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PlayStation Store welcomes an all-new promotion, starting August 27. For a limited time*, Ready, Set, Play will offer a vast selection of games, including blockbuster franchises, acclaimed indies and standalone greats, at discount. The question then is, where do you start? We’re here to help you with the answer. Browse a selection of games on offer below, then when the promotion goes live, head to PlayStation Store to discover your regional discount. A Fisherman’s Tale 2 A Plague Tale: Innocence Abyss Odyssey: Extended Dream Edition AC Mirage + Valhalla Bundle Actraiser Renaissance Ad Infinitum – Nightmare Edition AEW: Fight Forever – Ultimate Edition After the Fall After the Fall (PSVR2 standard edition) Age of Empires II: Definitive Edition Premium Edition Age of Mythology: Retold Alan Wake 2 Deluxe Edition Alba: A Wildlife Adventure Alien: Isolation – The Collection Aliens: Dark Descent Alone in the Dark – Digital Deluxe Edition AO Tennis 2 Arizona Sunshine® Remake Arkane Collection PS5 Assassin’s Creed III Remastered Assassin’s Creed IV: Black Flag Assassin’s Creed Odyssey – Deluxe Edition Assassin’s Creed Odyssey – Gold Edition Assassin’s Creed Origins – Deluxe Edition Assassin’s Creed Origins – Season Pass Astria Ascending Atomic Heart – Premium Edition Atomic Heart – Standard Edition Attractio Avatar: Frontiers of Pandora Deluxe Edition Avatar: Frontiers of Pandora Gold Edition Away: Journey to the Unexpected Balatro Banishers: Ghosts of New Eden Barbie Project Friendship™ Batman: Arkham VR Call of Duty: Advanced Warfare – Digital Pro Edition (Day Zero) Call of Duty: Black Ops 4 Call of Duty: Black Ops III – Zombies Chronicles Edition Call of Duty: Infinite Warfare – Digital Deluxe Edition Call of Duty: WWII – Digital Deluxe Call of Duty®: Modern Warfare® Capcom Collab Pack Captain Tsubasa: Rise of New Champions – Deluxe Edition Car Mechanic Simulator 2021 DLC MegaPack Caravan Sandwitch Cassiodora Children of Morta Children of Zodiarcs Chroma Squad Chronos: Before the Ashes Cobra Kai 2: Dojos Rising – Nemesis Edition College Football 26 Deluxe Edition Commandos 2 & Commandos 3 – Bundle Digital Commandos: Origins – Deluxe Edition CONSCRIPT CRISIS CORE –FINAL FANTASY VII– REUNION DIGITAL DELUXE EDITION Cult of the Lamb Cyberpunk 2077 CYGNI: All Guns Blazing Dead Island 2 Main Game Dead Rising 4: Frank’s Big Package Dead Space Death Stranding Director’s Cut DEATHLOOP (GAME) Deliver At All Costs Demon’s Souls Destiny 2: Year of Prophecy Edition Destroy All Humans! 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2 Tropico 5 Tropico 5 – Complete Collection Upgrade Pack Tropico 6 – Next Gen Edition TT Isle Of Man 3 – Racing Fan Edition TT Isle of Man: Ride on the Edge Type:Rider UFC® 5 PS5 Umbrella Corps Umbrella Corps – Deluxe Edition Underworld Ascendant Unheard – Voices of Crime Unknown 9 Uno – Standard Edition Cross-buy Unturned Valkyria Chronicles Remastered Vanguard – Cross-Gen Edition Vanguard – PS5 Cross-Gen Edition Vernal Edge Voice of Cards Trilogy + DLC set Voice of Cards: The Beast of Burden ＋ DLC set Voice of Cards: The Isle Dragon Roars + DLC set V-Rally 4 – Ultimate Edition War Hospital Warhammer 40,000: Inquisitor – Martyr: Complete Collection Warhammer 40,000: Space Marine 2 Warhammer Ultimate Pack: Hack and Slash Warhammer: Chaosbane Warhammer: Chaosbane Slayer Edition Welcome to ParadiZe – Zombot Edition Werewolf: The Apocalypse – Earthblood Werewolf: The Apocalypse – Earthblood Champion of Gaia Wild Hearts Karakuri Edition Bundle Wildshade: Unicorn Champions Wolfenstein: Resistance Bundle Wolfenstein: Youngblood – Deluxe Edition Worms Rumble PS4 & PS5 WRC 2023 (PS5) WRC 9 FIA World Rally Championship PS4 WRC 9 FIA World Rally Championship PS5 WRC Generations – The FIA WRC Official Game Yakuza Complete Collection Yakuza: Like a Dragon Legendary Hero Edition Yakuza: Like a Dragon Legendary Hero Edition PS4 & PS5 Yakuza: Like a Dragon PS4 & PS5 Zombie Army Trilogy Zone of the Enders: The 2nd Runner – Mars *Ready Set Play promotion is live on PlayStation Store from Wednesday, August 27 at 00:00 AM PDT/BST/JST and finishes Wednesday September 10 at 11:59 PM PDT/BST/JST.

Le stand Amazon Web Services à la Hannover Messe, l’une des plus grandes foires industrielles du monde, à Hanovre, en Allemagne, le 30 mars 2025. FABIAN BIMMER / REUTERS L’Assemblée générale de l’Organisation des Nations unies (ONU) a créé, mardi 26 août, un groupe d’experts scientifiques sur l’intelligence artificielle (IA) qui sera chargé d’aider la communauté internationale à prendre des décisions informées sur ce sujet sensible, comme le fait le Groupe d’experts intergouvernemental sur l’évolution du climat (GIEC). S’inquiétant du développement rapide de technologies révolutionnaires qui pourraient menacer la démocratie et les droits humains, les Etats membres de l’ONU s’étaient engagés, en septembre 2024, dans le « Pacte pour l’avenir », à mettre en place un tel groupe d’experts pour éclairer le dialogue international entre gouvernements et autres acteurs du secteur. Dans une résolution adoptée mardi, l’Assemblée générale a formellement créé ce « Groupe scientifique international indépendant de l’intelligence artificielle » qui devra fournir des « évaluations scientifiques fondées sur des données probantes dans lesquelles seront synthétisées et analysées les études existantes sur les promesses, les risques et les répercussions de l’intelligence artificielle ». Son rapport de synthèse annuel « servira à éclairer la prise de décisions, sans toutefois être prescriptif », précise le texte. Lire aussi | Article réservé à nos abonnés De Meta AI à ChatGPT, le jeu dangereux d’une personnalisation toujours plus poussée des IA « Pont crucial » Mandaté par l’Assemblée, le secrétaire général de l’ONU, Antonio Guterres, qui a salué la création d’un « pont crucial entre la recherche de pointe sur l’IA et l’élaboration des politiques », va désormais lancer un appel à candidatures pour identifier les quarante futurs membres du groupe, qui siégeront pour un mandat de trois ans. « L’intelligence artificielle se développe à un rythme et à une échelle qui affectent tous les pays », a commenté la représentante permanente du Costa Rica auprès de l’ONU, Maritza Chan Valverde, qui a supervisé les négociations avec son homologue espagnol. « Avec cette résolution, les Nations unies réaffirment leur rôle central pour garantir que l’IA sera au service de l’humanité », a-t-elle insisté. « En fournissant des évaluations scientifiques rigoureuses et indépendantes, [le groupe] aidera la communauté internationale à anticiper les défis émergents et à prendre des décisions informées sur comment régir cette technologie transformatrice », a commenté le porte-parole du secrétaire général, Stéphane Dujarric. Le Monde avec AFP

Elon Musk à Grünheide, en Allemagne, le 22 mars 2022. PATRICK PLEUL/VIA REUTERS Le réseau social X et la start-up xAI, propriétés d’Elon Musk, ont porté plainte, lundi 25 août, contre Apple et OpenAI qu’ils accusent d’avoir formé une alliance illégale pour entraver la concurrence dans le domaine de l’intelligence artificielle (IA) générative sur les smartphones. Le milliardaire, qui a saisi une cour fédérale du Texas, affirme que le fabricant de l’iPhone et l’éditeur de ChatGPT se sont mis d’accord pour intégrer l’assistant IA aux smartphones d’Apple, tout en écartant des rivaux, comme Grok, l’assistant IA de xAI. « C’est l’histoire de deux monopoles qui unissent leurs forces pour assurer leur domination continue dans un monde désormais propulsé par la technologie la plus puissante jamais créée par l’humanité : l’intelligence artificielle », peut-on lire dans la plainte. X et xAI affirment qu’Apple détient 65 % du marché des smartphones aux Etats-Unis, tandis qu’OpenAI contrôlerait au moins 80 % du marché des assistants d’IA générative, grâce à ChatGPT. Apple et OpenAI ont annoncé leur partenariat en juin 2024, intégrant le célèbre assistant à certaines fonctionnalités de l’iPhone, notamment son assistant vocal Siri. Selon la plainte, cet accord donnerait à ChatGPT un accès exclusif à « des milliards de requêtes d’utilisateurs » provenant de centaines de millions d’appareils. Elon Musk accuse également Apple de manipuler le classement de sa plateforme de téléchargement des applications mobiles (App Store) pour favoriser l’application ChatGPT, tout en retardant l’approbation des mises à jour de l’application Grok. Ses entreprises réclament plusieurs milliards de dollars de dommages et intérêts ainsi qu’une injonction permanente pour mettre fin aux pratiques anticoncurrentielles qu’elles dénoncent. Lire aussi | Article réservé à nos abonnés Intelligence artificielle : les échanges aigres-doux entre Sam Altman et Mark Zuckerberg, nouveaux rivaux de la tech « Campagne acharnée » « Cette nouvelle plainte correspond bien au comportement récurrent de M. Musk, caractérisé par le harcèlement », a réagi un porte-parole d’OpenAI. Apple n’a pas répondu à une sollicitation de l’Agence France-Presse. Elon Musk a fait partie de l’équipe de onze personnes qui a fondé OpenAI en 2015, mais il a quitté l’entreprise en 2018 et ne cesse de l’attaquer sur X et devant les tribunaux depuis le succès phénoménal de ChatGPT à la fin de 2022. Il a entrepris une action en justice contre la star de la Silicon Valley qui aurait, selon lui, trahi ses valeurs, mais a aussi proposé de la racheter. OpenAI a riposté en avril avec une plainte contre le milliardaire, l’accusant de mener une « campagne acharnée » pour lui nuire. Newsletter Newsletter Le Monde Newsletter Suivez-nous sur WhatsApp Ce mois-ci, Elon Musk s’en est pris à Apple : « Apple agit de manière à rendre impossible pour toute entreprise d’IA autre qu’OpenAI d’atteindre la première place sur l’App Store, ce qui constitue une violation manifeste des règles de concurrence », a lancé le milliardaire sur X. Ces accusations ont provoqué une passe d’armes avec Sam Altman, cofondateur et patron d’OpenAI. « C’est une affirmation remarquable, compte tenu de ce que j’ai entendu dire à propos d’Elon, qui manipulerait X pour son propre bénéfice et celui de ses entreprises et pour nuire à ses concurrents ainsi qu’aux personnes qu’il n’apprécie pas », a-t-il réagi sur X. Sam Altman « ment comme il respire », a renchéri Elon Musk, qualifiant son message de « connerie ». Lire aussi | Article réservé à nos abonnés De Mark Zuckerberg à Elon Musk, le « boys club » de Palo Alto Le Monde avec AFP Réutiliser ce contenu

Des investissements mirobolants, des valorisations boursières extravagantes et trop peu de profits pour l’instant, à l’exception du fabricant de microprocesseurs Nvidia : la folie de l’intelligence artificielle (IA) est-elle en passe de se transformer en bulle financière ? C’est la mise en garde lancée mi-août par Sam Altman, le PDG d’OpenAI. « Si l’on considère la plupart des bulles financières de l’histoire, comme la bulle Internet, on constate qu’il y avait une réalité : Internet était un phénomène majeur, les gens étaient surexcités. Sommes-nous dans une phase où les investisseurs dans leur ensemble sont surexcités par l’IA ? Je pense que oui. L’IA est-elle la chose la plus importante à venir depuis très longtemps ? Je pense que oui également », a-t-il déclaré à des journalistes américains. Lire aussi | Article réservé à nos abonnés IA : Donald Trump lâche la bride à la Silicon Valley pour assurer aux Etats-Unis « une domination mondiale » L’inquiétude est de plus en plus partagée. « Je m’attends à un krach »,Technological Revolutions and Financial Capital : The Dynamics of Bubbles and Golden Ages, « révolutions technologiques et capital financier, les dynamiques des bulles et des âges d’or »,« Des trois acteurs en jeu, les investisseurs, les entreprises d’IA et les utilisateurs, les seuls à réaliser des profits sont les acteurs financiers dont les valorisations augmentent. C’est une situation de bulle typique : des plus-values ​​élevées et des profits faibles. » L’affaire a un petit goût de déjà-vu pour l’économiste, réputée pour ses travaux sur l’innovation, qui a examiné les cinq révolutions industrielles majeures : le métier à tisser mû par un moulin à aubes en Angleterre (1771), la locomotive à vapeur de George Stephenson (1829), l’acier d’Andrew Carnegie à Pittsburgh (1875), la chaîne d’assemblage de Ford (1913) et le premier microprocesseur Intel (1971). Toutes ont révolutionné l’Occident. Lire aussi | Article réservé à nos abonnés Après le métavers, Mark Zuckerberg investit des dizaines de milliards de dollars dans la « superintelligence » grâce à ses résultats mirobolants Mais avant de s’installer durablement et de diffuser leurs effets à l’économie, ces innovations ont provoqué une frénésie d’investissements – trop de canaux en Angleterre, trop de chemins de fer peu rentables — et de spéculation financière détachée des réalités, provoquant krachs ou corrections boursières. Beaucoup, sur les marchés, ont en mémoire l’éclatement de la bulle Internet en l’an 2000. « La bulle de l’IA est aujourd’hui plus importante que celle des technologies de l’information des années 1990 », estimait mi-juillet Torsten Slok, économiste en chef du fonds Apollo. Il vous reste 73.74% de cet article à lire. La suite est réservée aux abonnés.

Bubsy 4D from Atari and Fabraz is looking like it might be a damn fine platformer The post The New <i>Bubsy</i> Game Actually Looks Awesome, Seriously appeared first on Kotaku.

Everton, away. That is where Brighton head coach Fabian Hurzeler's Premier League story began just over a year ago.

AI reasoning, inference and networking will be top of mind for attendees of next week’s Hot Chips conference. A key forum for processor and system architects from industry and academia, Hot Chips — running Aug. 24-26 at Stanford University — showcases the latest innovations poised to advance AI factories and drive revenue for the trillion-dollar data center computing market. At the conference, NVIDIA will join industry leaders including Google and Microsoft in a “tutorial” session — taking place on Sunday, Aug. 24 — that discusses designing rack-scale architecture for data centers. In addition, NVIDIA experts will present at four sessions and one tutorial detailing how: NVIDIA networking, including the NVIDIA ConnectX-8 SuperNIC, delivers AI reasoning at rack- and data-center scale. (Featuring Idan Burstein, principal architect of network adapters and systems-on-a-chip at NVIDIA) Neural rendering advancements and massive leaps in inference — powered by the NVIDIA Blackwell architecture, including the NVIDIA GeForce RTX 5090 GPU — provide next-level graphics and simulation capabilities. (Featuring Marc Blackstein, senior director of architecture at NVIDIA) Co-packaged optics (CPO) switches with integrated silicon photonics — built with light-speed fiber rather than copper wiring to send information quicker and using less power — enable efficient, high-performance, gigawatt-scale AI factories. The talk will also highlight NVIDIA Spectrum-XGS Ethernet, a new scale-across technology for unifying distributed data centers into AI super-factories. (Featuring Gilad Shainer, senior vice president of networking at NVIDIA) The NVIDIA GB10 Superchip serves as the engine within the NVIDIA DGX Spark desktop supercomputer. (Featuring Andi Skende, senior distinguished engineer at NVIDIA) It’s all part of how NVIDIA’s latest technologies are accelerating inference to drive AI innovation everywhere, at every scale. NVIDIA Networking Fosters AI Innovation at Scale AI reasoning — when artificial intelligence systems can analyze and solve complex problems through multiple AI inference passes — requires rack-scale performance to deliver optimal user experiences efficiently. In data centers powering today’s AI workloads, networking acts as the central nervous system, connecting all the components — servers, storage devices and other hardware — into a single, cohesive, powerful computing unit. NVIDIA ConnectX-8 SuperNIC Burstein’s Hot Chips session will dive into how NVIDIA networking technologies — particularly NVIDIA ConnectX-8 SuperNICs — enable high-speed, low-latency, multi-GPU communication to deliver market-leading AI reasoning performance at scale. As part of the NVIDIA networking platform, NVIDIA NVLink, NVLink Switch and NVLink Fusion deliver scale-up connectivity — linking GPUs and compute elements within and across servers for ultra low-latency, high-bandwidth data exchange. NVIDIA Spectrum-X Ethernet provides the scale-out fabric to connect entire clusters, rapidly streaming massive datasets into AI models and orchestrating GPU-to-GPU communication across the data center. Spectrum-XGS Ethernet scale-across technology extends the extreme performance and scale of Spectrum-X Ethernet to interconnect multiple, distributed data centers to form AI super-factories capable of giga-scale intelligence. Connecting distributed AI data centers with NVIDIA Spectrum-XGS Ethernet. At the heart of Spectrum-X Ethernet, CPO switches push the limits of performance and efficiency for AI infrastructure at scale, and will be covered in detail by Shainer in his talk. NVIDIA GB200 NVL72 — an exascale computer in a single rack — features 36 NVIDIA GB200 Superchips, each containing two NVIDIA B200 GPUs and an NVIDIA Grace CPU, interconnected by the largest NVLink domain ever offered, with NVLink Switch providing 130 terabytes per second of low-latency GPU communications for AI and high-performance computing workloads. An NVIDIA rack-scale system. Built with the NVIDIA Blackwell architecture, GB200 NVL72 systems deliver massive leaps in reasoning inference performance. NVIDIA Blackwell and CUDA Bring AI to Millions of Developers The NVIDIA GeForce RTX 5090 GPU — also powered by Blackwell and to be covered in Blackstein’s talk — doubles performance in today’s games with NVIDIA DLSS 4 technology. NVIDIA GeForce RTX 5090 GPU It can also add neural rendering features for games to deliver up to 10x performance, 10x footprint amplification and a 10x reduction in design cycles,  helping enhance realism in computer graphics and simulation. This offers smooth, responsive visual experiences at low energy consumption and improves the lifelike simulation of characters and effects. NVIDIA CUDA, the world’s most widely available computing infrastructure, lets users deploy and run AI models using NVIDIA Blackwell anywhere. Hundreds of millions of GPUs run CUDA across the globe, from NVIDIA GB200 NVL72 rack-scale systems to GeForce RTX– and NVIDIA RTX PRO-powered PCs and workstations, with NVIDIA DGX Spark powered by NVIDIA GB10 — discussed in Skende’s session — coming soon. From Algorithms to AI Supercomputers — Optimized for LLMs NVIDIA DGX Spark Delivering powerful performance and capabilities in a compact package, DGX Spark lets developers, researchers, data scientists and students push the boundaries of generative AI right at their desktops, and accelerate workloads across industries. As part of the NVIDIA Blackwell platform, DGX Spark brings support for NVFP4, a low-precision numerical format to enable efficient agentic AI inference, particularly of large language models (LLMs). Learn more about NVFP4 in this NVIDIA Technical Blog. Open-Source Collaborations Propel Inference Innovation NVIDIA accelerates several open-source libraries and frameworks to accelerate and optimize AI workloads for LLMs and distributed inference. These include NVIDIA TensorRT-LLM, NVIDIA Dynamo, TileIR, Cutlass, the NVIDIA Collective Communication Library and NIX — which are integrated into millions of workflows. Allowing developers to build with their framework of choice, NVIDIA has collaborated with top open framework providers to offer model optimizations for FlashInfer, PyTorch, SGLang, vLLM and others. Plus, NVIDIA NIM microservices are available for popular open models like OpenAI’s gpt-oss and Llama 4,  making it easy for developers to operate managed application programming interfaces with the flexibility and security of self-hosting models on their preferred infrastructure. Learn more about the latest advancements in inference and accelerated computing by joining NVIDIA at Hot Chips.  

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Across the globe, AI factories are rising — massive new data centers built not to serve up web pages or email, but to train and deploy intelligence itself. Internet giants have invested billions in cloud-scale AI infrastructure for their customers. Companies are racing to build AI foundries that will spawn the next generation of products and services. Governments are investing too, eager to harness AI for personalized medicine and language services tailored to national populations. Welcome to the age of AI factories — where the rules are being rewritten and the wiring doesn’t look anything like the old internet. These aren’t typical hyperscale data centers. They’re something else entirely. Think of them as high-performance engines stitched together from tens to hundreds of thousands of GPUs — not just built, but orchestrated, operated and activated as a single unit. And that orchestration? It’s the whole game. This giant data center has become the new unit of computing, and the way these GPUs are connected defines what this unit of computing can do. One network architecture won’t cut it. What’s needed is a layered design with bleeding-edge technologies — like co-packaged optics that once seemed like science fiction. The complexity isn’t a bug; it’s the defining feature. AI infrastructure is diverging fast from everything that came before it, and if there isn’t rethinking on how the pipes connect, scale breaks down. Get the network layers wrong, and the whole machine grinds to a halt. Get it right, and gain extraordinary performance. With that shift comes weight — literally. A decade ago, chips were built to be sleek and lightweight. Now, the cutting edge looks like the multi‑hundred‑pound copper spine of a server rack. Liquid-cooled manifolds. Custom busbars. Copper spines. AI now demands massive, industrial-scale hardware. And the deeper the models go, the more these machines scale up, and out. The NVIDIA NVLink spine, for example, is built from over 5,000 coaxial cables — tightly wound and precisely routed. It moves more data per second than the entire internet. That’s 130 TB/s of GPU-to-GPU bandwidth, fully meshed. This isn’t just fast. It’s foundational. The AI super-highway now lives inside the rack. The Data Center Is the Computer Training the modern large language models (LLMs) behind AI isn’t about burning cycles on a single machine. It’s about orchestrating the work of tens or even hundreds of thousands of GPUs that are the heavy lifters of AI computation. These systems rely on distributed computing, splitting massive calculations across nodes (individual servers), where each node handles a slice of the workload. In training, those slices — typically massive matrices of numbers — need to be regularly merged and updated. That merging occurs through collective operations, such as “all-reduce” (which combines data from all nodes and redistributes the result) and “all-to-all” (where each node exchanges data with every other node). These processes are susceptible to the speed and responsiveness of the network — what engineers call latency (delay) and bandwidth (data capacity) — causing stalls in training. For inference — the process of running trained models to generate answers or predictions — the challenges flip. Retrieval-augmented generation systems, which combine LLMs with search, demand real-time lookups and responses. And in cloud environments, multi-tenant inference means keeping workloads from different customers running smoothly, without interference. That requires lightning-fast, high-throughput networking that can handle massive demand with strict isolation between users. Traditional Ethernet was designed for single-server workloads — not for the demands of distributed AI. Tolerating jitter and inconsistent delivery were once acceptable. Now, it’s a bottleneck. Traditional Ethernet switch architectures were never designed for consistent, predictable performance — and that legacy still shapes their latest generations. Distributed computing requires a scale-out infrastructure built for zero-jitter operation — one that can handle bursts of extreme throughput, deliver low latency, maintain predictable and consistent RDMA performance, and isolate network noise. This is why InfiniBand networking is the gold standard for high-performance computing supercomputers and AI factories. With NVIDIA Quantum InfiniBand, collective operations run inside the network itself using Scalable Hierarchical Aggregation and Reduction Protocol technology, doubling data bandwidth for reductions. It uses adaptive routing and telemetry-based congestion control to spread flows across paths, guarantee deterministic bandwidth and isolate noise. These optimizations let InfiniBand scale AI communication with precision. It’s why NVIDIA Quantum infrastructure connects the majority of the systems on the TOP500 list of the world’s most powerful supercomputers, demonstrating 35% growth in just two years. For clusters spanning dozens of racks, NVIDIA Quantum‑X800 Infiniband switches push InfiniBand to new heights. Each switch provides 144 ports of 800 Gbps connectivity, featuring hardware-based SHARPv4, adaptive routing and telemetry-based congestion control. The platform integrates co‑packaged silicon photonics to minimize the distance between electronics and optics, reducing power consumption and latency. Paired with NVIDIA ConnectX-8 SuperNICs delivering 800 Gb/s per GPU, this fabric links trillion-parameter models and drives in-network compute. But hyperscalers and enterprises have invested billions in their Ethernet software infrastructure. They need a quick path forward that uses the existing ecosystem for AI workloads. Enter NVIDIA Spectrum‑X: a new kind of Ethernet purpose-built for distributed AI. Spectrum‑X Ethernet: Bringing AI to the Enterprise Spectrum‑X reimagines Ethernet for AI. Launched in 2023 Spectrum‑X delivers lossless networking, adaptive routing and performance isolation. The SN5610 switch, based on the Spectrum‑4 ASIC, supports port speeds up to 800 Gb/s and uses NVIDIA’s congestion control to maintain 95% data throughput at scale. Spectrum‑X is fully standards‑based Ethernet. In addition to supporting Cumulus Linux, it supports the open‑source SONiC network operating system — giving customers flexibility. A key ingredient is NVIDIA SuperNICs — based on NVIDIA BlueField-3 or ConnectX-8 — which provide up to 800 Gb/s RoCE connectivity and offload packet reordering and congestion management. Spectrum-X brings InfiniBand’s best innovations — like telemetry-driven congestion control, adaptive load balancing and direct data placement — to Ethernet, enabling enterprises to scale to hundreds of thousands of GPUs. Large-scale systems with Spectrum‑X, including the world’s most colossal AI supercomputer, have achieved 95% data throughput with zero application latency degradation. Standard Ethernet fabrics would deliver only ~60% throughput due to flow collisions. A Portfolio for Scale‑Up and Scale‑Out No single network can serve every layer of an AI factory. NVIDIA’s approach is to match the right fabric to the right tier, then tie everything together with software and silicon. NVLink: Scale Up Inside the Rack Inside a server rack, GPUs need to talk to each other as if they were different cores on the same chip. NVIDIA NVLink and NVLink Switch extend GPU memory and bandwidth across nodes. In an NVIDIA GB300 NVL72 system, 36 NVIDIA Grace CPUs and 72 NVIDIA Blackwell Ultra GPUs are connected in a single NVLink domain, with an aggregate bandwidth of 130 TB/s. NVLink Switch technology further extends this fabric: a single GB300 NVL72 system can offer 130 TB/s of GPU bandwidth, enabling clusters to support 9x the GPU count of a single 8‑GPU server. With NVLink, the entire rack becomes one large GPU. Photonics: The Next Leap To reach million‑GPU AI factories, the network must break the power and density limits of pluggable optics. NVIDIA Quantum-X and Spectrum-X Photonics switches integrate silicon photonics directly into the switch package, delivering 128 to 512 ports of 800 Gb/s with total bandwidths ranging from 100 Tb/s to 400 Tb/s. These switches offer 3.5x more power efficiency and 10x better resiliency compared with traditional optics, paving the way for gigawatt‑scale AI factories. Delivering on the Promise of Open Standards Spectrum‑X and NVIDIA Quantum InfiniBand are built on open standards. Spectrum‑X is fully standards‑based Ethernet with support for open Ethernet stacks like SONiC, while NVIDIA Quantum InfiniBand and Spectrum-X conform to the InfiniBand Trade Association’s InfiniBand and RDMA over Converged Ethernet (RoCE) specifications. Key elements of NVIDIA’s software stack — including NCCL and DOCA libraries — run on a variety of hardware, and partners such as Cisco, Dell Technologies, HPE and Supermicro integrate Spectrum-X into their systems. Open standards create the foundation for interoperability, but real-world AI clusters require tight optimization across the entire stack — GPUs, NICs, switches, cables and software. Vendors that invest in end‑to‑end integration deliver better latency and throughput. SONiC, the open‑source network operating system hardened in hyperscale data centers, eliminates licensing and vendor lock‑in and allows intense customization, but operators still choose purpose‑built hardware and software bundles to meet AI’s performance needs. In practice, open standards alone don’t deliver deterministic performance; they need innovation layered on top. Toward Million‑GPU AI Factories AI factories are scaling fast. Governments in Europe are building seven national AI factories, while cloud providers and enterprises across Japan, India and Norway are rolling out NVIDIA‑powered AI infrastructure. The next horizon is gigawatt‑class facilities with a million GPUs. To get there, the network must evolve from an afterthought to a pillar of AI infrastructure. The lesson from the gigawatt data center age is simple: the data center is now the computer. NVLink stitches together GPUs inside the rack. NVIDIA Quantum InfiniBand scales them across it. Spectrum-X brings that performance to broader markets. Silicon photonics makes it sustainable. Everything is open where it matters, optimized where it counts.      

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