Posts in category: nVidia AI

AI integration across design and productivity applications is becoming the new standard, fueling demand for advanced computing performance. This means professionals and creatives will need to tap into increased compute power, regardless of the scale, complexity or scope of their projects.

To meet this growing need, NVIDIA is expanding its RTX professional graphics offerings with two new NVIDIA Ampere architecture-based GPUs for desktops: the NVIDIA RTX A400 and NVIDIA RTX A1000.

They expand access to AI and ray-tracing technology, equipping professionals with the tools they need to transform their daily workflows.

A New Era of Creativity, Performance and Efficiency

The RTX A400 GPU introduces accelerated ray tracing and AI to the RTX 400 series GPUs. With 24 Tensor Cores for AI processing, it surpasses traditional CPU-based solutions, enabling professionals to run cutting-edge AI applications, such as intelligent chatbots and copilots, directly on their desktops.

The GPU delivers real-time ray tracing so creators can build vivid, physically accurate 3D renders that push the boundaries of creativity and realism.

The A400 also includes four display outputs, a first for its series. This makes it ideal for high-density display environments, which are critical for industries like financial services, command and control, retail, and transportation.

The NVIDIA RTX A1000 GPU brings Tensor Cores and RT Cores to the RTX 1000 series GPUs for the first time, unlocking accelerated AI and ray-tracing performance for creatives and professionals.

With 72 Tensor Cores, the A1000 offers a tremendous upgrade over the previous generation, delivering over 3x faster generative AI processing for tools like Stable Diffusion. In addition, its 18 RT Cores speed graphics and rendering tasks by up to 3x, accelerating professional workflows such as 2D and 3D computer-aided design (CAD), product and architectural design, and 4K video editing.

The A1000 also excels in video processing, handling up to 38% more encode streams and offering 2x faster decode performance over the previous generation.

With a sleek, single-slot design and consuming just 50W, the A400 and A1000 GPUs bring impressive features to compact, energy-efficient workstations.

Expanding the Reach of RTX

These new GPUs empower users with cutting-edge AI, graphics and compute capabilities to boost productivity and unlock creative possibilities. Advanced workflows involving ray-traced renders and AI are now within reach, allowing professionals to push the boundaries of their work and achieve stunning levels of realism.

Industrial planners can use ‌these new powerful and energy-efficient computing solutions for edge deployments. Creators can boost editing and rendering speeds to produce richer visual content. Architects and engineers can seamlessly transition ideas from 3D CAD concepts into tangible designs. Teams working in smart spaces can use the GPUs for real-time data processing, AI-enhanced security and digital signage management in space-constrained settings. And healthcare professionals can achieve quicker, more precise medical imaging analyses.

Financial professionals have always used expansive, high-resolution visual workspaces for more effective trading, analysis and data management. With the RTX A400 GPU supporting up to four 4K displays natively, financial services users can now achieve a high display density with fewer GPUs, streamlining their setups and reducing costs.

Next-Generation Features and Accelerated Performance 

The NVIDIA RTX A400 and A1000 GPUs are equipped with features designed to supercharge everyday workflows, including:

• Second-generation RT Cores: Real-time ray tracing, photorealistic, physically based rendering and visualization for all professional workflows, including architectural drafting, 3D design and content creation, where accurate lighting and shadow simulations can greatly enhance the quality of work.
• Third-generation Tensor Cores: Accelerates AI-augmented tools and applications such as generative AI, image rendering denoising and deep learning super sampling to improve image generation speed and quality.
• Ampere architecture-based CUDA cores: Up to 2x the single-precision floating point throughput of the previous generation for significant speedups in graphics and compute workloads.
• 4GB or 8GB of GPU memory: 4GB of GPU memory with the A400 GPU and 8GB with the A1000 GPU accommodate a range of professional needs, from basic graphic design and photo editing to more demanding 3D modeling with textures or high-resolution editing and data analyses. The GPUs also feature increased memory bandwidth over the previous generation for quicker data processing and smoother handling of larger datasets and scenes.
• Encode and decode engines: With seventh-generation encode (NVENC) and fifth-generation decode (NVDEC) engines, the GPUs offer efficient video processing to support high-resolution video editing, streaming and playback with ultra-low latency. Inclusion of AV1 decode enables higher efficiency and smoother playback of more video formats.

Availability 

The NVIDIA RTX A1000 GPU is now available through global distribution partners such as PNY and Ryoyo Electric. The RTX A400 GPU is expected to be available from channel partners starting in May, with anticipated availability from manufacturers in the summer.

Editor’s note: This post is part of our In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks, and demonstrates how NVIDIA Studio technology improves creative workflows. We’re also deep diving on new GeForce RTX 40 Series GPU features, technologies and resources, and how they dramatically accelerate content creation.

Video editors have more to look forward to than just April showers.

Blackmagic Design’s DaVinci Resolve released version 19, adding the IntelliTrack AI point tracker and UltraNR AI-powered features to further streamline video editing workflows.

The NAB 2024 trade show is bringing together thousands of content professionals
from all corners of the broadcast, media and entertainment industries, with video editors and livestreamers seeking ways to improve their creative workflows with NVIDIA RTX technology.

The recently launched Design app SketchUp 2024 introduced a new graphics engine that uses DirectX 12, which renders scenes 2.5x faster than the previous engine.

April also brings the latest NVIDIA Studio Driver, which optimizes the latest creative app updates, available for download today.

And this week’s featured In the NVIDIA Studio artist Rakesh Kumar created his captivating 3D scene The Rooted Vault using RTX acceleration.

Video Editor’s DaVinci Code

DaVinci Resolve is a powerful video editing package with color correction, visual effects, motion graphics and audio post-production all in one software tool. Its elegant, modern interface is easy to learn for new users, while offering powerful capabilities for professionals.

Two new AI features make video editing even more efficient: the IntelliTrack AI point tracker for object tracking, stabilization and audio panning, and UltraNR, which uses AI for spatial noise reduction — doing so 3x faster on the GeForce RTX 4090 vs. the Mac M2 Ultra.

All DaVinci Resolve AI effects are accelerated on RTX GPUs by NVIDIA TensorRT, boosting AI performance by up to 2x. The update also includes acceleration for Beauty, Edge Detect and Watercolor effects, doubling performance on NVIDIA GPUs.

For more information, check out the DaVinci Resolve website.

SketchUp Steps Up

SketchUp 2024 is a professional-grade 3D design software toolkit for designing buildings and landscapes, commonly used by designers and architects.

The new app, already receiving positive reviews, introduced a robust graphics engine that uses DirectX 12, which increases frames per second (FPS) by a factor of 2.5x over the previous engine. Navigating and orbiting complex models feels considerably lighter and faster with quicker, more predictable performance.

In testing, the scene below runs 4.5x faster FPS using the NVIDIA RTX 4090 vs. the Mac M2 Ultra and other competitors.

SketchUp 2024 also unlocks import and export functionality for OpenUSD files to efficiently manage the interoperability of complex 3D scenes and animations across numerous 3D apps.

Get the full release details.

Art Rooted in Nature

Rakesh Kumar’s passion for 3D modeling and animation stemmed from his love for gaming and storytelling.

“My goal is to inspire audiences and take them to new realms by showcasing the power of immersive storytelling, captivating visuals and the idea of creating worlds and characters that evoke emotions,” said Kumar.

His scene The Rooted Vault aims to convey the beauty of the natural world, transporting viewers to a serene setting filled with the soothing melodies of nature.

Kumar began by gathering reference material.

He then used Autodesk Maya to block out the basic structure and piece together the house as a series of modules. GPU-accelerated viewport graphics ensured fast, interactive 3D modeling and animations.

Next, Kumar used ZBrush to sculpt high-resolution details into the modular assets.

He used the ZBrush decimation tool alongside Unreal Engine’s Nanite workflow to efficiently create most of the modular building props.

Traditional poly-modeling workflows for the walls enabled vertex blending shaders for seamless texture transitions.

Textures were created with Adobe Substance 3D Painter. Kumar’s RTX GPU used RTX-accelerated light and ambient occlusion to bake and optimize assets in mere seconds.

Kumar moved the project to Unreal Engine 5, where near-final finishing touches such as lighting, shadows and visual effects were applied.

GPU acceleration played a crucial role in real-time rendering, allowing him to instantly see and adjust the scene.

Kumar then moved to Blackmagic Design’s DaVinci Resolve to color grade the scene for the desired mood and aesthetic, before he began final editing in Premiere Pro, adding transitions and audio.

“While the initial concept required significant revisions, the final result demonstrates the iterative nature of artistic creation — all inspired by my mentors, friends and family, who were always there to support me,” Kumar said.

Check out Kumar’s latest work on Instagram.

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AI promises to bring the full benefits of the digital revolution to billions across the globe, NVIDIA CEO Jensen Huang said Friday during a conversation with Oregon State University President Jayathi Murthy.

“I believe that artificial intelligence is the technology industry’s single greatest contribution to social elevation, to lift all of the people that have historically been left behind,” Huang told more than 2,000 faculty, students and staff gathered for his conversation with Murthy.

The talk was the highlight of a forum marking the groundbreaking for a new research building that will be named for Huang and his wife, Lori, both Oregon State alumni.

The facility positions Oregon State as a leader not just in the semiconductor industry but also at the intersection of high performance computing and a growing number of fields.

Those innovations have world-changing implications.

Huang said those who know a programming language such as C++ typically have greater opportunities.

“Because programming is so hard, the number of people who have benefitted from this, putting it to use for their economic prosperity, has been limited,” Huang said.

AI unlocks that and more.

“So you essentially have a collaborator with you at all times, essentially have a tutor at all times, and so I think the ability for AI to elevate all of the people left behind is quite extraordinary,” he added.

Huang’s appearance in Corvallis, Oregon, capped off a week of announcements underscoring NVIDIA’s commitment to preparing the future workforce with advanced AI, data science and high performance computing training.

On Tuesday, NVIDIA announced that it would participate in a $110 million partnership between Japan and the United States, which would include funding for university research.

On Wednesday, Georgia Tech announced a new NVIDIA-powered supercomputer that will help prepare undergraduate students to solve complex challenges with AI and HPC.

And later this month, NVIDIA founder Chris Malachowsky will be inducted into the Hall of Fame for the University of Florida’s Department of Electrical & Computer Engineering, following the November inauguration of the university’s $150 million Malachowsky Hall for Data Science & Information Technology.

Educating Future Leaders for ‘New Industrial Revolution’

NVIDIA has been investing in universities for decades, providing computing resources, advanced training curricula, donations and other support.

These contributions enable students and professors to access the high performance computing necessary for groundbreaking results at a key moment in the history of the industry.

“We’re at the beginning of a new industrial revolution, and the reason why I say that is because an industrial revolution produces something new that was impossible to produce in the past,” Huang said.

“And in this new world, you can apply electricity, and what’s going to come out of it is a whole bunch of floating-point numbers. We call them tokens, and those tokens are essentially artificial intelligence,” Huang said.

“And so this industrial revolution is going to be manufacturing intelligence at a very large scale,” Huang said.

OSU Breaks Ground on $213 Million Research Complex

Friday’s event in Oregon highlighted the Huangs’ commitment to education and reflected the couple’s deep personal ties to Oregon State, where the two met.

The conversation with Murthy followed the groundbreaking for the Jen-Hsun Huang and Lori Mills Huang Collaborative Innovation Complex, which took place Friday morning on the Corvallis campus.

When it opens in 2026, the 150,000-square-foot, $213 million complex — supported by a $50 million gift from the Huangs — will increase Oregon State’s support for the semiconductor and technology industry in Oregon and beyond.

Harnessing one of the nation’s most powerful NVIDIA supercomputers, the complex will bring together faculty and students to solve critical challenges facing the world in areas such as climate science, clean energy and water resources.

Huang sees the center — and AI — as helping put the benefits of computing at the service of people doing work across a broad range of disciplines.

Oregon State is one of the world’s premier schools in forestry, Huang said, adding that “let’s just face it, it’s very unlikely that somebody who was in forestry, it’s not impossible, but C++ is probably not your thing,” Huang said.

Thanks to ChatGPT, you can “now use a computer to apply it to your field of science and apply this computing technology to revolutionize your work.”

That makes learning how to think — and how to collaborate — more important than ever, Huang said. It’s “no different than if I gave you a partner to collaborate with you to solve problems,” Huang said.

“You still need to know how to collaborate, how to prompt, how to frame a problem, how to refine the solution, how to iterate on it and how to change your mind.”

NVIDIA Joins $110 Million Partnership to Help Universities Teach AI Skills

The groundbreaking at Oregon State is just one of several announcements highlighting NVIDIA’s global commitment to advancing the global technology industry.

Last week, the Biden Administration announced a new $110 million AI partnership between Japan and the United States, including an initiative to fund research through collaboration between the University of Washington and the University of Tsukuba.

As part of this, NVIDIA is committing $25 million to a collaboration with Amazon to bring the latest technologies to the University of Washington, in Seattle, and the University of Tsukuba, northeast of Tokyo.

Georgia Tech Unveils New AI Makerspace in Collaboration With NVIDIA

And on Wednesday, Georgia Tech’s College of Engineering established an AI supercomputing hub dedicated to teaching students.

The AI Makerspace was launched in collaboration with NVIDIA. College leaders call it a “digital sandbox” for students to understand and use AI. Initially focusing on undergraduates, the AI Makerspace aims to democratize access to computing resources typically reserved for researchers or technology companies.

Students will access the cluster online as part of their coursework. The Makerspace will also better position students after graduation as they work with AI professionals and help shape future applications.

‘Beginning of a New World’

To be sure, AI has limits, Huang explained. “It’s no different than when you work with teammates or lab partners; you’re guiding each other along because you know each other’s weaknesses and strengths,” he said.

However, Huang said now is a fantastic time to get an education and prepare for a career.

“This is the beginning of a new world and this is the best of times to go to school — the whole world is changing, right? New technology and new capabilities, new instruments and new ways to learn,” Huang said.

Images courtesy of Oregon State University.

Welcome to the wasteland, Vault Dwellers. Bethesda’s Fallout 4 and Fallout 76 are bringing post-nuclear adventures to the cloud.

These highly acclaimed action role-playing games lead 10 new titles joining GeForce NOW this week.

Announced as coming to GeForce NOW at CES, Honkai: Star Rail is targeting a release this quarter. Stay tuned for future updates.

Vault Into the Cloud

Adventurers needed, whether for mapping the irradiated wasteland or shaping the fate of humanity.

Embark on a journey through ruins of the post-apocalyptic Commonwealth in Fallout 4. As the sole survivor of Vault 111, navigate a world destroyed by nuclear war, make choices to reshape the wasteland and rebuild society one settlement at a time. With a vast, open world, dynamic crafting systems and a gripping storyline, the game offers an immersive single-player experience that challenges dwellers to emerge as beacons of hope for humanity’s remnants.

Plus, in Fallout 76, head back to the early days of post-nuclear Appalachia and experience the Fallout universe’s largest, most dynamic world. Encounter unique challenges, build portable player homes called C.A.M.P.s, and cooperate or compete with other survivors in the mountainous lands in West Virginia.

Join the proud ranks of Vault survivors in the cloud today and stream these titles, including Creation Club content for Fallout 4, across devices. With longer gaming sessions and faster access to servers, GeForce NOW members can play anywhere, anytime, and at up to 4K resolution, streaming with an Ultimate membership. The games come just in time for those tuning into the Fallout series TV adaptation, released today, for a Fallout-filled week.

Go Big or Go Home

Gigantic: Rampage Edition promises big fun with epic 5v5 matches, crossplay support, an exciting roster of heroes and more. Rush to the cloud to jump into the latest game from Arc Games and team with four other players to control objectives and take down the opposing team’s mighty Guardian. Think fast, be bold and go gigantic!

Look forward to these new games this week:

• Gigantic: Rampage Edition (New release on Steam, April 9)
• Inkbound 1.0 (New release, on Steam, April 9)
• Broken Roads (New release on Steam, April 10)
• Infection Free Zone (New release on Steam, April 11)
• Shadow of the Tomb Raider: Definitive Edition (New release on Xbox and available on PC Game Pass, April 11)
• Backpack Battles (Steam)
• Fallout 4 (Steam)
• Fallout 76 (Steam and Xbox, available on PC Game Pass)
• Ghostrunner (Epic Games Store, free April 11-18)
• Terra Invicta (Xbox, available on PC Game Pass)

What are you planning to play this weekend? Let us know on X or in the comments below.

can’t help 𝙛𝙖𝙡𝙡ing into the cloud

— NVIDIA GeForce NOW (@NVIDIAGFN) April 10, 2024

Talk about scrubbing data. Curtis Northcutt, cofounder and CEO of Cleanlab, and Steven Gawthorpe, senior data scientist at Berkeley Research Group, speak about Cleanlab’s groundbreaking approach to data curation with Noah Kravitz, host of NVIDIA’s AI Podcast, in an episode recorded live at the NVIDIA GTC global AI conference. The startup’s tools enhance data reliability and trustworthiness through sophisticated error identification and correction algorithms. Northcutt and Gawthorpe provide insights into how AI-powered data analytics can help combat economic crimes and corruption and discuss the intersection of AI, data science and ethical governance in fostering a more just society.

Cleanlab is a member of the NVIDIA Inception program for cutting-edge startups.

Stay tuned for more episodes recorded live from GTC.

Time Stamps

1:05: Northcutt on Cleanlab’s inception and mission
2:41: What Cleanlab offers its customers
4:24: The human element in Cleanlab’s data verification
8:57: Gawthorpe on the core functions, aims of the Berkeley Research Group
10:42: Gawthorpe’s approach to data collection and analysis in fraud investigations
16:38: Cleanlab’s one-click solution for generating machine learning models
18:30: The evolution of machine learning and its impact on data analytics
20:07: Future directions in data-driven crimefighting

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Editor’s note: This post is part of the AI Decoded series, which demystifies AI by making the technology more accessible, and which showcases new hardware, software, tools and accelerations for RTX PC users.

Skyscrapers start with strong foundations. The same goes for apps powered by AI.

A foundation model is an AI neural network trained on immense amounts of raw data, generally with unsupervised learning.

It’s a type of artificial intelligence model trained to understand and generate human-like language. Imagine giving a computer a huge library of books to read and learn from, so it can understand the context and meaning behind words and sentences, just like a human does.

A foundation model’s deep knowledge base and ability to communicate in natural language make it useful for a broad range of applications, including text generation and summarization, copilot production and computer code analysis, image and video creation, and audio transcription and speech synthesis.

ChatGPT, one of the most notable generative AI applications, is a chatbot built with OpenAI’s GPT foundation model. Now in its fourth version, GPT-4 is a large multimodal model that can ingest text or images and generate text or image responses.

Online apps built on foundation models typically access the models from a data center. But many of these models, and the applications they power, can now run locally on PCs and workstations with NVIDIA GeForce and NVIDIA RTX GPUs.

Foundation Model Uses

Foundation models can perform a variety of functions, including:

• Language processing: understanding and generating text
• Code generation: analyzing and debugging computer code in many programming languages
• Visual processing: analyzing and generating images
• Speech: generating text to speech and transcribing speech to text

They can be used as is or with further refinement. Rather than training an entirely new AI model for each generative AI application — a costly and time-consuming endeavor — users commonly fine-tune foundation models for specialized use cases.

Pretrained foundation models are remarkably capable, thanks to prompts and data-retrieval techniques like retrieval-augmented generation, or RAG. Foundation models also excel at transfer learning, which means they can be trained to perform a second task related to their original purpose.

For example, a general-purpose large language model (LLM) designed to converse with humans can be further trained to act as a customer service chatbot capable of answering inquiries using a corporate knowledge base.

Enterprises across industries are fine-tuning foundation models to get the best performance from their AI applications.

Types of Foundation Models

More than 100 foundation models are in use — a number that continues to grow. LLMs and image generators are the two most popular types of foundation models. And many of them are free for anyone to try — on any hardware — in the NVIDIA API Catalog.

LLMs are models that understand natural language and can respond to queries. Google’s Gemma is one example; it excels at text comprehension, transformation and code generation. When asked about the astronomer Cornelius Gemma, it shared that his “contributions to celestial navigation and astronomy significantly impacted scientific progress.” It also provided information on his key achievements, legacy and other facts.

Extending the collaboration of the Gemma models, accelerated with the NVIDIA TensorRT-LLM on RTX GPUs, Google’s CodeGemma brings powerful yet lightweight coding capabilities to the community. CodeGemma models are available as 7B and 2B pretrained variants that specialize in code completion and code generation tasks.

MistralAI’s Mistral LLM can follow instructions, complete requests and generate creative text. In fact, it helped brainstorm the headline for this blog, including the requirement that it use a variation of the series’ name “AI Decoded,” and it assisted in writing the definition of a foundation model.

Meta’s Llama 2 is a cutting-edge LLM that generates text and code in response to prompts.

Mistral and Llama 2 are available in the NVIDIA ChatRTX tech demo, running on RTX PCs and workstations. ChatRTX lets users personalize these foundation models by connecting them to personal content — such as documents, doctors’ notes and other data — through RAG. It’s accelerated by TensorRT-LLM for quick, contextually relevant answers. And because it runs locally, results are fast and secure.

Image generators like StabilityAI’s Stable Diffusion XL and SDXL Turbo let users generate images and stunning, realistic visuals. StabilityAI’s video generator, Stable Video Diffusion, uses a generative diffusion model to synthesize video sequences with a single image as a conditioning frame.

Multimodal foundation models can simultaneously process more than one type of data — such as text and images — to generate more sophisticated outputs.

A multimodal model that works with both text and images could let users upload an image and ask questions about it. These types of models are quickly working their way into real-world applications like customer service, where they can serve as faster, more user-friendly versions of traditional manuals.

Kosmos 2 is Microsoft’s groundbreaking multimodal model designed to understand and reason about visual elements in images.

Think Globally, Run AI Models Locally 

GeForce RTX and NVIDIA RTX GPUs can run foundation models locally.

The results are fast and secure. Rather than relying on cloud-based services, users can harness apps like ChatRTX to process sensitive data on their local PC without sharing the data with a third party or needing an internet connection.

Users can choose from a rapidly growing catalog of open foundation models to download and run on their own hardware. This lowers costs compared with using cloud-based apps and APIs, and it eliminates latency and network connectivity issues. Generative AI is transforming gaming, videoconferencing and interactive experiences of all kinds. Make sense of what’s new and what’s next by subscribing to the AI Decoded newsletter.

The Biden Administration has announced a new $110 million AI partnership between Japan and the United States that includes an initiative to fund research through a collaboration between the University of Washington and the University of Tsukuba.

NVIDIA is committing $25 million in a collaboration with Amazon that aims to bring the latest technologies to the University of Washington, in Seattle, and the University of Tsukuba, which is northeast of Tokyo.

Universities around the world are preparing students for crucial AI skills by providing access to the high performance computing capabilities of supercomputing.

“This collaboration between the University of Washington, University of Tsukuba, Amazon, and NVIDIA will help provide the research and workforce training for our regions’ tech sectors to keep up with the profound impacts AI is having across every sector of our economy,” said Jay Inslee, governor of Washington State.

Creating AI Opportunities for Students

NVIDIA has been investing in universities for decades computing resources, advanced training curriculums, donations, and other support to provide students and professors with access to high performance computing (HPC) for groundbreaking research results.

NVIDIA founder and CEO Jensen Huang and his wife, Lori Huang, donated $50 million to their alma mater Oregon State University — where they met and earned engineering degrees —  to help build one of the world’s fastest supercomputers in a facility bearing their names. This computing center will help students research, develop and apply AI across Oregon State’s top-ranked programs in agriculture, computer sciences, climate science, forestry, oceanography, robotics, water resources, materials sciences and more.

The University of Florida recently unveiled Malachowsky Hall, which was made possible with a $50 million donation from NVIDIA co-founder Chris Malachowsky. This new building along with a previous donation of an AI supercomputer is enabling the University of Florida to offer world class AI training and research opportunities.

Strengthening US-Japan AI Research Collaboration

The U.S.-Japan HPC alliance will advance AI research and development and support the two nations’ global leadership in cutting-edge technology.

The University of Washington and Tsukuba University initiative will support research in critical areas where AI can drive impactful change, such as robotics, healthcare, climate change and atmospheric science, among others.

In addition to the university partnership,  NVIDIA recently announced a collaboration with Japan’s National Institute of Advanced Industrial Science and Technology (AIST) on AI and quantum technology.

Addressing Worldwide AI Talent Shortage

Demand for key AI skills is creating a talent shortage worldwide. Some experts calculate there has been a fivefold increase in demand for these skills as a percentage of total U.S. jobs. Universities around the world are looking for ways to prepare students with new skills for the workforce, and corporate-university partnerships are a key tool to help bridge the gap.

NVIDIA unveiled at GTC 2024 new professional certifications in generative AI to help enable the next generation of developers to obtain technical credibility in this important domain.

Learn more about NVIDIA generative AI courses here and here.

Whether delivering live sports programming, streaming services, network broadcasts or content on social platforms, media companies face a daunting landscape.

Viewers are increasingly opting for interactive and personalized content. Virtual reality and augmented reality continue their drive into the mainstream. New video compression standards are challenging traditional computing infrastructure. And AI is having an impact across the board.

In a situation this dynamic, media companies will benefit most from AI-enabled media solutions that flexibly align with their changing development and delivery needs.

NVIDIA Holoscan for Media, available now, is a software-defined platform that enables developers to easily build live media applications, supercharge them with AI and then deploy them across media platforms.

A New Approach to Media Application Development 

Holoscan for Media offers a new approach to development in live media. It simplifies application development by providing an internet protocol (IP)-based, cloud-native architecture that isn’t constrained by dedicated hardware, environments or locations. Instead, it integrates open-source and ubiquitous technologies and streamlines application delivery to customers, all while optimizing costs.

Traditional application development for the live media market relies on dedicated hardware. Because software is tied to that hardware, developers are constrained when it comes to innovating or upgrading applications.

Each deployment type, whether on premises or in the cloud, requires its own build, making development costly and inefficient. Beyond designing an application’s user interface and core functionalities, developers have to build out additional infrastructure services, further eating into research and development budgets.

The most significant challenge is incorporating AI, due to the complexity of building an AI software stack. This prevents many applications in pilot programs from moving to production.

Holoscan for Media eases the integration of AI into application development due to its underlying architecture, which enables software-defined video to be deployed on the same software stack as AI applications, including generative AI-based tools. This benefits vendors and research and development departments looking to incorporate AI apps into live video.

Since the platform is cloud-native, the same architecture can run independent of location, whether in the cloud, on premises or at the edge. Additionally, it’s not tied to a specific device, field-programmable gate array or appliance.

The Holoscan for Media architecture includes services like authentication, logging and security, as well as features that help broadcasters migrate to IP-based technologies, including the SMPTE ST 2110 transport protocol, the precision time protocol for timing and synchronization, and the NMOS controller and registry for dynamic device management.

A Growing Ecosystem of Partners

Beamr, Comprimato, Lawo, Media.Monks, Pebble, RED Digital Cinema, Sony Corporation and Telestream are among the early adopters already transforming live media with Holoscan for Media.

“We use Holoscan for Media as the core infrastructure for our broadcast and media workflow, granting us powerful scale to deliver interest-based content across a wide range of channels and platforms,” said Lewis Smithingham, senior vice president of innovation special operations at Media.Monks, a provider of software-defined production workflows.

“By compartmentalizing applications and making them interoperable, Holoscan for Media allows for easy adoption of new innovations from many different companies in one platform,” said Jeff Goodman, vice president of product management at RED Digital Cinema, a manufacturer of professional digital cinema cameras. “It takes much of the integration complexity out of the equation and will significantly increase the pace of innovation. We are very excited to be a part of it.”

“We believe NVIDIA Holoscan for Media is one of the paths forward to enabling the development of next-generation products and services for the industry, allowing the scaling of GPU power as needed,” said Masakazu Murata, senior general manager of media solutions business at Sony Corporation. “Our M2L-X software switcher prototype running on Holoscan for Media demonstrates how customers can run Sony’s solutions on GPU clusters.”

“Telestream is committed to transforming the media landscape, enhancing efficiency and content experiences without sacrificing quality or user-friendliness,” said Charlie Dunn, senior vice president and general manager at Telestream, a provider of digital media software and solutions. “We’ve seamlessly integrated the Holoscan for Media platform into our INSPECT IP video monitoring solution to achieve a clear and efficient avenue for ST 2110 compliance.”

Experience Holoscan for Media at NAB Show

These partners will showcase how they’re using NVIDIA Holoscan for Media at NAB Show, an event for the broadcast, media and entertainment industry, taking place April 13-17 in Las Vegas.

Explore development on Holoscan for Media and discover applications running on the platform at the Dell Technologies booth. Learn more about NVIDIA’s presence at NAB Show, including details on sessions and demos on generative AI, software-defined broadcast and immersive graphics.

Apply for access to NVIDIA Holoscan for Media today.

NVIDIA and Google Cloud have announced a new collaboration to help startups around the world accelerate the creation of generative AI applications and services.

The announcement, made today at Google Cloud Next ‘24 in Las Vegas, brings together the NVIDIA Inception program for startups and the Google for Startups Cloud Program to widen access to cloud credits, go-to-market support and technical expertise to help startups deliver value to customers faster.

Qualified members of NVIDIA Inception, a global program supporting more than 18,000 startups, will have an accelerated path to using Google Cloud infrastructure with access to Google Cloud credits, offering up to $350,000 for those focused on AI.

Google for Startups Cloud Program members can join NVIDIA Inception and gain access to technological expertise, NVIDIA Deep Learning Institute course credits, NVIDIA hardware and software, and more. Eligible members of the Google for Startups Cloud Program also can participate in NVIDIA Inception Capital Connect, a platform that gives startups exposure to venture capital firms interested in the space.

High-growth emerging software makers of both programs can also gain fast-tracked onboarding to Google Cloud Marketplace, co-marketing and product acceleration support.

This collaboration is the latest in a series of announcements the two companies have made to help ease the costs and barriers associated with developing generative AI applications for enterprises of all sizes. Startups in particular are constrained by the high costs associated with AI investments.

It Takes a Full-Stack AI Platform

In February, Google DeepMind unveiled Gemma, a family of state-of-the-art open models. NVIDIA, in collaboration with Google, recently launched optimizations across all NVIDIA AI platforms for Gemma, helping to reduce customer costs and speed up innovative work for domain-specific use cases.

Teams from the companies worked closely together to accelerate the performance of Gemma — built from the same research and technology used to create Google DeepMind’s most capable model yet, Gemini — with NVIDIA TensorRT-LLM, an open-source library for optimizing large language model inference, when running on NVIDIA GPUs.

NVIDIA NIM microservices, part of the NVIDIA AI Enterprise software platform, together with Google Kubernetes Engine (GKE) provide a streamlined path for developing AI-powered apps and deploying optimized AI models into production. Built on inference engines including NVIDIA Triton Inference Server and TensorRT-LLM, NIM supports a wide range of leading AI models and delivers seamless, scalable AI inferencing to accelerate generative AI deployment in enterprises.

The Gemma family of models, including Gemma 7B, RecurrentGemma and CodeGemma, are available from the NVIDIA API catalog for users to try from a browser, prototype with the API endpoints and self-host with NIM.

Google Cloud has made it easier to deploy the NVIDIA NeMo framework across its platform via GKE and Google Cloud HPC Toolkit. This enables developers to automate and scale the training and serving of generative AI models, allowing them to rapidly deploy turnkey environments through customizable blueprints that jump-start the development process.

NVIDIA NeMo, part of NVIDIA AI Enterprise, is also available in Google Cloud Marketplace, providing customers another way to easily access NeMo and other frameworks to accelerate AI development.

Further widening the availability of NVIDIA-accelerated generative AI computing, Google Cloud also announced the general availability of A3 Mega will be coming next month. The instances are an expansion to its A3 virtual machine family, powered by NVIDIA H100 Tensor Core GPUs. The new instances will double the GPU-to-GPU network bandwidth from A3 VMs.

Google Cloud’s new Confidential VMs on A3 will also include support for confidential computing to help customers protect the confidentiality and integrity of their sensitive data and secure applications and AI workloads during training and inference — with no code changes while accessing H100 GPU acceleration. These GPU-powered Confidential VMs will be available in Preview this year.

Next Up: NVIDIA Blackwell-Based GPUs

NVIDIA’s newest GPUs based on the NVIDIA Blackwell platform will be coming to Google Cloud early next year in two variations: the NVIDIA HGX B200 and the NVIDIA GB200 NVL72.

The HGX B200 is designed for the most demanding AI, data analytics and high performance computing workloads, while the GB200 NVL72 is designed for next-frontier, massive-scale, trillion-parameter model training and real-time inferencing.

The NVIDIA GB200 NVL72 connects 36 Grace Blackwell Superchips, each with two NVIDIA Blackwell GPUs combined with an NVIDIA Grace CPU over a 900GB/s chip-to-chip interconnect, supporting up to 72 Blackwell GPUs in one NVIDIA NVLink domain and 130TB/s of bandwidth. It overcomes communication bottlenecks and acts as a single GPU, delivering 30x faster real-time LLM inference and 4x faster training compared to the prior generation.

NVIDIA GB200 NVL72 is a multi-node rack-scale system that will be combined with Google Cloud’s fourth generation of advanced liquid-cooling systems.

NVIDIA announced last month that NVIDIA DGX Cloud, an AI platform for enterprise developers that’s optimized for the demands of generative AI, is generally available on A3 VMs powered by H100 GPUs. DGX Cloud with GB200 NVL72 will also be available on Google Cloud in 2025.