The NVIDIA GeForce RTX 5070 Ti graphics cards—built on the NVIDIA Blackwell architecture—are out now, ready to power generative AI content creation and accelerate creative performance. GeForce RTX 5070 Ti GPUs feature fifth-generation Tensor Cores with support for FP4, doubling performance and reducing VRAM requirements to run generative AI models.

In addition, the GPU comes equipped with two ninth-generation encoders and a sixth-generation decoder that add support for the 4:2:2 pro-grade color format and increase encoding quality for HEVC and AV1. This combo accelerates video editing workflows, reducing export times by 8x compared with single encoder GPUs without 4:2:2 support like the GeForce RTX 3090. The GeForce RTX 5070 Ti GPU also includes 16G B of fast GDDR7 memory and 896 GB/sec of total memory bandwidth—a 78% increase over the GeForce RTX 4070 Ti GPU.

In nearly every corner of our lives, the buzz about AI is impossible to ignore. It's destined to revolutionize how we work, learn, and play. For those of us immersed in the world of gaming—whether as players or creators—the question isn't just how AI will change the game, but how it will ignite new possibilities.

At Xbox, we're all about using AI to make things better (and more fun!) for players and game creators. We want to bring more games to more people around the world and always stay true to the creative vision and artistry of game developers. We believe generative AI can boost this creativity and open up new possibilities. We're excited to announce a generative AI breakthrough, published today in the journal Nature and announced by Microsoft Research, that shows this potential to open up new possibilities—including the opportunity to make older games accessible to future generations of players across new devices and in new ways.

New worlds await in the upcoming Sonic the Hedgehog racing game—Sonic Racing: CrossWorlds—introducing a unique gameplay mechanic transporting the iconic characters from the Sonic and Sega universes into new dimensions. The newest entry to the Sonic Racing series is a Sonic game, driving game, and action game all-in-one that will offer an exciting racing experience across several modes, worlds, and more! Sonic Racing: CrossWorlds is coming to PC and current generation consoles soon. Sega is sharing details on what players can expect to see in the game.

Travel Rings
Sonic Racing: CrossWorlds introduces Travel Rings, a new gameplay mechanic making each race feel surprising and fresh. Travel Rings bring dramatic changes to races, transporting players from one world to a completely new location. The lead racer gets to choose the CrossWorld that all players will be transported to on the second lap, allowing the environments to come alive with various track changes. Each CrossWorld offers a theme park-like experience with surprises around every turn, including large monsters, engaging obstacles, and tracks filled with beautiful scenery.

Moore Threads, a Chinese manufacturer of proprietary GPU designs is (reportedly) the latest company to jump onto the DeepSeek-R1 bandwagon. Since late January, NVIDIA, Microsoft and AMD have swooped in with their own interpretations/deployments. By global standards, Moore Threads GPUs trail behind Western-developed offerings—early 2024 evaluations presented the firm's MTT S80 dedicated desktop graphics card struggling against an AMD integrated solution: Radeon 760M. The recent emergence of DeepSeek's open source models has signalled a shift away from reliance on extremely powerful and expensive AI-crunching hardware (often accessed via the cloud)—widespread excitement has been generated by DeepSeek solutions being relatively frugal, in terms of processing requirements. Tom's Hardware has observed cases of open source AI models running (locally) on: "inexpensive hardware, like the Raspberry Pi."

According to recent Chinese press coverage, Moore Threads has announced a successful deployment of DeepSeek's R1-Distill-Qwen-7B distilled model on the aforementioned MTT S80 GPU. The company also revealed that it had taken similar steps with its MTT S4000 datacenter-oriented graphics hardware. On the subject of adaptation, a Moore Threads spokesperson stated: "based on the Ollama open source framework, Moore Threads completed the deployment of the DeepSeek-R1-Distill-Qwen-7B distillation model and demonstrated excellent performance in a variety of Chinese tasks, verifying the versatility and CUDA compatibility of Moore Threads' self-developed full-featured GPU." Exact performance figures, benchmark results and technical details were not disclosed to the Chinese public, so Moore Threads appears to be teasing the prowess of its MTT GPU designs. ITHome reported that: "users can also perform inference deployment of the DeepSeek-R1 distillation model based on MTT S80 and MTT S4000. Some users have previously completed the practice manually on MTT S80." Moore Threads believes that its: "self-developed high-performance inference engine, combined with software and hardware co-optimization technology, significantly improves the model's computing efficiency and resource utilization through customized operator acceleration and memory management. This engine not only supports the efficient operation of the DeepSeek distillation model, but also provides technical support for the deployment of more large-scale models in the future."

Advantech, a leader in embedded IoT computing solutions, is excited to introduce their AI-integrated desktop platform series: the Mini-ITX AIMB-2710 and Micro-ATX AIMB-589. These platforms are powered by Intel Core Ultra Processors (Series 2) S-Series, featuring the first desktop processor with an integrated NPU, delivering up to 36 TOPS for superior AI acceleration. Designed for data visualization and image analysis, both models offer PCIe Gen 5 support for high-performance GPU cards and feature 6400 MHz DDR5 memory, USB4 Type-C, multiple USB 3.2 Gen 2 and 2.5GbE LAN ports for fast and accurate data transmission in real time.

The AIMB-2710 and AIMB-589 excel in high-speed computing and AI-driven performance, making them ideal for applications such as medical imaging, automated optical inspection, and semiconductor testing. Backed by comprehensive software support, these platforms are engineered for the next wave of AI innovation.

Intel could be working on a new Arc graphics card according to Quantum Bits quoted by VideoCardz. It's based on the Battlemage architecture and has 24 GB of memory, twice as much as current models. This new card seems to be oriented more towards professionals, not gamers. Intel's Battlemage lineup currently has the Arc B580 model with 12 GB GDDR6 memory and a 192-bit bus. There's also the upcoming B570 with 10 GB and a 160-bit bus. The new 24 GB model will use the same BGM-G21 GPU as the B580, while the increased VRAM version could use higher capacity memory modules or a dual-sided module setup. No further technical details are available at this moment.

Intel looks to be aiming this 24 GB version at professional tasks such as artificial intelligence jobs like Large Language Models (LLMs) and generative AI. The card would be useful in data centers, edge computing, schools, and research, and this makes sense for Intel as they don't have a high-memory GPU for professional productivity markets yet. The company wants to launch this Arc Battlemage with bigger memory in 2025, we guess it might be announced in late spring or ahead of next year's Computex if there's no rush. Intel in the meantime will keep making their current gaming cards too as the latest Arc series was very well received, a big win for Intel after all the struggles. This rumor hints that Intel's expanding its GPU plan rather than letting it fade away, that was a gray scenario before the launch of Battlemage. Now it seems they want to compete in the professional and AI acceleration markets as well.

Axelera AI - a leading edge-inference company - and Arduino, the global leader in open-source hardware and software, today announced a strategic partnership to make high-performance AI at the edge more accessible than ever, building advanced technology solutions based on inference and an open ecosystem. This furthers Axelera AI's strategy to democratize artificial intelligence everywhere.

The collaboration will combine the strengths of Axelera AI's Metis AI Platform with the powerful SOMs from the Arduino Pro range to provide customers with easy-to-use hardware and software to innovate around AI. Users will enjoy the freedom to dictate their own AI journey, thanks to tools that provide unique digital in-memory computing and RISC-V controlled dataflow technology, delivering high performance and usability at a fraction of the cost and power of other solutions available today.

NVIDIA's RTX 5000 series GPU hardware has been leaked repeatedly in the weeks and months leading up to CES 2025, with previous leaks tipping significant updates for the RTX 5070 Ti in the VRAM department. Now, Inno3D is apparently hinting that the RTX 5000 series will also introduce updated machine learning and AI tools to NVIDIA's GPU line-up. An official CES 2025 teaser published by Inno3D, titled "Inno3D At CES 2025, See You In Las Vegas!" makes mention of potential updates to NVIDIA's AI acceleration suite for both gaming and productivity.

The Inno3D teaser specifically points out "Advanced DLSS Technology," "Enhanced Ray Tracing" with new RT cores, "better integration of AI in gaming and content creation," "AI-Enhanced Power Efficiency," AI-powered upscaling tech for content creators, and optimizations for generative AI tasks. All of this sounds like it builds off of previous NVIDIA technology, like RTX Video Super Resolution, although the mention of content creation suggests that it will be more capable than previous efforts, which were seemingly mostly consumer-focussed. Of course, improved RT cores in the new RTX 5000 GPUs is also expected, although it will seemingly be the first time NVIDIA will use AI to enhance power draw, suggesting that the CES announcement will come with new features for the NVIDIA App. The real standout feature, though, are called "Neural Rendering" and "Advanced DLSS," both of which are new nomenclatures. Of course, Advanced DLSS may simply be Inno3D marketing copy, but Neural Rendering suggests that NVIDIA will "Revolutionize how graphics are processed and displayed," which is about as vague as one could be.

Akeana, the company committed to driving dramatic change in semiconductor IP innovation and performance, has announced its official company launch approximately three years after its foundation, having raised over $100 million in capital, with support from A-list investors including Kleiner Perkins, Mayfield, and Fidelity. Today's launch marks the formal availability of the company's expansive line of IP solutions that are uniquely customizable for any workload or application.

Formed by the same team that designed Marvell's ThunderX2 server chips, Akeana offers a variety of IP solutions, including microcontrollers, Android clusters, AI vector cores and subsystems, and compute clusters for networking and data centers. Akeana moves the industry beyond the status quo of legacy vendors and architectures, like Arm, with equitable licensing options and processors that fill and exceed current performance gaps.

Ampere has announced a significant update to its product roadmap, highlighting the upcoming 512-core AmpereOne Aurora processor. This new chip is specifically designed to address the growing demands of cloud-native AI computing.

The newly announced AmpereOne Aurora 512 cores processor integrates AI acceleration and on-chip High Bandwidth Memory (HBM), promising three times the performance per rack compared to current AmpereOne processors. Aurora is designed to handle both AI training and inference workloads, indicating Ampere's commitment to becoming a major player in the AI computing space.

MaxLinear, Inc., a leading provider of data storage acceleration solutions for enterprise and data center applications, today announced it will demonstrate the advanced compression, encryption, and security performance of its storage acceleration solution, Panther III, at the Future of Memory and Storage (FMS) 2024 trade show from August 6-8, 2024. The demos will show that Panther III can achieve up to 40 times more throughput, up to 190 times better latency, and up to 1000 times less CPU utilization than a software-only solution, leading to significant cost savings in terms of flash drives and needed CPU cores.

MaxLinear's Panther III creates a bold new product category for maximizing the performance of data storage systems - a comprehensive, all-in-one "storage accelerator." Unlike encryption and/or compression solutions, MaxLinear's Panther III consolidates a comprehensive suite of storage acceleration functions, including compression, deduplication, encryption, data protection, and real-time validation, in a single hardware-based solution. Panther III is engineered to offload and expedite specific data processing tasks, thus providing a significant performance boost, storage cost savings, and energy savings compared to traditional software-only, FPGA, and other competitive solutions.

At Razer, we're continually pushing the boundaries of what's possible with gaming technology, and our latest software updates for Razer mice are set to redefine precision and adaptability for gamers everywhere. The new Mouse Rotation and Dynamic Sensitivity features are now available on Razer's latest esports mice - the Razer Viper V3 Pro, and Razer DeathAdder V3 HyperSpeed.

Mouse Rotation: Aligning Movement with Natural Motion
Mouse Rotation customizes the output angle from your mouse sensor to perfectly match your unique setup and grip style. This is especially beneficial for gamers who have a naturally angled swipe or an unconventional setup. By adjusting the angle in Synapse, users ensure that a left-to-right swipe on their desk corresponds directly to a horizontal movement in-game, enhancing both comfort and control.

At Computex 2024, ASUS unveiled major updates to its popular laptop lineups, designed for the "Copilot+" era of AI computing. The first is the Zenbook S16 is a premium 16-inch laptop series powered by AMD's latest Ryzen AI 9 HX 370 processors with dedicated AI acceleration. Remarkably, ASUS has managed to pack this high-performance silicon into an ultra-portable 1.1 cm thin chassis weighing just 1.5 kg. The Zenbook S16 integrates AMD's new NPU capable of a 50 TOPS of AI compute for accelerating AI/ML workloads. The centerpiece is the laptop's stunning 16-inch 3K OLED display made with ASUS Lumina technology. It offers 100% vibrant DCI-P3 color gamut coverage, a blazing-fast 120 Hz refresh rate with 0.2 ms response time, and up to 600 nits brightness. ASUS paired this premium visual experience with a six-speaker audio system for an immersive multimedia experience.

Today, in advance of ISC High Performance 2024, SpiNNcloud Systems announced the commercial availability of its SpiNNaker2 platform, a supercomputer-level hybrid AI high-performance computer system based on principles of the human brain. Pioneered by Steve Furber, designer of the original ARM and SpiNNaker1 architectures, the SpiNNaker2 supercomputing platform uses a large number of low-power processors for efficiently computing AI and other workloads.

First-generation SpiNNaker1 architecture is currently used in dozens of research groups across 23 countries worldwide. Sandia National Laboratories, Technical University of München and Universität Göttingen are among the first customers placing orders for SpiNNaker2, which was developed around commercialized IP invented in the Human Brain Project, a billion-euro research project funded by the European Union to design intelligent, efficient artificial systems.

Extropic, a pioneer in physics-based computing, this week emerged from stealth mode and announced the release of its Litepaper, which outlines the company's revolutionary approach to AI acceleration through thermodynamic computing. Founded in 2022 by Guillaume Verdon, Extropic has been developing novel chips and algorithms that leverage the natural properties of out-of-equilibrium thermodynamic systems to perform probabilistic computations for generative AI applications in a highly efficient manner. The Litepaper delves into Extropic's groundbreaking computational paradigm, which aims to address the limitations of current digital hardware in handling the complex probability distributions required for generative AI.

Today's algorithms spend around 25% of their time moving numbers around in memory, limiting the speedup achievable by accelerating specific operations. In contrast, Extropic's chips natively accelerate a broad class of probabilistic algorithms by running them physically as a rapid and energy-efficient, physics-based process in their entirety, unlocking a new regime of AI acceleration well beyond what was previously thought achievable. In coming out of stealth, the company has announced the fabrication of a superconducting prototype processor and developments surrounding room-temperature semiconductor-based devices for the broader market, with the goal of revolutionizing the field of AI acceleration and enabling new possibilities in generative AI.

Konstantin Seurer, a Mesa developer, has spent the past couple of months working on CPU-based Vulkan ray tracing—naturally, some folks will express scepticism about this project's practicality. Seurer has already set expectations with a brief message: "don't ask about performance." His GitLab merge request page attracted Michael Larabel's attention—the Phoronix founder and principal author was suitably impressed with Seurer's coding wizardry. He: "managed to implement support for VK_KHR_acceleration_structure, VK_KHR_deferred_host_operations, and VK_KHR_ray_query for Lavapipe. This Lavapipe Vulkan ray tracing support is based in part on porting code from the emulated ray tracing worked on for RADV with older Radeon GPUs." A lone screenshot provided evidence of Quake II running at 1 FPS with Vulkan ray tracing enabled—this "atrocious" performance was achieved thanks to a Mesa Lavapipe driver "implementing the Vulkan API for CPU-based execution."

VideoCardz has highlighted an older example of CPU-based rendering techniques: "this is not the first time we heard about ray tracing on the CPU in Quake. In 2008, Intel demonstrated Enemy Territory: Quake Wars running at 720p resolution at 14 to 29 FPS on 16 core and 20-35 FPS at 24 core CPUs (quad-socket). The basic implementation of ray tracing in 2008 is not comparable to complex ray tracing techniques designed for GPUs, thus the performance on modern system is actually much lower. Beyond that, that game was specifically designed for the Intel architecture and used a specific API to achieve that. Sadly, the original ET demo is no longer available, it would be interesting to see how it performs today." CPU-based Vulkan ray tracing is expected to hit public distribution channels with the rollout of Mesa 24.1. Several members of the Phoronix community reckon that modern AMD Threadripper PRO processors have the potential to post double-digit in-game frame rates.

Qualcomm Technologies, Inc. unveiled its latest advancements in artificial intelligence (AI) at Mobile World Congress (MWC) Barcelona. From the new Qualcomm AI Hub, to cutting-edge research breakthroughs and a display of commercial AI-enabled devices, Qualcomm Technologies is empowering developers and revolutionizing user experiences across a wide range of devices powered by Snapdragon and Qualcomm platforms.

"With Snapdragon 8 Gen 3 for smartphones and Snapdragon X Elite for PCs, we sparked commercialization of on-device AI at scale. Now with the Qualcomm AI Hub, we will empower developers to fully harness the potential of these cutting-edge technologies and create captivating AI-enabled apps," said Durga Malladi, senior vice president and general manager, technology planning and edge solutions, Qualcomm Technologies, Inc. "The Qualcomm AI Hub provides developers with a comprehensive AI model library to quickly and easily integrate pre-optimized AI models into their applications, leading to faster, more reliable and private user experiences."

Chad Pralle, Principle Technical Program Manager at Microsoft's Windows AI NPU division has introduced the DirectML 1.13.1 and ONNX Runtime 1.17 APIs—this appears to be a collaborative effort—Samsung was roped in to some degree, according to Microsoft's announcement and a recent Team Blue blog entry. Pralle and his team are suitably proud of this joint effort that involved open source models: "we are excited to announce developer preview support for NPU acceleration in DirectML, the machine learning platform API for Windows. This developer preview enables support for a subset of models on new Windows 11 devices with Intel Core Ultra processors with Intel AI boost."

Further on in Microsoft's introductory piece, Samsung Electronics is announced as a key launch partner—Hwang-Yoon Shim, VP and Head of New Computing H/W R&D Group stated that: "NPUs are emerging as a critical resource for broadly delivering efficient machine learning experiences to users, and Windows DirectML is one of the most efficient ways for Samsung's developers to make those experiences for Windows." Microsoft notes that NPU support in DirectML is still "a work in progress," but Pralle and his colleagues are eager to receive user feedback from the testing community. It is currently "only compatible with a subset of machine learning models, some models may not run at all or may have high latency or low accuracy." They hope to implement improvements in the near future. The release is limited to modern Team Blue hardware, so NPU-onboard AMD devices are excluded at this point in time, naturally.

Marvell Technology, a leader in data infrastructure semiconductor solutions, is enabling networking equipment and firewall manufacturers achieve breakthrough levels of performance and efficiency with two new OCTEON 10 data processing units (DPUs), the OCTEON 10 CN102 and OCTEON 10 CN103. The 5 nm OCTEON CN102 and CN103, broadly available to OEMs for product design and pilot production, are optimized for data and control plane applications in routers, firewalls, 5G small cells, SD-WAN appliances, and control plane applications in top-of-rack switches and line card controllers. Several of the world's largest networking equipment manufacturers have already incorporated the OCTEON 10 CN102 into a number of product designs.

Containing up to eight Arm Neoverse N2 cores, OCTEON 10 CN102 and CN103 deliver 3x the performance of Marvell current DPU solutions for devices while reducing power consumption by 50% to 25 W. Achieving SPEC CPU (2017) integer rate (SPECint) scores of 36.5, OCTEON 10 CN102 and CN103 are able to deliver nearly 1.5 SPECint points per Watt. The chips can serve as an offload DPU for host processors or as the primary processor in devices; advanced performance per watt also enables OEMs to design fanless systems to simplify systems and further reduce cost, maintenance and power consumption.

Thanks to the leaked slides obtained by @InstLatX64, we have more details and some performance estimates about Intel's upcoming 5th Generation Xeon "Emerald Rapids" CPUs, boasting a significant performance leap over its predecessors. Leading the Emerald Rapids family is the top-end SKU, the Xeon 8592+, which features 64 cores and 128 threads, backed by a massive 480 MB L3 cache pool. The upcoming lineup shifts from a 4-tile to a 2-tile design to minimize latency and improve performance. The design utilizes the P-Core architecture under the Raptor Cove ISA and promises up to 40% faster performance than the current 4th Generation "Sapphire Rapids" CPUs in AI applications utilizing Intel AMX engine. Each chiplet has 35 cores, three of which are disabled, and each tile has two DDR5-5600 MT/s memory controllers, which operate two memory channels each and translating that into eight-channel design. There are three PCIe controllers per die, making it six in total.

Newer protocols and AI accelerators also back the upcoming lineup. Now, the Emerald Rapids family supports the Compute Express Link (CXL) Types 1/2/3 in addition to up to 80 PCIe Gen 5 lanes and enhanced Intel Ultra Path Interconnect (UPI). There are four UPI controllers spread over two dies. Moreover, features like the four on-die Intel Accelerator Engines, optimized power mode, and up to 17% improvement in general-purpose workloads make it seem like a big step up from the current generation. Much of this technology is found on the existing Sapphire Rapids SKUs, with the new generation enhancing the AI processing capability further. You can see the die configuration below. The 5th Generation Emerald Rapids designs are supposed to be official on December 14th, just a few days away.

During its Ignite conference, Microsoft introduced a duo of custom-designed silicon made to accelerate AI and excel in cloud workloads. First of the two is Microsoft's Azure Cobalt 100 CPU, a 128-core design that features a 64-bit Armv9 instruction set, implemented in a cloud-native design that is set to become a part of Microsoft's offerings. While there aren't many details regarding the configuration, the company claims that the performance target is up to 40% when compared to the current generation of Arm servers running on Azure cloud. The SoC has used Arm's Neoverse CSS platform customized for Microsoft, with presumably Arm Neoverse N2 cores.

The next and hottest topic in the server space is AI acceleration, which is needed for running today's large language models. Microsoft hosts OpenAI's ChatGPT, Microsoft's Copilot, and many other AI services. To help make them run as fast as possible, Microsoft's project Athena now has the name of Maia 100 AI accelerator, which is manufactured on TSMC's 5 nm process. It features 105 billion transistors and supports various MX data formats, even those smaller than 8-bit bit, for maximum performance. Currently tested on GPT 3.5 Turbo, we have yet to see performance figures and comparisons with competing hardware from NVIDIA, like H100/H200 and AMD, with MI300X. The Maia 100 has an aggregate bandwidth of 4.8 Terabits per accelerator, which uses a custom Ethernet-based networking protocol for scaling. These chips are expected to appear in Microsoft data centers early next year, and we hope to get some performance numbers soon.

CyberLink, a leader in digital creative editing software and artificial intelligence (AI), attended the Intel Innovation Taipei 2023. As a long-standing Intel independent software vendor (ISV) partner, CyberLink demonstrated how its latest generative AI technology is used for easily creating amazing photo and video content with tools such as: AI Business Outfits, AI Product Background, and AI Video to Anime. During the forum, CyberLink Chairman and CEO Jau Huang shared how Intel's upcoming AI PC is expected to benefit content creators by popularizing generative AI creativity from cloud computing to personal computers, to not only reduce the cost of AI computing but, simultaneously eliminate users' privacy concerns, fostering an entirely new AI content creation experience where it's even easier to unleash creativity with generative AI.

The Intel Innovation Taipei was kicked off by Intel CEO Pat Gelsinger. The event highlighted four major themes: artificial intelligence, edge to cloud, next-generation systems and platforms, and advance technologies, as well as the latest results of cooperation with Taiwan ecosystem partners, including the latest AI PCs, etc.

Supermicro, Inc., a Total IT Solution Provider for AI, Cloud, Storage, and 5G/Edge, is expanding its AI reach with the upcoming support for the new NVIDIA HGX H200 built with H200 Tensor Core GPUs. Supermicro's industry leading AI platforms, including 8U and 4U Universal GPU Systems, are drop-in ready for the HGX H200 8-GPU, 4-GPU, and with nearly 2x capacity and 1.4x higher bandwidth HBM3e memory compared to the NVIDIA H100 Tensor Core GPU. In addition, the broadest portfolio of Supermicro NVIDIA MGX systems supports the upcoming NVIDIA Grace Hopper Superchip with HBM3e memory. With unprecedented performance, scalability, and reliability, Supermicro's rack scale AI solutions accelerate the performance of computationally intensive generative AI, large language Model (LLM) training, and HPC applications while meeting the evolving demands of growing model sizes. Using the building block architecture, Supermicro can quickly bring new technology to market, enabling customers to become more productive sooner.

Supermicro is also introducing the industry's highest density server with NVIDIA HGX H100 8-GPUs systems in a liquid cooled 4U system, utilizing the latest Supermicro liquid cooling solution. The industry's most compact high performance GPU server enables data center operators to reduce footprints and energy costs while offering the highest performance AI training capacity available in a single rack. With the highest density GPU systems, organizations can reduce their TCO by leveraging cutting-edge liquid cooling solutions.

Building on the AI PC use cases shared at Innovation 2023, Intel today launched the AI PC Acceleration Program, a global innovation initiative designed to accelerate the pace of AI development across the PC industry.

The program aims to connect independent hardware vendors (IHVs) and independent software vendors (ISVs) with Intel resources that include AI toolchains, co-engineering, hardware, design resources, technical expertise and co-marketing opportunities. These resources will help the ecosystem take full advantage of Intel Core Ultra processor technologies and corresponding hardware to maximize AI and machine learning (ML) application performance, accelerate new use cases and connect the wider PC industry to the solutions emerging in the AI PC ecosystem. More information is available on the AI PC Acceleration Program website.

Generative AI is one of the most important trends in the history of personal computing, bringing advancements to gaming, creativity, video, productivity, development and more. And GeForce RTX and NVIDIA RTX GPUs, which are packed with dedicated AI processors called Tensor Cores, are bringing the power of generative AI natively to more than 100 million Windows PCs and workstations.

Today, generative AI on PC is getting up to 4x faster via TensorRT-LLM for Windows, an open-source library that accelerates inference performance for the latest AI large language models, like Llama 2 and Code Llama. This follows the announcement of TensorRT-LLM for data centers last month. NVIDIA has also released tools to help developers accelerate their LLMs, including scripts that optimize custom models with TensorRT-LLM, TensorRT-optimized open-source models and a developer reference project that showcases both the speed and quality of LLM responses.