To speed up AI adoption across industries, HPE and NVIDIA today launched new AI factory offerings at HPE Discover in Las Vegas. The new lineup includes everything from modular AI factory infrastructure and HPE’s AI-ready RTX PRO Servers, to the next generation of HPE’s turnkey AI platform, HPE Private Cloud AI. The goal: give enterprises a framework to build and scale generative, agentic and industrial AI. The NVIDIA AI Computing by HPE portfolio is now among the broadest in the market. The portfolio combines NVIDIA Blackwell accelerated computing, NVIDIA Spectrum-X Ethernet and NVIDIA BlueField-3 networking technologies, NVIDIA AI Enterprise software and HPE’s full portfolio of servers, storage, services and software. This now includes HPE OpsRamp Software, a validated observability solution for the NVIDIA Enterprise AI Factory, and HPE Morpheus Enterprise Software for orchestration. The result is a pre-integrated, modular infrastructure stack to help teams get AI into production faster. This includes the next-generation HPE Private Cloud AI, co-engineered with NVIDIA and validated as part of the NVIDIA Enterprise AI Factory framework. This full-stack, turnkey AI factory solution will offer HPE ProLiant Compute DL380a Gen12 servers with the new NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs. These new NVIDIA RTX PRO Servers from HPE provide a universal data center platform for a wide range of enterprise AI and industrial AI use cases, and are now available to order from HPE. HPE Private Cloud AI includes the latest NVIDIA AI Blueprints, including the NVIDIA AI-Q Blueprint for AI agent creation and workflows. HPE also announced a new NVIDIA HGX B300 system, the HPE Compute XD690, built with NVIDIA Blackwell Ultra GPUs. It’s the latest entry in the NVIDIA AI Computing by HPE lineup and is expected to ship in October. In Japan, KDDI is working with HPE to build NVIDIA AI infrastructure to accelerate global adoption. The HPE-built KDDI system will be based on the NVIDIA GB200 NVL72 platform, built on the NVIDIA Grace Blackwell architecture, at the KDDI Osaka Sakai Data Center. To accelerate AI for financial services, HPE will co-test agentic AI workflows built on Accenture’s AI Refinery with NVIDIA, running on HPE Private Cloud AI. Initial use cases include sourcing, procurement and risk analysis. HPE said it’s adding 26 new partners to its “Unleash AI” ecosystem to support more NVIDIA AI use cases. The company now offers more than 70 packaged AI workloads, from fraud detection and video analytics to sovereign AI and cybersecurity. Security and governance were a focus, too. HPE Private Cloud AI supports air-gapped management, multi-tenancy and post-quantum cryptography. HPE’s try-before-you-buy program lets customers test the system in Equinix data centers before purchase. HPE also introduced new programs, including AI Acceleration Workshops with NVIDIA, to help scale AI deployments. Watch the keynote: HPE CEO Antonio Neri announced the news from the Las Vegas Sphere on Tuesday at 9 a.m. PT. Register for the livestream and watch the replay. Explore more: Learn how NVIDIA and HPE build AI factories for every industry. Visit the partner page. #hpe #nvidia #debut #factory #stack

Editor’s note: This blog is a part of Into the Omniverse, a series focused on how developers, 3D practitioners and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse. Simulated driving environments enable engineers to safely and efficiently train, test and validate autonomous vehiclesacross countless real-world and edge-case scenarios without the risks and costs of physical testing. These simulated environments can be created through neural reconstruction of real-world data from AV fleets or generated with world foundation models— neural networks that understand physics and real-world properties. WFMs can be used to generate synthetic datasets for enhanced AV simulation. To help physical AI developers build such simulated environments, NVIDIA unveiled major advances in WFMs at the GTC Paris and CVPR conferences earlier this month. These new capabilities enhance NVIDIA Cosmos — a platform of generative WFMs, advanced tokenizers, guardrails and accelerated data processing tools. Key innovations like Cosmos Predict-2, the Cosmos Transfer-1 NVIDIA preview NIM microservice and Cosmos Reason are improving how AV developers generate synthetic data, build realistic simulated environments and validate safety systems at unprecedented scale. Universal Scene Description, a unified data framework and standard for physical AI applications, enables seamless integration and interoperability of simulation assets across the development pipeline. OpenUSD standardization plays a critical role in ensuring 3D pipelines are built to scale. NVIDIA Omniverse, a platform of application programming interfaces, software development kits and services for building OpenUSD-based physical AI applications, enables simulations from WFMs and neural reconstruction at world scale. Leading AV organizations — including Foretellix, Mcity, Oxa, Parallel Domain, Plus AI and Uber — are among the first to adopt Cosmos models. Foundations for Scalable, Realistic Simulation Cosmos Predict-2, NVIDIA’s latest WFM, generates high-quality synthetic data by predicting future world states from multimodal inputs like text, images and video. This capability is critical for creating temporally consistent, realistic scenarios that accelerate training and validation of AVs and robots. In addition, Cosmos Transfer, a control model that adds variations in weather, lighting and terrain to existing scenarios, will soon be available to 150,000 developers on CARLA, a leading open-source AV simulator. This greatly expands the broad AV developer community’s access to advanced AI-powered simulation tools. Developers can start integrating synthetic data into their own pipelines using the NVIDIA Physical AI Dataset. The latest release includes 40,000 clips generated using Cosmos. Building on these foundations, the Omniverse Blueprint for AV simulation provides a standardized, API-driven workflow for constructing rich digital twins, replaying real-world sensor data and generating new ground-truth data for closed-loop testing. The blueprint taps into OpenUSD’s layer-stacking and composition arcs, which enable developers to collaborate asynchronously and modify scenes nondestructively. This helps create modular, reusable scenario variants to efficiently generate different weather conditions, traffic patterns and edge cases. Driving the Future of AV Safety To bolster the operational safety of AV systems, NVIDIA earlier this year introduced NVIDIA Halos — a comprehensive safety platform that integrates the company’s full automotive hardware and software stack with AI research focused on AV safety. The new Cosmos models — Cosmos Predict- 2, Cosmos Transfer- 1 NIM and Cosmos Reason — deliver further safety enhancements to the Halos platform, enabling developers to create diverse, controllable and realistic scenarios for training and validating AV systems. These models, trained on massive multimodal datasets including driving data, amplify the breadth and depth of simulation, allowing for robust scenario coverage — including rare and safety-critical events — while supporting post-training customization for specialized AV tasks. At CVPR, NVIDIA was recognized as an Autonomous Grand Challenge winner, highlighting its leadership in advancing end-to-end AV workflows. The challenge used OpenUSD’s robust metadata and interoperability to simulate sensor inputs and vehicle trajectories in semi-reactive environments, achieving state-of-the-art results in safety and compliance. Learn more about how developers are leveraging tools like CARLA, Cosmos, and Omniverse to advance AV simulation in this livestream replay: Hear NVIDIA Director of Autonomous Vehicle Research Marco Pavone on the NVIDIA AI Podcast share how digital twins and high-fidelity simulation are improving vehicle testing, accelerating development and reducing real-world risks. Get Plugged Into the World of OpenUSD Learn more about what’s next for AV simulation with OpenUSD by watching the replay of NVIDIA founder and CEO Jensen Huang’s GTC Paris keynote. Looking for more live opportunities to learn more about OpenUSD? Don’t miss sessions and labs happening at SIGGRAPH 2025, August 10–14. Discover why developers and 3D practitioners are using OpenUSD and learn how to optimize 3D workflows with the self-paced “Learn OpenUSD” curriculum for 3D developers and practitioners, available for free through the NVIDIA Deep Learning Institute. Explore the Alliance for OpenUSD forum and the AOUSD website. Stay up to date by subscribing to NVIDIA Omniverse news, joining the community and following NVIDIA Omniverse on Instagram, LinkedIn, Medium and X. #into #omniverse #world #foundation #models

Mark Theriault founded the startup FITY envisioning a line of clever cooling products: cold drink holders that come with freezable pucks to keep beverages cold for longer without the mess of ice. The entrepreneur started with 3D prints of products in his basement, building one unit at a time, before eventually scaling to mass production. Founding a consumer product company from scratch was a tall order for a single person. Going from preliminary sketches to production-ready designs was a major challenge. To bring his creative vision to life, Theriault relied on AI and his NVIDIA GeForce RTX-equipped system. For him, AI isn’t just a tool — it’s an entire pipeline to help him accomplish his goals. about his workflow below. Plus, GeForce RTX 5050 laptops start arriving today at retailers worldwide, from GeForce RTX 5050 Laptop GPUs feature 2,560 NVIDIA Blackwell CUDA cores, fifth-generation AI Tensor Cores, fourth-generation RT Cores, a ninth-generation NVENC encoder and a sixth-generation NVDEC decoder. In addition, NVIDIA’s Plug and Play: Project G-Assist Plug-In Hackathon — running virtually through Wednesday, July 16 — invites developers to explore AI and build custom G-Assist plug-ins for a chance to win prizes. the date for the G-Assist Plug-In webinar on Wednesday, July 9, from 10-11 a.m. PT, to learn more about Project G-Assist capabilities and fundamentals, and to participate in a live Q&A session. From Concept to Completion To create his standout products, Theriault tinkers with potential FITY Flex cooler designs with traditional methods, from sketch to computer-aided design to rapid prototyping, until he finds the right vision. A unique aspect of the FITY Flex design is that it can be customized with fun, popular shoe charms. For packaging design inspiration, Theriault uses his preferred text-to-image generative AI model for prototyping, Stable Diffusion XL — which runs 60% faster with the NVIDIA TensorRT software development kit — using the modular, node-based interface ComfyUI. ComfyUI gives users granular control over every step of the generation process — prompting, sampling, model loading, image conditioning and post-processing. It’s ideal for advanced users like Theriault who want to customize how images are generated. Theriault’s uses of AI result in a complete computer graphics-based ad campaign. Image courtesy of FITY. NVIDIA and GeForce RTX GPUs based on the NVIDIA Blackwell architecture include fifth-generation Tensor Cores designed to accelerate AI and deep learning workloads. These GPUs work with CUDA optimizations in PyTorch to seamlessly accelerate ComfyUI, reducing generation time on FLUX.1-dev, an image generation model from Black Forest Labs, from two minutes per image on the Mac M3 Ultra to about four seconds on the GeForce RTX 5090 desktop GPU. ComfyUI can also add ControlNets — AI models that help control image generation — that Theriault uses for tasks like guiding human poses, setting compositions via depth mapping and converting scribbles to images. Theriault even creates his own fine-tuned models to keep his style consistent. He used low-rank adaptationmodels — small, efficient adapters into specific layers of the network — enabling hyper-customized generation with minimal compute cost. LoRA models allow Theriault to ideate on visuals quickly. Image courtesy of FITY. “Over the last few months, I’ve been shifting from AI-assisted computer graphics renders to fully AI-generated product imagery using a custom Flux LoRA I trained in house. My RTX 4080 SUPER GPU has been essential for getting the performance I need to train and iterate quickly.” – Mark Theriault, founder of FITY  Theriault also taps into generative AI to create marketing assets like FITY Flex product packaging. He uses FLUX.1, which excels at generating legible text within images, addressing a common challenge in text-to-image models. Though FLUX.1 models can typically consume over 23GB of VRAM, NVIDIA has collaborated with Black Forest Labs to help reduce the size of these models using quantization — a technique that reduces model size while maintaining quality. The models were then accelerated with TensorRT, which provides an up to 2x speedup over PyTorch. To simplify using these models in ComfyUI, NVIDIA created the FLUX.1 NIM microservice, a containerized version of FLUX.1 that can be loaded in ComfyUI and enables FP4 quantization and TensorRT support. Combined, the models come down to just over 11GB of VRAM, and performance improves by 2.5x. Theriault uses the Blender Cycles app to render out final files. For 3D workflows, NVIDIA offers the AI Blueprint for 3D-guided generative AI to ease the positioning and composition of 3D images, so anyone interested in this method can quickly get started. Photorealistic renders. Image courtesy of FITY. Finally, Theriault uses large language models to generate marketing copy — tailored for search engine optimization, tone and storytelling — as well as to complete his patent and provisional applications, work that usually costs thousands of dollars in legal fees and considerable time. Generative AI helps Theriault create promotional materials like the above. Image courtesy of FITY. “As a one-man band with a ton of content to generate, having on-the-fly generation capabilities for my product designs really helps speed things up.” – Mark Theriault, founder of FITY Every texture, every word, every photo, every accessory was a micro-decision, Theriault said. AI helped him survive the “death by a thousand cuts” that can stall solo startup founders, he added. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.  Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter. Follow NVIDIA Workstation on LinkedIn and X.  See notice regarding software product information. #startup #uses #nvidia #rtxpowered #generative

🌟 What an incredible journey at the Annecy Festival! Day 5 was packed with inspiring interviews and fascinating discussions about generative AI. 🎤✨ Despite the soaring temperatures, the passion for sustainable production shines bright! ☀️💚 Engaging with brilliant minds like Pete Docter and Mary Alice Drumm reminded us of the endless possibilities that creative innovation brings. Let's embrace change, foster collaboration, and create a brighter future together! 🚀🎨 Keep pushing your boundaries and never stop dreaming! 💖 #AnnecyFestival #GenerativeAI #SustainableProduction #CreativityUnleashed #Inspiration

AI, Alexa, Amazon, generative AI, voice assistant, technology, Daniel Rausch, Alexa+, engineering ## Introduction In the ever-evolving world of technology, Amazon has recently announced significant updates to its voice assistant, Alexa. The new version, dubbed Alexa+, has been developed using a staggering amount of generative AI tools. This initiative marks a pivotal moment for Amazon's engineering teams, as they leverage advanced artificial intelligence to enhance the functionality and perfor...

Midjourney, Disney, Universal, procès pour droits d’auteur, vidéos génératives, personnages célèbres, créativité numérique, IA générative, contenu numérique ## Introduction Dans un monde où la technologie évolue à une vitesse fulgurante, nous assistons à des développements fascinants qui transcendent notre imagination. Récemment, une nouvelle a captivé l'attention des passionnés de cinéma et de technologie : Midjourney, l'innovant studio d'intelligence artificielle, a lancé un nouvel outil vid...

What a world we live in when scientists finally unlock the secrets to the axolotls' ability to regenerate limbs, only to reveal that the key lies not in some miraculous regrowth molecule, but in its controlled destruction! Seriously, what kind of twisted logic is this? Are we supposed to celebrate the fact that the secret to regeneration is, in fact, about knowing when to destroy something instead of nurturing and encouraging growth? This revelation is not just baffling; it's downright infuriating! In an age where regenerative medicine holds the promise of healing wounds and restoring functionality, we are faced with the shocking realization that the science is not about building up, but rather about tearing down. Why would we ever want to focus on the destruction of growth molecules instead of creating an environment where regeneration can bloom unimpeded? Where is the inspiration in that? It feels like a slap in the face to anyone who believes in the potential of science to improve lives! Moreover, can we talk about the implications of this discovery? If the key to regeneration involves a meticulous dance of destruction, what does that say about our approach to medical advancements? Are we really expected to just stand by and accept that we must embrace an idea that says, "let's get rid of the good stuff to allow for growth"? This is not just a minor flaw in reasoning; it's a fundamental misunderstanding of what regeneration should mean for us! To make matters worse, this revelation could lead to misguided practices in regenerative medicine. Instead of developing therapies that promote healing and growth, we could end up with treatments that focus on the elimination of beneficial molecules. This is absolutely unacceptable! How dare the scientific community suggest that the way forward is through destruction rather than cultivation? We should be demanding more from our researchers, not less! Let’s not forget the ethical implications. If the path to regeneration is paved with the controlled destruction of vital components, how can we trust the outcomes? We’re putting lives in the hands of a process that promotes destruction. Just imagine the future of medicine being dictated by a philosophy that sounds more like a dystopian nightmare than a beacon of hope. It is high time we hold scientists accountable for the direction they are taking in regenerative research. We need a shift in focus that prioritizes constructive growth, not destructive measures. If we are serious about advancing regenerative medicine, we must reject this flawed notion and demand a commitment to genuine regeneration—the kind that nurtures life, rather than sabotages it. Let’s raise our voices against this madness. We deserve better than a science that advocates for destruction as the means to an end. The axolotls may thrive on this paradox, but we, as humans, should expect far more from our scientific endeavors. #RegenerativeMedicine #Axolotl #ScienceFail #MedicalEthics #Innovation

Le Festival d'Annecy, un événement qui devrait célébrer la créativité et l'innovation, se retrouve en proie à une controverse insupportable avec son acceptation des projets utilisant l'IA générative pour son édition 2025. Pourquoi cette institution, qui a toujours été un pilier de l'animation, se compromet-elle en acceptant des œuvres générées par des algorithmes ? C'est tout simplement inacceptable ! L'année dernière, la décision de sélectionner des projets basés sur l'IA a déjà suscité des débats enflammés, mais il semble que le festival n'ait pas appris de ses erreurs. Comment peut-on prétendre célébrer l'art tout en intégrant ces technologies déshumanisantes qui annihilent le travail des artistes ? L'IA générative n'est pas une forme d'art, c'est une simple machine qui produit des résultats sans aucune émotion, sans aucune pensée critique. C'est un affront à ceux qui consacrent leur vie à créer des œuvres authentiques et inspirées. Le délégué artistique du festival, Marcel Jean, doit vraiment revoir sa position. Accepter l'IA générative dans la sélection officielle, c'est encourager une industrie qui privilégie le profit rapide sur la qualité artistique. Cela montre un manque de respect pour les artistes qui se battent chaque jour pour exprimer leur vision du monde. Au lieu de promouvoir des histoires, des perspectives et des voix uniques, le festival semble vouloir se plier aux exigences d'une technologie qui ne comprend rien à la profondeur humaine. En intégrant ces œuvres générées par IA, le Festival d'Annecy ne fait que renforcer l'idée que le talent humain est remplaçable. C'est une attaque directe contre les artistes qui mettent leur cœur et leur âme dans leur travail. Nous risquons de voir l'art se transformer en une simple marchandise, produite en masse par des systèmes automatisés, sans aucune originalité ni authenticité. Et que dire de la responsabilité éthique ? Où sont les discussions sur l'impact de l'IA sur l'emploi créatif ? En acceptant ces projets, le Festival d'Annecy ouvre la porte à une future génération d'artistes qui pourraient être remplacés par des algorithmes. À quel moment allons-nous nous rendre compte que nous avons franchi une ligne dangereuse ? Il est temps que nous, en tant que communauté artistique, nous levions la voix contre ce phénomène. Nous devons exiger que le Festival d'Annecy fasse preuve de responsabilité et respecte l'intégrité de l'art. La créativité humaine doit primer sur les algorithmes. Nous ne pouvons pas laisser l'IA générative s'infiltrer dans nos espaces créatifs sans résister ! #FestivalAnnecy #IAGénérative #ArtVsTech #Créativité #Éthique

generative engine optimization, AI-powered search, content optimization, search engines, ChatGPT, Google SEO, digital marketing, AI content strategies, online visibility, future of search ## Introduction In the evolving landscape of digital marketing, the term Generative Engine Optimization (GEO) has surfaced as a significant development. This practice revolves around optimizing content specifically for AI-powered search engines, such as ChatGPT and Google. As search engines continue to incorp...

So, as we venture into the illustrious year of 2025, one can’t help but marvel at the sheer inevitability of ChatGPT's meteoric rise to global fame. I mean, who needs human interaction when you can chat with a glorified algorithm that receives 5.19 billion visits a month? That's right, folks—if you ever wondered what it’s like to be more popular than a cat video on the internet, just look at our dear AI friend. In a world where 400 million users are frantically asking ChatGPT whether pineapple belongs on pizza (spoiler alert: it does), it's no surprise that “How to Rank in ChatGPT and AI Overviews” has turned into the hottest guide of the decade. Because if we can’t rank in a chat platform, what’s left? A life of obscurity, endlessly scrolling through TikTok videos of people pretending to be experts? And let’s not forget the wise folks at Google, who’ve taken the AI plunge much like that friend who jumps into the pool before checking the water temperature. Their integration of generative AI into Search is like putting a fancy bow on a mediocre gift—yes, it looks nice, but underneath it all, it’s still just a bunch of algorithms trying to figure out what you had for breakfast. But fear not, my friends! The secret to ranking in ChatGPT lies not in those pesky things called “qualifications” or “experience,” but in mastering the art of keywords! Yes, sprinkle a few buzzwords around like confetti, and voilà! You’re an instant expert. Just remember, if it sounds impressive, it must be true. Who needs substance when you can dazzle with style? Oh, and let’s address the elephant in the room (or should I say the AI in the chat). In a landscape where “AI Overviews” are the new gospel, it’s clear that we’re all just one poorly phrased question away from existential dread. “Why can’t I find my soulmate?” “Why is my cat judging me?” “Why does my life feel like a never-ending cycle of rephrased FAQs?” ChatGPT has the answers, or at least it will confidently pretend to. So buckle up, everyone! The race to rank in ChatGPT is the most exhilarating ride since the invention of the wheel (okay, maybe that’s a stretch, but you get the point). Let’s throw all our doubts into the void and embrace the chaos of AI with open arms. After all, if we can’t find meaning in our interactions with a chatbot, what’s the point of even logging in? And remember: in the grand scheme of things, we’re all just trying to outrank each other in a digital world where the lines between human and machine are as blurred as the coffee stain on my keyboard. Cheers to that! #ChatGPT #AIOverviews #DigitalTrends #SEO #2025Guide