Summit (October 13-16, San Jose, CA), Booth C14. Under the theme "From AI Server to Cluster - Open for Growth. Built to Cool." MiTAC will showcase modular, scalable infrastructures advancing from single AI servers to full clusters, powered by cutting-edge liquid-cooling and sustainable designs. Teaming up with AMD, Broadcom, CoolIT, Intel, Micron, Murata, NVIDIA, and Solidigm, MiTAC continues to drive open computing innovation and energy-efficient data center evolution.

Samsung is reportedly set to be the main supplier of HBM4 memory to AMD's upcoming MI450 chips according to TrendForce citing SeDaily. The rumors (news) came just days after AMD announced a multi-year deal with OpenAI paving the way for a 6-Gigawatt partnership (and the option for OpenAI to acquire up to 10% of AMD). Collaboration between Samsung and AMD is nothing new as current generation chips such as MI350X and MI355X feature 12-high HBM3e memory from Samsung and Micron.

OpenAI made initial agreements with Samsung and SK hynix to obtain memory for its huge Stargate data center project last week, before joining forces with AMD. Reuters reports that OpenAI's needs might soar to 900,000 DRAM wafers - a number that could make up almost 40% of the world's total DRAM production. Maeil Business Newspaper states that Samsung plans to provide not just HBM but also graphics DRAM (GDDR) high-capacity SSDs, and LPDDR5X-PIM - low-power DRAM with in-memory computing - to use in AI applications for OpenAI's Stargate project. The industry seems to polarize even more around NVIDIA and AMD since Intel just teamed up with Team Green. To counter NVIDIA's proprietary NVLink, AMD is pushing for the Ultra Accelerator Link (UALink) open-standard alternative. This initiative managed to gather quite a sizable momentum, gathering partners such as Apple, Google, Microsoft, Synopsis, Meta, and Intel. The latter's presence in the UALink consortium remains to be seen, due to its latest partnership with NVIDIA.

AMD at its 2025 Advancing AI event name-dropped its two next generations of EPYC server processors to succeed the current EPYC "Turin" powered by Zen 5 microarchitecture. 2026 will see AMD debut the Zen 6 microarchitecture, and its main workhorse for the server segment will be EPYC "Venice." This processor will likely see a generational increase in CPU core counts, increased IPC from the full-sized Zen 6 cores, support for newer ISA, and an updated I/O package. AMD is looking to pack "Venice" with up to 256 CPU cores per package.

AMD is looking to increase the CPU core count per CCD (CPU complex die) with "Zen 6." The company plans to build these CCDs on the 2 nm TSMC N2 process node. The sIOD (server I/O die) of "Venice" implements PCI-Express Gen 6 for a generational doubling in bandwidth to GPUs, SSDs, and NICs. AMD is also claiming memory bandwidth as high as 1.6 TB/s. There are a couple of ways they can go about achieving this, either by increasing the memory clock speeds, or giving the processor a 16-channel DDR5 memory interface, up from the current 12-channel DDR5. The company could also add support for multichannel DIMM standards, such as MR-DIMM and MCR-DIMMs. All said and done, AMD is claiming a 70% increase in multithreaded performance over the current EPYC "Turin," which we assume is comparing the highest performing part to its next-gen successor.

Giga Computing, a subsidiary of GIGABYTE and an industry leader in generative AI servers and advanced cooling technologies, today announced participation at AMD Advancing AI 2025 to join conversations with AI thought leaders and to share powerful GIGABYTE servers for AI innovations. This one-day event will be highlighted by the keynote from AMD's Dr. Lisa Su and afterwords attendees will join customer breakout sessions, workshops, and more, including discussions with the Giga Computing team.

At AMD Advancing AI Day, GIGABYTE servers demonstrate powerful solutions for AMD Instinct MI350X and MI355X GPUs. The new server platforms are highly efficient and compute dense, and the GIGABYTE G4L3 series exemplifies this with its support for direct liquid cooling (DLC) technology for the MI355X GPU. In traditional data centers without liquid cooling infrastructure, the GIGABYTE G893 Series provides a reliable air-cooled platform for the MI350X GPU. Together, these platforms showcase GIGABYTE's readiness to meet diverse deployment needs—whether maximizing performance with liquid cooling or ensuring broad compatibility in traditional air-cooled environments. With support for the latest AMD Instinct GPUs, GIGABYTE is driving the next wave of AI innovation.

At its "Advancing AI 2025" event, AMD rolled out its new Instinct MI350 lineup on the CDNA 4 architecture and teased the upcoming UDNA-based AI accelerator. True to its roughly one-year refresh rhythm, the company confirmed that the Instinct MI400 series will land in early 2026, showcasing a huge leap in memory, interconnect bandwidth, and raw compute power. Each MI400 card features twelve HBM4 stacks, providing a whopping 432 GB of on-package memory and pushing nearly 19.6 TB/s of memory bandwidth. Those early HBM4 modules deliver approximately 1.6 TB/s each, just shy of the 2 TB/s mark. On the compute front, AMD pegs the MI400 at 20 PetaFLOPS of FP8 throughput and 40 PetaFLOPS of FP4, doubling the sparse-matrix performance of today's MI355X cards. But the real game-changer is how AMD is scaling those GPUs. Until now, you could connect up to eight cards via Infinity Fabric, and anything beyond that had to go over Ethernet.

The MI400's upgraded fabric link now offers 300 GB/s, nearly twice the speed of the MI350 series, allowing you to build full-rack clusters without relying on slower networks. That upgrade paves the way for "Helios," AMD's fully integrated AI rack solution. It combines upcoming EPYC "Venice" CPUs with MI400 GPUs and trim-to-fit networking gear, offering a turnkey setup for data center operators. AMD didn't shy away from comparisons, either. A Helios rack with 72 MI400 cards delivers approximately 3.1 ExaFLOPS of tensor performance and 31 TB of HBM4 memory. NVIDIA's Vera Rubin system, slated to feature 72 GPUs and 288 GB of memory each, is expected to achieve around 3.6 ExaFLOPS, with AMD's capabilities surpassing it in both bandwidth and capacity. And if that's not enough, whispers of a beefed-up MI450X IF128 system are already swirling. Due in late 2026, it would directly link 128 GPUs with Infinity Fabric at 1.8 TB/s bidirectional per device, unlocking truly massive rack-scale AI clusters.

AMD today unveiled its Instinct MI350X series AI GPU. Based on the company's latest CDNA 4 compute architecture, the MI350X is designed to compete with NVIDIA B200 "Blackwell" AI GPU series, with the top-spec Instinct MI355X being compared by AMD to the B200 in its presentation. The chip debuts not just the CDNA 4 architecture, but also the latest ROCm 7 software stack, and hardware ecosystem based on the industry-standard Open Compute Project specification, which combines AMD EPYC Zen 5 CPUs, Instinct MI350 series GPUs, AMD-Pensando Pollara scale-out NICs supporting Ultra-Ethernet, and industry-standard racks and nodes, both in air- and liquid-cooled form-factors.

The MI350 is a gigantic chiplet-based AI GPU that consists of stacked silicon. There are two base tiles called I/O dies (IODs), each built on the 6 nm TSMC N6 process. This tile has microscopic wiring for up to four Accelerator Compute Die (XCD) tiles stacked on top, besides the 128-channel HBM3E memory controllers, 256 MB of Infinity Cache memory, the Infinity Fabric interfaces, and a PCI-Express 5.0 x16 root complex. The XCDs are built on the 3 nm TSMC N3P foundry node. These contain a 4 MB L2 cache, and four shader engines, each with 9 compute units. Each XCD hence has 36 CU, and each IOD seats 144 CU. Two IODs are joined at the hip by a 5.5 TB/s bidirectional interconnect that enables full cache coherency among the two IODs. The package has a total of 288 CU. Each IOD controls four HBM3E stacks for 144 GB of memory, the package has 288 GB.

As AI computing accelerates toward higher density and greater energy efficiency, Compal Electronics (Compal; Stock Ticker: 2324.TW), a global leader in IT and computing solutions, unveiled its latest high-performance server platform: SG720-2A/ OG720-2A at both AMD Advancing AI 2025 in the U.S. and the International Supercomputing Conference (ISC) 2025 in Europe. It features the AMD Instinct MI355X GPU architecture and offers both single-phase and two-phase liquid cooling configurations, showcasing Compal's leadership in thermal innovation and system integration. Tailored for next-generation generative AI and large language model (LLM) training, the SG720-2A/OG720-2A delivers exceptional flexibility and scalability for modern data center operations, drawing significant attention across the industry.

With generative AI and LLMs driving increasingly intensive compute demands, enterprises are placing greater emphasis on infrastructure that offers both performance and adaptability. The SG720-2A/OG720-2A emerges as a robust solution, combining high-density GPU integration and flexible liquid cooling options, positioning itself as an ideal platform for next-generation AI training and inference workloads.

AMD delivered its comprehensive, end-to-end integrated AI platform vision and introduced its open, scalable rack-scale AI infrastructure built on industry standards at its 2025 Advancing AI event.

AMD and its partners showcased:

• How they are building the open AI ecosystem with the new AMD Instinct MI350 Series accelerators
• The continued growth of the AMD ROCm ecosystem
• The company's powerful, new, open rack-scale designs and roadmap that bring leadership rack-scale AI performance beyond 2027

Tomorrow evening, AMD will host its "Advancing AI" livestream to introduce the Instinct MI350 series, a new line of GPU accelerators designed for large-scale AI training and inference. First shown in prototype form at ISC 2025 in Hamburg just a day ago, each MI350 card features 288 GB of HBM3E memory, delivering up to 8 TB/s of sustained bandwidth. Customers can choose between the single-card MI350X and the higher-clocked MI355X or opt for a full eight-GPU platform that aggregates to over 2.3 TB of memory. Both chips are built on the CDNA 4 architecture, which now supports four different precision formats: FP16, FP8, FP6, and FP4. The addition of FP6 and FP4 is designed to boost throughput in modern AI workloads, where models of tomorrow with tens of trillions of parameters are trained on FP6 and FP4.

In half-precision tests, the MI350X achieves 4.6 PetaFLOPS on its own and 36.8 PetaFLOPS in eight-GPU platform form, while the MI355X surpasses those numbers, reaching 5.03 PetaFLOPS and just over 40 PetaFLOPS. AMD is also aiming to improve energy efficiency by a factor of thirty compared with its previous generation. The MI350X card runs within a 1,000 Watt power envelope and relies on air cooling, whereas the MI355X steps up to 1,400 Watts and is intended for direct-liquid cooling setups. That 400 Watt increase puts it right at NVIDIA's upcoming GB300 "Grace Blackwell Ultra" superchip, which is also a 1,400 W design. With memory capacity, raw computing, and power efficiency all pushed to new heights, the question remains whether real-world benchmarks will match these ambitious specifications. AMD now only lacks platform scaling beyond eight GPUs, which the Instinct MI400 series will address.

AMD's Instinct MI355X accelerators for AI workloads are gaining traction, and Oracle just became one of the bigger customers. According to Oracle's latest financial results, the company noted that it had acquired 30,000 AMD Instinct MI355X accelerators. "In Q3, we signed a multi billion dollar contract with AMD to build a cluster of 30,000 of their latest MI355X GPUs," noted Larry Ellison, adding that "And all four of the leading cloud security companies, CrowdStrike, Cyber Reason, Newfold Digital and Palo Alto, they all decided to move to the Oracle Cloud. But perhaps most importantly, Oracle has developed a new product called the AI data platform that enables our huge install base of database customers to use the latest AI models from OpenAI, XAI and Meta to analyze all of the data they have stored in their millions of existing Oracle databases. By using Oracle version 23 AI's vector capabilities, customers can automatically put all of their existing data into the vector format that is understood by AI models. This allows those AI models to learn, understand and analyze every aspect of your company or government agency, instantly unlocking the value in your data while keeping your data private and secure."

AMD's Instinct MI355X accelerator introduces the CDNA4 architecture on TSMC's N3 process node with a focus on AI workload acceleration. The chiplet-based GPU delivers 2.3 petaflops of FP16 compute and 4.6 petaflops of FP8 compute, marking a 77% performance increase over the MI300X series. The MI355X's key advancement comes through support for reduced-precision FP4 and FP6 numerical formats, enabling up to 9.2 petaflops of FP4 compute. Memory specifications include 288 GB of HBM3E across eight stacks, providing 8 TB/s of total bandwidth. Production timelines place the MI355X's market entry in the second half of 2025, continuing AMD's annual cadence for data center GPU launches. By second half, Oracle will likely prepare data center space for these GPUs and just power them on once AMD ships these accelerators.