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In his first live keynote since the pandemic, NVIDIA founder and CEO Jensen Huang today kicked off the COMPUTEX conference in Taipei, announcing platforms that companies can use to ride a historic wave of generative AI that’s transforming industries from advertising to manufacturing to telecom. “We’re back,” Huang roared as he took the stage after years of virtual keynotes, some from his home kitchen. “I haven’t given a public speech in almost four years — wish me luck!” Speaking for nearly two hours to a packed house of some 3,500, he described accelerated computing services, software and systems that are enabling new business models and making current ones more efficient. “Accelerated computing and AI mark a reinvention of computing,” said Huang, whose travels in his hometown over the past week have been tracked daily by local media. In a demonstration of its power, he used the massive 8K wall he spoke in front of to show a text prompt generating a theme song for his keynote, singable as any karaoke tune. Huang, who occasionally bantered with the crowd in his native Taiwanese, briefly led the audience in singing the new anthem. “We’re now at the tipping point of a new computing era with accelerated computing and AI that’s been embraced by almost every computing and cloud company in the world,” he said, noting 40,000 large companies and 15,000 startups now use NVIDIA technologies with 25 million downloads of CUDA software last year alone. Top News Announcements From the Keynote Grace Hopper powers big-memory supercomputers for gen AI. Modular reference architecture enables 100+ accelerated server configurations. WPP, NVIDIA create digital ad content engine in Omniverse. SoftBank, NVIDIA build 5G, gen AI data centers in Japan. Networking technology accelerates Ethernet-based AI clouds. NVIDIA ACE for Games breathes life into characters with gen AI. Electronics manufacturers worldwide embrace NVIDIA AI. A New Engine for Enterprise AI For enterprises that need the ultimate in AI performance, he unveiled DGX GH200, a large-memory AI supercomputer. It uses NVIDIA NVLink to combine up to 256 NVIDIA GH200 Grace Hopper Superchips into a single data-center-sized GPU. The GH200 Superchip, which Jensen said is now in full production, combines an energy-efficient NVIDIA Grace CPU with a high-performance NVIDIA H100 Tensor Core GPU in one superchip. The DGX GH200 packs an exaflop of performance and 144 terabytes of shared memory, nearly 500x more than in a single NVIDIA DGX A100 320GB system. That lets developers build large language models for generative AI chatbots, complex algorithms for recommender systems, and graph neural networks used for fraud detection and data analytics. Google Cloud, Meta and Microsoft are among the first expected to gain access to the DGX GH200, which can be used as a blueprint for future hyperscale generative AI infrastructure. NVIDIA’s DGX GH200 AI supercomputer delivers 1 exaflop of performance for generative AI. “DGX GH200 AI supercomputers integrate NVIDIA’s most advanced accelerated computing and networking technologies to expand the frontier of AI,” Huang told the audience in Taipei, many of whom had lined up outside the hall for hours before the doors opened. NVIDIA is building its own massive AI supercomputer, NVIDIA Helios, coming online this year. It will use four DGX GH200 systems linked with NVIDIA Quantum-2 InfiniBand networking to supercharge data throughput for training large AI models. The DGX GH200 forms the pinnacle of hundreds of systems announced at the event. Together, they’re bringing generative AI and accelerated computing to millions of users. Zooming out to the big picture, Huang announced more than 400 system configurations are coming to market powered by NVIDIA’s latest Hopper, Grace, Ada Lovelace and BlueField architectures. They aim to tackle the most complex challenges in AI, data science and high performance computing. Acceleration in Every Size To fit the needs of data centers of every size, Huang announced NVIDIA MGX, a modular reference architecture for creating accelerated servers. System makers will use it to quickly and cost-effectively build more than a hundred different server configurations to suit a wide range of AI, HPC and NVIDIA Omniverse applications. MGX lets manufacturers build CPU and accelerated servers using a common architecture and modular components. It supports NVIDIA’s full line of GPUs, CPUs, data processing units (DPUs) and network adapters as well as x86 and Arm processors across a variety of air- and liquid-cooled chassis. QCT and Supermicro will be the first to market with MGX designs appearing in August. Supermicro’s ARS-221GL-NR system announced at COMPUTEX will use the Grace CPU, while QCT’s S74G-2U system, also announced at the event, uses Grace Hopper. ASRock Rack, ASUS, GIGABYTE and Pegatron will also use MGX to create next-generation accelerated computers. 5G/6G Calls for Grace Hopper Separately, Huang said NVIDIA is helping shape future 5G and 6G wireless and video communications. A demo showed how AI running on Grace Hopper will transform today’s 2D video calls into more lifelike 3D experiences, providing an amazing sense of presence. Laying the groundwork for new kinds of services, Huang announced NVIDIA is working with telecom giant SoftBank to build a distributed network of data centers in Japan. It will deliver 5G services and generative AI applications on a common cloud platform. The data centers will use NVIDIA GH200 Superchips and NVIDIA BlueField-3 DPUs in modular MGX systems as well as NVIDIA Spectrum Ethernet switches to deliver the highly precise timing the 5G protocol requires. The platform will reduce cost by increasing spectral efficiency while reducing energy consumption. The systems will help SoftBank explore 5G applications in autonomous driving, AI factories, augmented and virtual reality, computer vision and digital twins. Future uses could even include 3D video conferencing and holographic communications. Turbocharging Cloud Networks Separately, Huang unveiled NVIDIA Spectrum-X, a networking platform purpose-built to improve the performance and efficiency of Ethernet-based AI clouds. It combines Spectrum-4 Ethernet switches with BlueField-3 DPUs and software to deliver 1.7x gains in AI performance and power efficiency over traditional Ethernet fabrics. NVIDIA Spectrum-X, Spectrum-4 switches and BlueField-3 DPUs are available now from system makers including Dell Technologies, Lenovo and Supermicro. NVIDIA Spectrum-X accelerates AI workflows that can experience performance losses on traditional Ethernet networks. Bringing Game Characters to Life Generative AI impacts how people play, too. Huang announced NVIDIA Avatar Cloud Engine (ACE) for Games, a foundry service developers can use to build and deploy custom AI models for speech, conversation and animation. It will give non-playable characters conversational skills so they can respond to questions with lifelike personalities that evolve. NVIDIA ACE for Games includes AI foundation models such as NVIDIA Riva to detect and transcribe the player’s speech. The text prompts NVIDIA NeMo to generate customized responses animated with NVIDIA Omniverse Audio2Face. NVIDIA ACE for Games provides a tool chain for bringing characters to life with generative AI. Accelerating Gen AI on Windows Huang described how NVIDIA and Microsoft are collaborating to drive innovation for Windows PCs in the generative AI era. New and enhanced tools, frameworks and drivers are making it easier for PC developers to develop and deploy AI. For example, the Microsoft Olive toolchain for optimizing and deploying GPU-accelerated AI models and new graphics drivers will boost DirectML performance on Windows PCs with NVIDIA GPUs. The collaboration will enhance and extend an installed base of 100 million PCs sporting RTX GPUs with Tensor Cores that boost performance of more than 400 AI-accelerated Windows apps and games. Digitizing the World’s Largest Industries Generative AI is also spawning new opportunities in the $700 billion digital advertising industry. For example, WPP, the world’s largest marketing services organization, is working with NVIDIA to build a first-of-its kind generative AI-enabled content engine on Omniverse Cloud. In a demo, Huang showed how creative teams will connect their 3D design tools such as Adobe Substance 3D, to build digital twins of client products in NVIDIA Omniverse. Then, content from generative AI tools trained on responsibly sourced data and built with NVIDIA Picasso will let them quickly produce virtual sets. WPP clients can then use the complete scene to generate a host of ads, videos and 3D experiences for global markets and users to experience on any web device. “Today ads are retrieved, but in the future when you engage information much of it will be generated — the computing model has changed,” Huang said. Factories Forge an AI Future With an estimated 10 million factories, the $46 trillion manufacturing sector is a rich field for industrial digitalization. “The world’s largest industries make physical things. Building them digitally first can save billions,” said Huang. The keynote showed how electronics makers including Foxconn Industrial Internet, Innodisk, Pegatron, Quanta and Wistron are forging digital workflows with NVIDIA technologies to realize the vision of an entirely digital smart factory. They’re using Omniverse and generative AI APIs to connect their design and manufacturing tools so they can build digital twins of factories. In addition, they use NVIDIA Isaac Sim for simulating and testing robots and NVIDIA Metropolis, a vision AI framework, for automated optical inspection. The latest component, NVIDIA Metropolis for Factories, can create custom quality-control systems, giving manufacturers a competitive advantage. It’s helping companies develop state-of-the-art AI applications. AI Speeds Assembly Lines For example, Pegatron — which makes 300 products worldwide, including laptops and smartphones — is creating virtual factories with Omniverse, Isaac Sim and Metropolis. That lets it try out processes in a simulated environment, saving time and cost. Pegatron also used the NVIDIA DeepStream software development kit to develop intelligent video applications that led to a 10x improvement in throughput. Foxconn Industrial Internet, a service arm of the world’s largest technology manufacturer, is working with NVIDIA Metropolis partners to automate significant portions of its circuit-board quality-assurance inspection points. Crowds lined up for the keynote hours before doors opened. In a video, Huang showed how Techman Robot, a subsidiary of Quanta, tapped NVIDIA Isaac Sim to optimize inspection on the Taiwan-based giant’s manufacturing lines. It’s essentially using simulated robots to train robots how to make better robots. In addition, Huang announced a new platform to enable the next generation of autonomous mobile robot (AMR) fleets. Isaac AMR helps simulate, deploy and manage fleets of autonomous mobile robots. A large partner ecosystem — including ADLINK, Aetina, Deloitte, Quantiphi and Siemens — is helping bring all these manufacturing solutions to market, Huang said. It’s one more example of how NVIDIA is helping companies feel the benefits of generative AI with accelerated computing. “It’s been a long time since I’ve seen you, so I had a lot to tell you,” he said after the two-hour talk to enthusiastic applause. To learn more, watch the full keynote. View the full article

As mobile robot shipments surge to meet the growing demands of industries seeking operational efficiencies, NVIDIA is launching a new platform to enable the next generation of autonomous mobile robot (AMR) fleets. Isaac AMR brings advanced mapping, autonomy and simulation to mobile robots and will soon be available for early customers, NVIDIA founder and CEO Jensen Huang announced during his keynote address at the COMPUTEX technology conference in Taipei. Isaac AMR is a platform to simulate, validate, deploy, optimize and manage fleets of autonomous mobile robots. It includes edge-to-cloud software services, computing and a set of reference sensors and robot hardware to accelerate development and deployment of AMRs, reducing costs and time to market. Mobile robot shipments are expected to climb from 251,000 units in 2023 to 1.6 million by 2028, with revenue forecast to jump from $12.6 billion to $64.5 billion in the period, according to ABI Research. Simplifying the Path to Autonomy Despite the explosive adoption of robots, the intralogistics industry faces challenges. Traditionally, software applications for autonomous navigation are often coded from scratch for each robot, making rolling out autonomy across different robots complex. Also, warehouses, factories and fulfillment centers are enormous, frequently running a million square feet or more, making them hard to map for robots and keep updated. And integrating AMRs into existing workflows, fleet management and warehouse management systems can be complicated. For those working in advanced robotics and seeking to migrate traditional forklifts or automated guided vehicles to fully autonomous mobile robots, Isaac AMR provides the blueprint to accelerate the migration to full autonomy, reducing costs and speeding deployment of state-of-the-art AMRs. Orin-Based Reference Architecture Isaac AMR is built on the foundations of the NVIDIA Nova Orin reference architecture. Nova Orin is the brains and eyes of Isaac AMR. It integrates multiple sensors including stereo cameras, fisheye cameras, 2D and 3D lidars with the powerful NVIDIA Jetson AGX Orin system-on-module. The reference robot hardware comes with Nova Orin pre-integrated, making it easy for developers to evaluate Isaac AMR in their own environments. The compute engine of Nova is Orin, which delivers access to some of the most advanced AI and hardware-accelerated algorithms that can be run using 275 tera operations per second (TOPS) of edge computing in real time. The synchronized and calibrated sensor suite offers sensor diversity and redundancy for real-time 3D perception and mapping. Cloud-native tools for record, upload and replay enable easy debugging, map creation, training and analytics. Isaac AMR: Mapping, Autonomy, Simulation Isaac AMR offers a foundation for mapping, autonomy and simulation. Isaac AMR accelerates mapping and semantic understanding of large environments by tying into DeepMap’s cloud-based service to help accelerate robot mapping of large facilities from weeks to days, offering centimeter-level accuracy without the need for a highly skilled team of technicians. It can generate rich 3D voxel maps, which can be used to create occupancy maps and semantic maps for multiple types of AMRs. Additionally, Isaac AMR shortens the time to develop and deploy robots in large, highly dynamic and unstructured environments with autonomy that’s enabled by multimodal navigation with cloud-based fleet optimization using NVIDIA cuOpt software. An accelerated and modular framework enables real-time camera and lidar perception. Planning and control using advanced path planners, behavior planners and use of semantic information make the robot operate autonomously in complex environments. A low-code, no-code interface makes it easy to rapidly develop and customize applications for different scenarios and use cases. Finally, Isaac AMR simplifies robot operations by tapping into physics-based simulation from Isaac Sim, powered by NVIDIA Omniverse, an open development platform for industrial digitalization. This can bring digital twins to life, so the robot application can be developed, tested and customized for each customer before deploying in the physical world. This significantly reduces the operational cost and complexity of deploying AMRs. Sign up for early access to Isaac AMR. View the full article

How do you help robots build better robots? By simulating even more robots. NVIDIA founder and CEO Jensen Huang today showcased how leading electronics manufacturer Quanta is using AI-enabled robots to inspect the quality of its products. In his keynote speech at this week’s COMPUTEX trade show in Taipei, Huang presented on how electronics manufacturers are digitalizing their state-of-the art factories. For example, robots from Quanta subsidiary Techman Robot tapped NVIDIA Isaac Sim — a robotics simulation application built on NVIDIA Omniverse — to develop a custom digital twin application to improve inspection on the Taiwan-based electronics provider’s manufacturing line. The below demo shows how Techman uses Isaac Sim to optimize the inspection of robots by robots on the manufacturing line. In effect, it’s robots building robots. Automated optical inspection, or AOI, helps manufacturers more quickly identify defects and deliver high-quality products to their customers around the globe. The NVIDIA Metropolis vision AI framework, now enabled for AOI, is also used to optimize inspection workflows for products ranging from automobiles to circuit boards. Techman developed AOI with its factory-floor robots by using Isaac Sim to simulate, test and optimize its state-of-the-art collaborative robots, or cobots, while using NVIDIA AI and GPUs for training in the cloud and inference on the robots themselves. Isaac Sim is built on NVIDIA Omniverse — an open development platform for building and operating industrial metaverse applications. Unique features of Techman’s robotic AOI solutions include their placement of the inspection camera directly on articulated robotic arms and GPUs integrated in the robot controller. This allows the bots to inspect areas of products that fixed cameras simply can’t access, as well as use AI at the edge to instantly detect defects. “The distinctive features of Techman’s robots — compared to other robot brands — lie in their built-in vision system and AI inference engine,” said Scott Huang, chief operations officer at Techman. “NVIDIA RTX GPUs power up their AI performance.” But programming the movement of these robots can be time consuming. A developer has to determine the precise arm positions, as well as the most efficient sequence, to capture potentially hundreds of images as quickly as possible. This can involve several days of effort, exploring tens of thousands of possibilities to determine an optimal solution. The solution: robot simulation. Using Omniverse, Techman built a digital twin of the inspection robot — as well as the product to be inspected — in Isaac Sim. Programming the robot in simulation reduced time spent on the task by over 70%, compared to programming manually on the real robot. Using an accurate 3D model of the product, the application can be developed in the digital twin even before the real product is manufactured, saving valuable time on the production line. Then, with powerful optimization tools in Isaac Sim, Techman explored a massive number of program options in parallel on NVIDIA GPUs. The end result was an efficient solution that reduced the cycle time of each inspection by 20%, according to Huang. Every second saved in inspection time will drop down to the bottom line of Techman’s manufacturing customers. Gathering and labeling real-world images of defects is costly and time consuming, so Techman turned to synthetic data to improve the quality of inspections. It used the Omniverse Replicator framework to quickly generate high-quality synthetic datasets. These perfectly labeled images are used to train the AI models in the cloud and dramatically enhance their performance. And dozens of AI models can be run at the edge — efficiently and with low latency thanks to NVIDIA technology — while inspecting particularly complicated products, some of which take more than 40 models to scrutinize their different aspects. Learn more about how Isaac Sim on Omniverse, Metropolis and AI are streamlining the optical inspection process across products and industries by joining NVIDIA at COMPUTEX, where the Techman cobots will be on display. View the full article

The $46 trillion global electronics manufacturing industry spans more than 10 million factories worldwide, where much is at stake in producing defect-free products. To drive product excellence, leading electronics manufacturers are adopting NVIDIA Metropolis for Factories. More than 50 manufacturing giants and industrial automation providers — including Foxconn Industrial Internet, Pegatron, Quanta, Siemens and Wistron — are implementing Metropolis for Factories, NVIDIA founder and CEO Jensen Huang announced during his keynote address at the COMPUTEX technology conference in Taipei. NVIDIA Metropolis for Factories is a collection of factory automation workflows that enables industrial technology companies and manufacturers to develop, deploy and manage customized quality-control systems that offer a competitive advantage. Manufacturers globally spend more than $6 trillion a year in pursuit of quality control, and they apply defect detection on nearly every product line. But manual inspections can’t keep up with the demands. Many manufacturers have automated optical inspection (AOI) systems that can help, but often these have high false detection rates, requiring labor-intensive and costly secondary manual inspections in an already challenging labor market, reducing their value. NVIDIA Metropolis for Factories now offers a state-of-the-art AI platform and workflows for the development of incredibly accurate inspection applications such as AOI. Pegatron Drives AOI With Metropolis for Factories Leading manufacturer Pegatron, based in Taipei’s Beitou district, is using NVIDIA Metropolis for Factories on its production lines. Pegatron manufactures everything from motherboards to smartphones, laptops and game consoles. With a dozen manufacturing facilities handling more than 300 products and more than 5,000 parts per day, Pegatron has a lot of quality control to manage across its product portfolio. Further, frequent product updates require ongoing revisions to its AOI systems. Pegatron is using the entire Metropolis for Factories workflow to support its printed circuit board (PCB) factories with simulation, robotics and automated production inspection. Metropolis for Factories enables the electronics manufacturing giant to quickly update its defect detection models and achieve 99.8% accuracy on its AOI systems, starting with small datasets. Pegatron uses NVIDIA Isaac Sim, a robotic simulator, to program robotic arms in simulation and to model the performance of its fleets of mobile robots. Tapping into NVIDIA Omniverse Replicator provides synthetic data generation to simulate defects, helping build massive training datasets with domain randomization and other techniques. In Metropolis, NVIDIA TAO Toolkit allows Pegatron to access pretrained models and transfer learning to build its highly accurate defect detection models from its enhanced datasets. The NVIDIA DeepStream software development kit can be used to develop optimized intelligent video applications that handle multiple video, image and audio streams. Using DeepStream, Pegatron was able to achieve a 10x improvement in throughput. Moreover, Omniverse enables Pegatron to run digital twins of its inspection equipment, so it can simulate future inspection processes, promising increased efficiencies to its production workflow. It’s also used by Quanta subsidiary Techman Robot, which taps Isaac Sim to optimize the inspection of robots by robots on their manufacturing line. Metropolis for Factories is helping manufacturers like Pegatron to increase production line throughput, reduce costs and improve production quality. Growing Partner Ecosystem Supports Metropolis Metropolis for Factories can be deployed from the enterprise industrial edge to the cloud, and a large and growing ecosystem of partners is helping bring it to market. A host of specialists are joining forces on this effort including sensor makers, application partners, inspection equipment makers and integration partners. Basler, a leading maker of imaging sensors and systems, has partnered with NVIDIA to help developers build AI-enabled inspection systems faster through tighter integration with the NVIDIA DeepStream SDK. Quantiphi, a Metropolis partner, is working with one of the world’s largest beverage producers to automate inspections of fully packed pallets with GPU-powered vision AI. Overview and Advantech — both NVIDIA Metropolis partners — are collaborating to build a real-time AI-based inspection system to support industrial inspection, product counting and assembly verification. Metropolis partners Siemens and Data Monsters are working together to build industrial inspection systems, bringing together Omniverse Replicator synthetic data generation, NVIDIA TAO training, DeepStream runtime and Siemens’ NVIDIA Jetson-powered industrial personal computers. Learn more about NVIDIA Metropolis for Factories. View the full article

Generative AI is rapidly ushering in a new era of computing for productivity, content creation, gaming and more. Generative AI models and applications — like NVIDIA NeMo and DLSS 3 Frame Generation, Meta LLaMa, ChatGPT, Adobe Firefly and Stable Diffusion — use neural networks to identify patterns and structures within existing data to generate new and original content. When optimized for GeForce RTX and NVIDIA RTX GPUs, which offer up to 1,400 Tensor TFLOPS for AI inferencing, generative AI models can run up to 5x faster than on competing devices. This is thanks to Tensor Cores — dedicated hardware in RTX GPUs built to accelerate AI calculations — and regular software improvements. Enhancements introduced last week at the Microsoft Build conference doubled performance for generative AI models, such as Stable Diffusion, that take advantage of new DirectML optimizations. As more AI inferencing happens on local devices, PCs will need powerful yet efficient hardware to support these complex tasks. To meet this need, RTX GPUs will add Max-Q low-power inferencing for AI workloads. The GPU will operate at a fraction of the power for lighter inferencing tasks, while scaling up to unmatched levels of performance for heavy generative AI workloads. To create new AI applications, developers can now access a complete RTX-accelerated AI development stack running on Windows 11, making it easier to develop, train and deploy advanced AI models. This starts with development and fine-tuning of models with optimized deep learning frameworks available via Windows Subsystem for Linux. Developers can then move seamlessly to the cloud to train on the same NVIDIA AI stack, which is available from every major cloud service provider. Next, developers can optimize the trained models for fast inferencing with tools like the new Microsoft Olive. And finally, they can deploy their AI-enabled applications and features to an install base of over 100 million RTX PCs and workstations that have been optimized for AI. “AI will be the single largest driver of innovation for Windows customers in the coming years,” said Pavan Davuluri, corporate vice president of Windows silicon and system integration at Microsoft. “By working in concert with NVIDIA on hardware and software optimizations, we’re equipping developers with a transformative, high-performance, easy-to-deploy experience.” To date, over 400 RTX AI-accelerated apps and games have been released, with more on the way. During his keynote address kicking off COMPUTEX 2023, NVIDIA founder and CEO Jensen Huang introduced a new generative AI to support game development, NVIDIA Avatar Cloud Engine (ACE) for Games. This custom AI model foundry service transforms games by bringing intelligence to non-playable characters through AI-powered natural language interactions. Developers of middleware, tools and games can use ACE for Games to build and deploy customized speech, conversation and animation AI models in their software and games. Generative AI on RTX, Anywhere From servers to the cloud to devices, generative AI running on RTX GPUs is everywhere. NVIDIA’s accelerated AI computing is a low-latency, full-stack endeavor. We’ve been optimizing every part of our hardware and software architecture for many years for AI, including fourth-generation Tensor Cores — dedicated AI hardware on RTX GPUs. Regular driver optimizations ensure peak performance. The most recent NVIDIA driver, combined with Olive-optimized models and updates to DirectML, delivers significant speedups for developers on Windows 11. For example, Stable Diffusion performance is improved by 2x compared to the previous interference times for developers taking advantage of DirectML optimized paths. And with the latest generation of RTX laptops and mobile workstations built on the NVIDIA Ada Lovelace architecture, users can take generative AI anywhere. Our next-gen mobile platform brings new levels of performance and portability — in form factors as small as 14 inches and as lightweight as about three pounds. Makers like Dell, HP, Lenovo and ASUS are pushing the generative AI era forward, backed by RTX GPUs and Tensor Cores. “As AI continues to get deployed across industries at an expected annual growth rate of over 37% now through 2030, businesses and consumers will increasingly need the right technology to develop and implement AI, including generative AI. Lenovo is uniquely positioned to empower generative AI spanning from devices to servers to the cloud, having developed products and solutions for AI workloads for years. Our NVIDIA RTX GPU-powered PCs, such as select Lenovo ThinkPad, ThinkStation, ThinkBook, Yoga, Legion and LOQ devices, are enabling the transformative wave of generative AI for better everyday user experiences in saving time, creating content, getting work done, gaming and more.” — Daryl Cromer, vice president and chief technology officer of PCs and Smart Devices at Lenovo “Generative AI is transformative and a catalyst for future innovation across industries. Together, HP and NVIDIA equip developers with incredible performance, mobility and the reliability needed to run accelerated AI models today, while powering a new era of generative AI.” — Jim Nottingham, senior vice president and general manager of Z by HP “Our recent work with NVIDIA on Project Helix centers on making it easier for enterprises to build and deploy trustworthy generative AI on premises. Another step in this historic moment is bringing generative AI to PCs. Think of app developers looking to perfect neural network algorithms while keeping training data and IP under local control. This is what our powerful and scalable Precision workstations with NVIDIA RTX GPUs are designed to do. And as the global leader in workstations, Dell is uniquely positioned to help users securely accelerate AI applications from the edge to the datacenter.” — Ed Ward, president of the client product group at Dell Technologies “The generative AI era is upon us, requiring immense processing and fully optimized hardware and software. With the NVIDIA AI platform, including NVIDIA Omniverse, which is now preinstalled on many of our products, we are excited to see the AI revolution continue to take shape on ASUS and ROG laptops.” — Galip Fu, director of global consumer marketing at ASUS Soon, laptops and mobile workstations with RTX GPUs will get the best of both worlds. AI inference-only workloads will be optimized for Tensor Core performance while keeping power consumption of the GPU as low as possible, extending battery life and maintaining a cool, quiet system. The GPU can then dynamically scale up for maximum AI performance when the workload demands it. Developers can also learn how to optimize their applications end-to-end to take full advantage of GPU-acceleration via the NVIDIA AI for accelerating applications developer site. View the full article

Valve removed the Steam listing for Dolphin, a popular emulator for the GameCube and Wii, after it received a cease and desist from Nintendo, developers behind the project claim. The company behind Mario and Zelda accuses the emulator of illegally circumventing its protections, and says it’s merely protecting the… Read more... View the full article

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“You are running for food, or you are running from becoming food. And often times, you can’t tell which. Either way, run.” NVIDIA founder and CEO Jensen Huang today urged graduates of National Taiwan University to run hard to seize the unprecedented opportunities that AI will present, but embrace the inevitable failures along the way. Whatever you pursue, he told the 10,000 graduates of the island’s premier university, do it with passion and conviction — and stay humble enough to learn the hard lessons that await. “Whatever it is, run after it like we did. Run. Don’t walk,” Huang said, having swapped his signature black leather jacket for a black graduation robe, with the school’s plum-blossom emblem highlighting a royal blue, white and aqua collar. “Remember, either you are running for food; or you are running from becoming food. And often times, you can’t tell which. Either way, run.” Huang, who moved from Taiwan when he was young, recognized his parents in the audience, and shared three stories of initial failures and retreat. He called them instrumental in helping forge NVIDIA’s character during its three-decade journey from a three-person gaming-graphics startup to a global AI leader worth nearly a trillion dollars. “I was … successful — until I started NVIDIA,” he said. “At NVIDIA, I experienced failures — great big ones. All humiliating and embarrassing. Many nearly doomed us.” The first involved a key early contract the company won to help Sega build a gaming console. Rapid changes in the industry forced NVIDIA to give up the contract in a near-death brush with bankruptcy, which Sega’s leadership helped avert. “Confronting our mistake and, with humility, asking for help saved NVIDIA,” he said. The second was the decision in 2007 to put CUDA into all the company’s GPUs, enabling them to crunch data in addition to handling 3D graphics. It was an expensive, long-term investment that drew much criticism didn’t pay off for years until the chips started being used for machine learning. “Our market cap hovered just above a billion dollars,” he recalled. “We suffered many years of poor performance. Our shareholders were skeptical of CUDA and preferred we improve profitability.” The third was the decision in 2010 to charge into the promising mobile-phone market as graphics-rich capabilities were coming into reach. The market quickly commoditized, though, and NVIDIA retreated just as quickly, taking initial heat but opening the door to investing in promising new markets — robotics and self-driving cars. “Our strategic retreat paid off,” he said. “By leaving the phone market, we opened our minds to invent a new one.” Huang told grads that of the parallels in terms of boundless promise between the world he entered upon graduating four decades ago, on the cusp of the PC revolution, and the brave new age of AI they are entering today. “For your journey, take along some of my learnings,” he said. Admit mistakes and ask for help; endure pain and suffering to realize your dreams; and make sacrifices to dedicate yourself to a life of purpose. View the full article

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Rarely do I watch a trailer for a video game more than once. Yet with Bungie’s Marathon reboot/sequel/whatever, I’ve found myself looping its slick and stylish announcement trailer. It’s not just because the trailer slaps, but because Bungie is teasing looks to be one of the coolest shooters released in years. Read more... View the full article

With a game as expansive and malleable as Tears of the Kingdom, there are countless ways to solve puzzles, traverse the environment, defeat your enemies, or just have fun. As the game’s been out now just a couple of weeks, players are still discovering unique contraptions, and one that’s swiftly growing in popularity… Read more... View the full article

The official reveal of a Metal Gear Solid 3 remake was one of the headliners of Sony’s recent PlayStation 5 showcase, but it likely won’t be finished for some time. Fortunately, a collection of Metal Gear classics is coming to modern platforms this fall and it will actually include more games than originally expected. Read more... View the full article

The Outlast Trials is excessively nasty and obscene—appropriate, considering it’s developer Red Barrels’ first follow up in six years to its, in the best way, abhorrent Outlast survival horror series. Since its Early Access release on May 18, the blood-drenched multiplayer has been sliding up the Steam charts, making… Read more... View the full article

Artificial Intelligence is everywhere, from software like the language processor ChatGPT and the image generator DALL-E to AI chatbots—and now, even Twitch streamers are starting to take notice. Kaitlyn “Amouranth” Siragusa, one of the platform’s biggest stars with over 6.4 million followers, recently dropped her own… Read more... View the full article

A new glitch in Destiny 2’s Season of the Deep makes it easy to farm infinite Legendary Shards through unlimited Exotic drops. It’s super simple and easy and probably won’t be around for long. Read more... View the full article

The Last of Us’ long-awaited multiplayer game was notably absent at the PlayStation Showcase on Wednesday, and now we know why: Naughty Dog says it’s not ready for show. Read more... View the full article

Esports company turned Wall Street laughing stock, FaZe Clan, is at the center of another controversy as its members fight over the recent signing of Stranger Things actor and Twitch streamer, Grace Van Dien. Loud members like Nordan “FaZe Rain” Shat criticized the signing as a money grab, while Van Dien said Rain… Read more... View the full article

Hello Cornelio, Welcome to UnityHQ Nolfseries Community. Please feel free to browse around and get to know the others. If you have any questions please don't hesitate to ask. Cornelio joined on the 05/26/2023. View Member

On May 24, PlayStation held its first large-scale showcase since 2021. While it had some cool games, it was lacking the big and wild exclusives the company has historically put out. However, most would agree that the finale—a large gameplay preview of the upcoming, PS5-exclusive Spider-Man 2—was an impressive end for… Read more... View the full article

Well folks, Marathon is coming back. What do you mean you don’t know what that is? It’s only Bungie’s seminal series of first-person shooters everyone was playing on their Power Macintoshes and Pippins in the 1990s. Where even were you? It’s why Steve Jobs was so elated to first announce Halo for the Mac…before that… Read more... View the full article

When I saw the Super Mario Bros. Movie, the one moment I lost it in the theater was when Jack Black’s Bowser sang his piano-driven ballad “Peaches” midway through the movie. It was silly, pathetic, and hella catchy. This past week, a school audience got to relive that moment when a kid performed the song at a talent… Read more... View the full article

Once again, Link starts his journey scarcely clothed in The Legend of Zelda: Tears of the Kingdom. While there are a few clothing items near where Link starts out in the massive tutorial area, along with an OP shield, I was hoping for a specific item early on. I’m talking about the Champion’s Tunic, which you can use… Read more... View the full article