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    “We Created a Processor for the Generative AI Era,” NVIDIA CEO Says

    UHQBot
    By UHQBot,

    Generative AI promises to revolutionize every industry it touches — all that’s been needed is the technology to meet the challenge.

    NVIDIA CEO Jensen Huang on Monday introduced that technology—the company’s new Blackwell computing platform—as he outlined the major advances that increased computing power can deliver for everything from software to services, robotics to medical technology, and more.

    “Accelerated computing has reached the tipping point — general purpose computing has run out of steam,” Huang told more than 11,000 GTC attendees gathered in-person — and many tens of thousands more online — for his keynote address at Silicon Valley’s cavernous SAP Center arena.

    “We need another way of doing computing — so that we can continue to scale so that we can continue to drive down the cost of computing, so that we can continue to consume more and more computing while being sustainable. Accelerated computing is a dramatic speedup over general purpose computing, in every single industry.”

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    Huang spoke in front of massive images on a 40-foot tall, 8k screen the size of a tennis court to a crowd packed with CEOs and developers, AI enthusiasts and entrepreneurs, who walked together 20 minutes to the arena from the San Jose Convention Center on a dazzling spring day.

    Delivering a massive upgrade to the world’s AI infrastructure, Huang introduced the NVIDIA Blackwell platform to unleash real-time generative AI on trillion-parameter large language models.

    Huang presented NVIDIA NIM — a reference to NVIDIA inference microservices — a new way of packaging and delivering software that connects developers with hundreds of millions of GPUs to deploy custom AI of all kinds.

    And bringing AI into the physical world, Huang introduced Omniverse Cloud APIs to deliver advanced simulation capabilities.

    Huang punctuated these major announcements with powerful demos, partnerships with some of the world’s largest enterprises, and more than a score of announcements detailing his vision.

    GTC — which in 15 years has grown from the confines of a local hotel ballroom to the world’s most important AI conference — is returning to a physical event for the first time in five years.

    This year’s has over 900 sessions — including a panel discussion on transformers moderated by Huang with the eight pioneers who first developed the technology, more than 300 exhibits, and 20-plus technical workshops.

    It’s an event that’s at the intersection of AI and just about everything. In a stunning opening act to the keynote, Refik Anadol, the world’s leading AI artist, showed a massive real-time AI data sculpture with wave-like swirls in greens, blues, yellows and reds, crashing, twisting and unraveling across the screen.

    As he kicked off his talk, Huang explained that the rise of multi-modal AI — able to process diverse data types handled by different models — gives AI greater adaptability and power. By increasing their parameters, these models can handle more complex analyses.

    But this also means a significant rise in the need for computing power. And as these collaborative, multi-modal systems become more intricate — with as many as a trillion parameters — the demand for advanced computing infrastructure intensifies.

    “We need even larger models,” Huang said. “We’re going to train it with multimodality data, not just text on the internet, we’re going to train it on texts and images, graphs and charts, and just as we learned watching TV  there’s going to be a whole bunch of watching video.”

    The Next Generation of Accelerated Computing

    In short, Huang said “we need bigger GPUs.” The Blackwell platform is built to meet this challenge. Huang pulled a Blackwell chip out of his pocket and held it up side-by-side with a Hopper chip, which it dwarfed.

    Named for David Harold Blackwell — a University of California, Berkeley mathematician specializing in game theory and statistics, and the first Black scholar inducted into the National Academy of Sciences — the new architecture succeeds the NVIDIA Hopper architecture, launched two years ago.

    Blackwell delivers 2.5x its predecessor’s performance in FP8 for training, per chip, and 5x with FP4 for inference. It features a fifth-generation NVLINK interconnect that’s twice as fast as Hopper and scales up to 576 GPUs.

    And the NVIDIA GB200 Grace Blackwell Superchip connects two Blackwell NVIDIA B200 Tensor Core GPUs to the NVIDIA Grace CPU over a 900GB/s ultra-low-power NVLink chip-to-chip interconnect.

    Huang held up a board with the system. “This computer is the first of its kind where this much computing fits into this small of a space,: Huang said. “Since this is memory coherent they feel like it’s one big happy family working on one application together.”

    For the highest AI performance, GB200-powered systems can be connected with the NVIDIA Quantum-X800 InfiniBand and Spectrum-X800 Ethernet platforms, also announced today, which deliver advanced networking at speeds up to 800Gb/s.

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    “The amount of energy we save, the amount of networking bandwidth we save, the amount of wasted time we save, will be tremendous,” Huang said. “The future is generative…which is why this is a brand new industry. The way we compute is fundamentally different. We created a processor for the generative AI era.”

    To scale up Blackwell, NVIDIA built a new chip called NVLINK Switch. Each  can connect four NVLinks at 1.8 terabytes per second and eliminate traffic by doing in-network reduction.

    NVIDIA Switch and GB200 are key components of what Huang described as “one giant GPU,” the NVIDIA GB200 NVL72, a multi-node, liquid-cooled, rack-scale system that harnesses Blackwell to offer supercharged compute for trillion-parameter models, with 720 petaflops of AI training performance and 1.4 exaflops of AI inference performance in a single rack.

    “There are only a couple, maybe three exaflop machines on the planet as we speak,” Huang said of the machine, which packs 600,000 parts and weighs 3,000 pounds. “And so this is an exaflop AI system in one single rack. Well let’s take a look at the back of it.”

    Going even bigger, NVIDIA today also announced its next-generation AI supercomputer — the NVIDIA DGX SuperPOD powered by NVIDIA GB200 Grace Blackwell Superchips — for processing trillion-parameter models with constant uptime for superscale generative AI training and inference workloads.

    Featuring a new, highly efficient, liquid-cooled rack-scale architecture, the new DGX SuperPOD is built with NVIDIA DG GB200 systems and provides 11.5 exaflops of AI supercomputing at FP4 precision and 240 terabytes of fast memory — scaling to more with additional racks.

    “In the future, data centers are going to be thought of…as AI factories,” Huang said. “Their goal in life is to generate revenues, in this case, intelligence.”

    The industry has already embraced Blackwell.

    The press release announcing Blackwell includes endorsements from Alphabet and Google CEO Sundar Pichai, Amazon CEO Andy Jassy, Dell CEO Michael Dell, Google DeepMind CEO Demis Hassabis, Meta CEO Mark Zuckerberg, Microsoft CEO Satya Nadella, OpenAI CEO Sam Altman, Oracle Chairman Larry Ellison, and Tesla and xAI CEO Elon Musk.

    Blackwell is being adopted by every major global cloud services provider,  pioneering AI companies, system and server vendors, and regional cloud service providers and telcos all around the world.

    “The whole industry is gearing up for Blackwell,” which Huang said would be the most successful launch in the company’s history.

    A New Way to Create Software

    Generative AI changes the way applications are written, Huang said.

    Rather than writing software, he explained, companies will assemble AI models, give them missions, give examples of work products, review plans and intermediate results.

    These packages — NVIDIA NIMs, a reference to NVIDIA inference microservices — are built from NVIDIA’s accelerated computing libraries and generative AI models, Huang explained.

    “How do we build software in the future? It is unlikely that you’ll write it from scratch or write a whole bunch of Python code or anything like that,” Huang said. “It is very likely that you assemble a team of AIs.”

    The microservices support industry-standard APIs so they are easy to connect, work across NVIDIA’s large CUDA installed base, are re-optimized for new GPUs, and are constantly scanned for security vulnerabilities and exposures.

    Huang said customers can use NIM microservices off-the-shelf, or NVIDIA can help build proprietary AI and co-pilots, teaching a model specialized skills only your company would know to create invaluable new services.

    “The enterprise IT industry is sitting on a goldmine,” Huang said. “They have all these amazing tools (and data) that have been created over the years. If they could take that goldmine and turn it into copilots, these copilots can help us do things.”

    Major tech players are already putting it to work. Huang detailed how NVIDIA is already helping Cohesity, NetApp, SAP, ServiceNow, and Snowflake build co-pilots and virtual assistants. And industries are stepping in, as well.

    In telecoms, Huang announced the NVIDIA 6G research cloud, a generative AI and Omniverse-powered platform to advance the next communications era. It’s built with NVIDIA’s Sionna neural radio framework, NVIDIA Aerial CUDA-accelerated radio access network and the NVIDIA Aerial Omniverse Digital Twin for 6G.

    In semiconductor design and manufacturing, Huang announced that, in collaboration with TSMC and Synopsys, NVIDIA is bringing its breakthrough computational lithography platform, cuLitho, to production. This platform will accelerate the most compute-intensive workload in semiconductor manufacturing by 40-60x.

    Huang also announced the NVIDIA Earth Climate Digital Twin. The cloud platform — available now — enables interactive, high-resolution simulation to accelerate climate and weather prediction.

    The greatest impact of AI will be in healthcare, Huang said, explaining that NVIDIA is already in imaging systems, in gene sequencing instruments and working with leading surgical robotics companies.

    NVIDIA is launching a new type of biology software. NVIDIA today launched more than two dozen new microservices that allow healthcare enterprises worldwide to take advantage of the latest advances in generative AI from anywhere and on any cloud. They offer advanced imaging, natural language and speech recognition, and digital biology generation, prediction and simulation.

    Omniverse Brings AI to the Physical World

    The next wave of AI will be AI learning about the physical world, Huang said.

    “We need a simulation engine that represents the world digitally for the robot so that the robot has a gym to go learn how to be a robot,” he said. “We call that virtual world Omniverse.”

    That’s why NVIDIA today announced that NVIDIA Omniverse Cloud will be available as APIs, extending the reach of the world’s leading platform for creating industrial digital twin applications and workflows across the entire ecosystem of software makers.

    The five new Omniverse Cloud application programming interfaces enable developers to easily integrate core Omniverse technologies directly into existing design and automation software applications for digital twins, or their simulation workflows for testing and validating autonomous machines like robots or self-driving vehicles.

    To show how this works, Huang shared a demo of a robotic warehouse — using multi-camera perception and tracking — watching over workers and orchestrating robotic forklifts, which are driving autonomously with the full robotic stack running.

    Hang also announced that NVIDIA is bringing Omniverse to Apple Vision Pro, with the new Omniverse Cloud APIs letting developers stream interactive industrial digital twins into the VR headsets.

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    Some of the world’s largest industrial software makers are embracing Omniverse Cloud APIs, including Ansys, Cadence, Dassault Systèmes for its 3DEXCITE brand, Hexagon, Microsoft, Rockwell Automation, Siemens and Trimble.

    Robotics

    Everything that moves will be robotic, Huang said. The automotive industry will be a big part of that, NVIDIA computers are already in cars, trucks, delivery bots and robotaxis.

    Huang announced that BYD, the world’s largest AV company, has selected NVIDIA’s next-generation computer for their AV, building its next-generation EV fleets on DRIVE Thor.

    To help robots better see their environment, Huang also announced the Isaac Perceptor software development kit with state-of-the-art multi-camera visual odometry, 3D reconstruction and occupancy map, and depth perception.

    And to help make manipulators, or robotic arms, more adaptable, NVIDIA is announcing Isaac Manipulator — a state-of-the-art robotic arm perception, path planning and kinematic control library.
    Finally, Huang announced Project GR00T, a general-purpose foundation model for humanoid robots, designed to further the company’s work driving breakthroughs in robotics and embodied AI.

    Supporting that effort, Huang unveiled a new computer, Jetson Thor, for humanoid robots based on the NVIDIA Thor system-on-a-chip and significant upgrades to the NVIDIA Isaac robotics platform.

    In his closing minutes, Huang brought on stage a pair of diminutive NVIDIA-powered robots from Disney Research.

    “The soul of NVDIA — the intersection of computer graphics, physics, artificial intelligence,” he said.“It all came to bear at this moment.”

    View the full article


    All Aboard: NVIDIA Scores 23 World Records for Route Optimization

    UHQBot
    By UHQBot,

    With nearly two dozen world records to its name, NVIDIA cuOpt now holds the top spot for 100% of the largest routing benchmarks in the last three years. And this means the route optimization engine allows industries to hop on board for all kinds of cost-saving efficiencies.

    Kawasaki Heavy Industries and SyncTwin are among the companies that are riding cuOpt for logistics improvements.

    Today at GTC 2024, NVIDIA founder and CEO Jensen Huang announced that cuOpt is moving into general availability.

    “With cuOpt, NVIDIA is reinventing logistics management and operations research. It is NVIDIA’s pre-quantum computer, driving transformational operational efficiencies for deliveries, service calls, warehouses and factories, and supply chains,” he said.

    The NVIDIA cuOpt microservice, part of the NVIDIA AI Enterprise software platform, makes accelerated optimization for real-time dynamic rerouting, factory optimization and robotic simulations available to any organization.

    Companies can embed cuOpt into the advanced 3D tools, applications and USD-based workflows they develop with NVIDIA Omniverse, a software platform for developing and deploying advanced 3D applications and pipelines based on OpenUSD.

    Implemented together, cuOpt, Omniverse and NVIDIA Metropolis for Factories can help optimize and create safe environments in logistics-heavy facilities that rely on complex automation, precise material flow and human-robot interaction, such as automotive factories, semiconductor fabs and warehouses.

    cuOpt has been continuously tested against the best-known solutions on the most studied benchmarks for route optimization, with results up to 100x faster than CPU-based implementations. With 15 records from the Gehring & Homberger vehicle routing benchmark and eight from the Li & Lim pickup and delivery benchmark, cuOpt has demonstrated the world’s best accuracy with the fastest times.

    AI promises to deliver logistics efficiencies spanning from transportation networks to manufacturing and much more.

    Delivering Cost-Savings for Inspections With cuOpt

    Kawasaki Heavy Industries is a manufacturing company that’s been building large machinery for more than a hundred years. The Japanese company partnered with Slalom and used cuOpt to create routing efficiencies for the development of its AI-driven Kawasaki Track Maintenance Platform.

    Railroad track maintenance is getting an AI makeover worldwide. Traditionally, track inspections and maintenance are time-consuming and difficult to manage to keep trains running on time. But track maintenance is critical for safety and transportation service. Railway companies are automating track inspections with AI and machine learning paired with digital cameras, lasers and gyrometric sensors.

    Kawasaki is harnessing the edge computing of NVIDIA Jetson AGX Orin to develop track inspections on its Track Maintenance Platform for running onboard trains. The platform enables customers to improve vision models with the data collected on tracks for advances in the inspection capability of the edge-based AI system.

    The platform provides maintenance teams data on track conditions that allows them to prioritize repairs, creating increased safety and reliability of operations.

    According to Kawasaki, it’s estimated that such an AI-driven system can save $218 million a year for seven companies from automating their track inspections.

    Creating Manufacturing Efficiencies With cuOpt and Omniverse

    A worldwide leader in automotive seating manufacturing has adopted SyncTwin’s digital twin capability, which is driven by Omniverse and cuOpt, to improve its operations with AI.

    The global automotive seating manufacturer has a vast network of loading docks for the delivery of raw materials, and forklifts for unloading and transporting them to storage and handling areas to ensure a steady supply to production lines. SyncTwin’s connection to cuOpt delivers routing efficiencies that optimize all of these moving parts — from vehicles to robotic pallet jacks.

    As the SyncTwin solution was developed on top of Omniverse and USD, manufacturers can ensure that their various factory planning tools can contribute to the creation of a rich digital twin environment. Plus, they eliminate tedious manual data collection and gain new insights from their previously disconnected data.

    Attend GTC to explore how cuOpt is achieving world-record accuracy and performance to solve complex problems. Learn more about cuOpt world records in our tech blog. Learn more about Omniverse.

    View the full article


    All Eyes on AI: Automotive Tech on Full Display at GTC 2024

    UHQBot
    By UHQBot,

    All eyes across the auto industry are on GTC — the global AI conference running in San Jose, Calif., and online through Thursday, March 21 — as the world’s top automakers and tech leaders converge to showcase the latest models, demo new technologies and dive into the remarkable innovations reshaping the sector.

    Attendees will experience how generative AI and software-defined computing are advancing the automotive landscape and transforming the behind-the-wheel experience to become safer, smarter and more enjoyable.

    Automakers Adopting NVIDIA DRIVE Thor

    NVIDIA founder and CEO Jensen Huang kicked off GTC with a keynote address in which he revealed that NVIDIA DRIVE Thor, which combines advanced driver assistance technology and in-vehicle infotainment, now features the newly announced NVIDIA Blackwell GPU architecture for transformer and generative AI workloads.

    Following the keynote, top EV makers shared how they will integrate DRIVE Thor into their vehicles. BYD, the world’s largest electric vehicle maker, is expanding its ongoing collaboration with NVIDIA and building its next-generation EV fleets on DRIVE Thor. Hyper, a premium luxury brand owned by GAC AION, is announcing it has selected DRIVE Thor for its new models, which will begin production in 2025. XPENG will use DRIVE Thor as the AI brain of its next-generation EV fleets. These EV makers join Li Auto and ZEEKR, which previously announced they’re building their future vehicle roadmaps on DRIVE Thor.

    Additionally, trucking, robotaxis and goods delivery vehicle makers are announcing support for DRIVE Thor. Nuro is choosing DRIVE Thor to power the Nuro Driver. Plus is announcing that future generations of its level 4 solution, SuperDrive, will run on DRIVE Thor. Waabi is  leveraging DRIVE Thor to deliver the first generative AI-powered autonomous trucking solution to market. WeRide, in cooperation with tier 1 partner Lenovo Vehicle Computing, is creating level 4 autonomous driving solutions for commercial applications built on DRIVE Thor.

    And, DeepRoute.ai is unveiling its new smart driving architecture powered by NVIDIA DRIVE Thor, scheduled to launch next year.

    Next-Generation Tech on the Show Floor

    The GTC exhibit hall is buzzing with excitement as companies showcase the newest vehicle models and offer technology demonstrations.

    Attendees have the opportunity to see firsthand the latest NVIDIA-powered vehicles on display,  including Lucid Air, Mercedes-Benz Concept CLA Class, Nuro R3, Polestar 3, Volvo EX90, WeRide Robobus, and an Aurora truck. The Lucid Air is available for test drives during the week.

    A wide array of companies are showcasing innovative automotive technology at GTC, including Foretellix, Luminar and MediaTek, which is launching its Dimensity Auto Cockpit chipsets at the show. The new solutions harness NVIDIA’s graphics and AI technologies to help deliver state-of-the-art in-vehicle user experiences, added safety and security capabilities.

    Also Announced at GTC: Omniverse Cloud APIs, Generative AI

    • Omniverse Cloud APIs, announced today at NVIDIA GTC, are poised to accelerate the path to autonomy by enabling high-fidelity sensor simulation for AV development and validation. Developers and software vendors such as CARLA, MathWorks, MITRE, Foretellix and Voxel51 underscore the broad appeal of these APIs in autonomous vehicles.
    • Generative AI developers including Cerence, Geely, Li Auto, NIO, SoundHound, Tata Consulting Services and Wayve announced plans to transform the in-vehicle experience by using NVIDIA’s cloud-to-edge technology to help develop intelligent AI assistants, driver and passenger monitoring, scene understanding and more.

    AI and Automotive Sessions Available Live and on Demand

    Throughout the week, the world’s foremost experts on automotive technology will lead a broad array of sessions and panels at GTC, including:

    On DRIVE Developer Day, taking place Thursday, March 21, NVIDIA’s engineering experts will highlight the latest DRIVE features and developments through a series of deep-dive sessions on how to build safe and robust self-driving systems.

    See the full schedule of automotive programming at GTC and be sure to tune in.

    View the full article


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