Techbio is a field combining data, technology and biology to enhance scientific processes — and AI has the potential to supercharge the biopharmaceutical industry further. In this episode of NVIDIA’s AI Podcast, host Noah Kravitz speaks with Chris Gibson, cofounder and CEO of Recursion, about how the company uses AI and machine learning to accelerate drug discovery and development at scale. Tune in to hear Gibson discuss how AI is transforming the biopharmaceutical industry by increasing efficiency and lowering discovery costs.
0:58: Background on Recursion
6:23: Recursion’s approach to drug discovery
12:06: Empirical data generation and generative AI prediction
17:46: How supercomputing is accelerating drug discovery
22:32: What is techbio?
29:15: The future — using natural language prompts to work with AI systems
31:44: Recursion’s plans for future
Caristo Diagnostics has developed an AI-powered solution for detecting coronary inflammation in cardiac CT scans. Dr. Keith Channon, cofounder and chief medical officer of the company, discusses how Caristo uses AI to improve treatment plans and risk predictions by providing patient-specific readouts.
Clinician-led healthcare AI company Harrison.ai has built annalise.ai. This AI solution serves as a “spell checker” for radiologists — flagging critical findings to improve the speed and accuracy of radiology image analysis, reducing misdiagnoses. Harrison.ai CEO and cofounder Aengus Tran discusses the potential of autonomous AI systems to scale global healthcare capacity.
Matice Biosciences is using AI to study the regeneration of tissues in animal species known as super-regenerators, such as salamanders and planarians. Jessica Whited, a regenerative biologist at Harvard and cofounder of Matice Biosciences, discusses the company’s goal to harness regenerative species and AI to develop new treatments that help humans heal from injuries without scarring.
Artificial intelligence is teaming up with crowdsourcing to improve the thermo-stability of mRNA vaccines, making distribution more accessible worldwide. Bojan Tunguz, a physicist and senior system software engineer at NVIDIA, and Johnny Israeli, senior manager of AI and cloud software at NVIDIA, discuss the fusion of AI, crowdsourcing and machine learning and its potential in drug discovery.
Editor’s note: This post is part of the AI Decoded series, which demystifies AI by making the technology more accessible, and showcases new hardware, software, tools and accelerations for RTX PC users.
AI powered by NVIDIA GPUs is accelerating nearly every industry, creating high demand for graduates, especially from STEM fields, who are proficient in using the technology. Millions of students worldwide are participating in university STEM programs to learn skills that will set them up for career success.
To prepare students for the future job market, NVIDIA has worked with top universities to develop a GPU-accelerated AI curriculum that’s now taught in more than 5,000 schools globally. Students can get a jumpstart outside of class with NVIDIA’s AI Learning Essentials, a set of resources that equips individuals with the necessary knowledge, skills and certifications for the rapidly evolving AI workforce.
NVIDIA GPUs — whether running in university data centers, GeForce RTX laptops or NVIDIA RTX workstations — are accelerating studies, helping enhance the learning experience and enabling students to gain hands-on experience with hardware used widely in real-world applications.
Supercharged AI Studies
NVIDIA provides several tools to help students accelerate their studies.
The RTX AI Toolkit is a powerful resource for students looking to develop and customize AI models for projects in computer science, data science, and other STEM fields. It allows students to train and fine-tune the latest generative AI models, including Gemma, Llama 3 and Phi 3, up to 30x faster — enabling them to iterate and innovate more efficiently, advancing their studies and research projects.
Students studying data science and economics can use NVIDIA RAPIDS AI and data science software libraries to run traditional machine learning models up to 25x faster than conventional methods, helping them handle large datasets more efficiently, perform complex analyses in record time and gain deeper insights from data.
AI-deal for Robotics, Architecture and Design
Students studying robotics can tap the NVIDIA Isaac platform for developing, testing and deploying AI-powered robotics applications. Powered by NVIDIA GPUs, the platform consists of NVIDIA-accelerated libraries, applications frameworks and AI models that supercharge the development of AI-powered robots like autonomous mobile robots, arms and manipulators, and humanoids.
While GPUs have long been used for 3D design, modeling and simulation, their role has significantly expanded with the advancement of AI. GPUs are today used to run AI models that dramatically accelerate rendering processes.
Some industry-standard design tools powered by NVIDIA GPUs and AI include:
SOLIDWORKS Visualize: This 3D computer-aided design rendering software uses NVIDIA Optix AI-powered denoising to produce high-quality ray-traced visuals, streamlining the design process by providing faster, more accurate visual feedback.
Blender: This popular 3D creation suite uses NVIDIA Optix AI-powered denoising to deliver stunning ray-traced visuals, significantly accelerating content creation workflows.
Enscape: Enscape makes it possible to ray trace more geometry at a higher resolution, at exactly the same frame rate. It uses DLSS to enhance real-time rendering capabilities, providing architects and designers with seamless, high-fidelity visual previews of their projects.
Beyond STEM
Students, hobbyists and aspiring artists use the NVIDIA Studio platform to supercharge their creative processes with RTX and AI. RTX GPUs power creative apps such as Adobe Creative Cloud, Autodesk, Unity and more, accelerating a variety of processes such as exporting videos and rendering art.
ChatRTX is a demo app that lets students create a personalized GPT large language model connected to their own content and study materials, including text, images or other data. Powered by advanced AI, ChatRTX functions like a personalized chatbot that can quickly provide students relevant answers to questions based on their connected content. The app runs locally on a Windows RTX PC or workstation, meaning students can get fast, secure results personalized to their needs.
NVIDIA ChatRTX user interface.
Schools are increasingly adopting remote learning as a teaching modality. NVIDIA Broadcast — a free application that delivers professional-level audio and video with AI-powered features on RTX PCs and workstations — integrates seamlessly with remote learning applications including BlueJeans, Discord, Google Meet, Microsoft Teams, Webex and Zoom. It uses AI to enhance remote learning experiences by removing background noise, improving image quality in low-light scenarios, and enabling background blur and background replacement.
NVIDIA RTX-powered mobile workstations and GeForce RTX and Studio RTX 40 Series laptops offer supercharged development, learning, gaming and creating experiences with AI-enabled tools and apps. They also include exclusive access to the NVIDIA Studio platform of creative tools and technologies, and Max-Q technologies that optimize battery life and acoustics — giving students an ideal platform for all aspects of campus life.
Say goodbye to late nights in the computer lab — GeForce RTX laptops and NVIDIA RTX workstations share the same architecture as the NVIDIA GPUs powering many university labs and data centers. That means students can study, create and play — all on the same PC.
STEM Application Performance for GeForce RTX 4060 Laptop GPU versus Laptop without GeForce RTX GPU.
High school student Selin Alara Ornek is looking ahead — using machine learning and the NVIDIA Jetson platform for edge AI and robotics to create robot guide dogs for the visually impaired.
The project, called IC4U, is one of seven robots Ornek has created to date, including a school aid robot, named BB4All, that can help prevent bullying with real-time notification and health-monitoring capabilities.
About the Maker
A high school senior from Istanbul, Turkey, Ornek has always had a passion for the intersection of AI, social good and robotics. She’s a self-taught robotics developer — in building IC4U, she used the Jetson Developer Kit as a sandbox to explore and experiment.
She is a member of AI4ALL, a nonprofit program with the mission to make AI more diverse and inclusive, and the New York Academy of Science. A global presence in the robotics scene, she’s been recognized at the European Youth Awards and Women in Tech Global Awards events. She placed first in the 2021 Istanbul Bosphorus Robot Cup and third at the 2023 OpenCV AI Competition.
Her Inspiration
Ornek’s inspiration for creating IC4U came from a trip to France, where she saw a guide dog assisting its owner. Her late dog, Korsan, was also a key source of inspiration.
“I started to think about if a visually impaired person lost their dog, not only would they lose their best friend, but their eyes,” Ornek said.
The project was built to offer the visually impaired a companion not limited by aging and health.
Her Jetson Project
Ornek initially used ultrasonic sensors located in IC4U’s eyes to detect obstacles. But after attending the 2021 World Summit AI as a panelist, she decided to develop new AI applications for the robot dog that’d enable it to mimic a real one.
The ultrasonic sensors only offered object detection from directly in front of IC4U, and Ornek wanted to expand detection to the robot’s entire surroundings.
The solution was using sound sensors located in the robot’s ears. IC4U can turn toward a sound and process visual information gathered by an integrated ZED 2i Wide-Angle 3D AI camera, which captures a wider range of visual data and helps detect information such as the size and speed of an object.
“To power the ZED 2i camera and for high-quality image processing, I used an NVIDIA Jetson Nano developer kit,” Ornek said. “I was so impressed with the ZED 2i camera’s performance that I didn’t want to limit its use to a simple object-recognition task.”
She began to think of other ways that IC4U could assist a visually impaired person. IC4U’s improved data processing from high-resolution sensors, powered by Jetson, enables it to detect city objects such as stop signs, traffic light colors and the denomination of paper money.
In addition, Ornek used the Jetson Nano to add a shopping feature to IC4U via web scraping from publicly available resources, aiming to one day expand it by partnering with online retail stores.
Back to School
In the long run, Ornek hopes to deploy IC4U for use in smart cities and spaces — continuing her exploration of AI applications with next-generation platforms like Jetson Orin.
This fall, she’ll begin studying computer science at the University of British Columbia on a full scholarship, as a recipient of the Karen McKellin International Leader of Tomorrow Award. She strives to encourage other youth, especially girls, that technology is fun.
Students and educators with a valid accredited university or education-related email address can sign up to purchase the Jetson Orin Nano or Jetson AGX Orin Developer Kit at a discounted rate. U.S.-based students and educators can visit Sparkfun to sign up for their discount — residents of other countries should check their eligibility (login required).
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 GPU features, technologies and resources, and how they dramatically accelerate content creation.
Every month brings new creative app updates and optimizations powered by the NVIDIA Studio platform — supercharging creative processes with NVIDIA RTX and AI.
RTX-powered video editing app CyberLink PowerDirector now has a setting for high-efficiency video encoding (HEVC). 3D artists can access new features and faster workflows in Adobe Substance 3D Modeler and SideFX: Houdini. And content creators using Topaz Video AI Pro can now scale their photo and video touchups faster with NVIDIA TensorRT acceleration.
The August Studio Driver is ready to install via the NVIDIA app beta — the essential companion for creators and gamers — to keep GeForce RTX PCs up to date with the latest NVIDIA drivers and technology.
And this week’s featured In the NVIDIA Studio artist Stavros Liaskos is creating physically accurate 3D digital replicas of Greek Orthodox churches, holy temples, monasteries and other buildings using the NVIDIA Omniverse platform for building and connecting Universal Scene Description (OpenUSD) apps.
The NVIDIA NVENC video encoder is built into every RTX graphics card, offloading the compute-intensive task of video encoding from the CPU to a dedicated part of the GPU.
CyberLink PowerDirector, a popular video editing program that recently added support for RTX Video HDR, now has a setting to increase HEVC with NVIDIA NVENC HEVC Ultra-High-Quality mode.
The new functionality reduces bit rates and improves encoding efficiency by 55%, significantly boosting video quality. Using the custom setting, content creators can offer audiences superior viewing experiences.
Encoding efficiency jumps by 55% with just a few clicks.
Alpha exporting allows users to add overlay effects to videos by exporting HEVC video with an alpha channel. This technique can be used to create transparent backgrounds and rapidly process animated overlays, making it ideal for creating social media content.
With an alpha channel, users can export HEVC videos up to 8x faster compared with run-length encoding supported by other processors, and with a 100x reduction in file size.
Adobe Substance 3D Modeler, a multisurface 3D sculpting tool for artists, virtual effects specialists and designers, released Block to Stock, an AI-powered, geometry-based feature for accelerating the prototyping of complex shapes.
It allows rough 3D shapes to be quickly replaced with pre-existing, similarly shaped 3D models that have greater detail. The result is a highly detailed shape crafted in no time.
The recently released version 20.5 of SideFX: Houdini, a 3D procedural software for modeling, animation and lighting, introduced NVIDIA OptiX 8 and NVIDIA’s Shader Execution Reordering feature to its Karma XPU renderer — exclusively on NVIDIA RTX GPUs.
With these additions, computationally intensive tasks can now be executed up to 4x faster on RTX GPUs.
Topaz Video AI Pro, a photo and video enhancement software for noise reduction, sharpening and upscaling, added TensorRT acceleration for multi-GPU configurations, enabling parallelization across multiple GPUs for supercharged rendering speeds — up to 2x faster with two GPUs over a single GPU system, with further acceleration in systems with additional GPUs.
Virtual Cultural Sites to G(r)eek Out About
Anyone can now explore over 30 Greek cultural sites in virtual reality, thanks to the immersive work of Stavros Liaskos, managing director of visual communications company Reyelise.
“Many historical and religious sites are at risk due to environmental conditions, neglect and socio-political issues,” he said. “By creating detailed 3D replicas, we’re helping to ensure their architectural splendor is preserved digitally for future generations.”
Liaskos dedicated the project to his father, who passed away last year.
“He taught me the value of patience and instilled in me the belief that nothing is unattainable,” he said. “His wisdom and guidance continue to inspire me every day.”
Churches are architecturally complex structures. To create physically accurate 3D models of them, Liaskos used the advanced real-time rendering capabilities of Omniverse, connected with a slew of content-creation apps.
The OpenUSD framework enabled a seamless workflow across the various apps Liaskos used. For example, after using Trimble X7 for highly accurate 3D scanning of structures, Liaskos easily moved to Autodesk 3ds Max and Blender for modeling and animation.
Then, with ZBrush, he sculpted intricate architectural details on the models and refined textures with Adobe Photoshop and Substance 3D. It was all brought together in Omniverse for real-time lighting and rendering.
Interior rendering of the Panagia Xrysospiliotissa Church in Nicosia, Cyprus.
For post-production work, like adding visual effects and compiling rendered scenes, Liaskos used OpenUSD to transfer his projects to Adobe After Effects, where he finalized the video output. Nearly every element of his creative workflow was accelerated by his NVIDIA RTX A4500 GPU.
Interior scene of the Church of Saint Basil on Metsovou Street in Athens.
Liaskos also explored developing extended reality (XR) applications that allow users to navigate his 3D projects in real time in virtual reality (VR).
First, he used laser scanning and photogrammetry to capture the detailed geometries and textures of the churches.
Then, he tapped Autodesk 3ds Max and Maxon ZBrush for retopology, ensuring the models were optimized for real-time rendering without compromising detail.
After importing them into NVIDIA Omniverse with OpenUSD, Liaskos packaged the XR scenes so they could be streamed to VR headsets using either the NVIDIA Omniverse Create XR spatial computing app or Unity Engine, enabling immersive viewing experiences.
“This approach will even more strikingly showcase the architectural beauty and cultural significance of these sites,” Liaskos said. “The simulation must be as good as possible to recreate the overwhelming, impactful feeling of calm and safety that comes with visiting a deeply spiritual space.”
Members can choose their own adventure with GeForce NOW bringing 18 new games to the cloud in August — including Square Enix’s fantasy role-playing game Visions of Mana when it launches on PC Thursday, Aug. 29.
From cozy games to thrilling battles, there’s something for everyone. Dive into the latest titles and experience powerful performance across all devices — start with the six games available to stream this week.
Plus, the limited-time GeForce NOW Summer Sale continues, offering a 50% discount on new one-month and six-month Ultimate and Priority memberships. Check it out before the deal ends on Sunday, Aug. 18.
Awesome August
Fight for the future.
Plunge into the heart of battle with Stormgate, a newly released real-time strategy game from Frost Giant Studios, which is renowned for its work on popular games StarCraft II and Warcraft III. In single-player or multiplayer mode, fight demonic invaders, build bases and command armies to save humanity. Get immersed in a rich storyline, explore diverse factions and experience a blend of new and classic real-time strategy mechanics.
Members can check out the following new additions this week:
Stormgate Early Access (New release on Steam, July 30)
HAWKED and Flintlock: The Siege of Dawn (Xbox) were included in the July games list — HAWKED will no longer be added to GeForce NOW, while Flintlock: The Siege of Dawn will be added at another time. Stay tuned to GFN Thursday for more updates.
Starting in November, GeForce NOW will transition away from updating the GeForce NOW Windows and macOS apps for legacy operating systems, including Windows 7, Windows 8.1 and macOS 10.11-10.14. Members on these systems can still enjoy streaming on play.geforcenow.com via supported web browsers.
What are you planning to play this weekend? Let us know on X or in the comments below.
In celebration of Zoox’s 10th anniversary, NVIDIA founder and CEO Jensen Huang recently joined the robotaxi company’s CEO, Aicha Evans, and its cofounder and CTO, Jesse Levinson, to discuss the latest in autonomous vehicle (AV) innovation and experience a ride in the Zoox robotaxi.
In a fireside chat at Zoox’s headquarters in Foster City, Calif., the trio reflected on the two companies’ decade of collaboration. Evans and Levinson highlighted how Zoox pioneered the concept of a robotaxi purpose-built for ride-hailing and created groundbreaking innovations along the way, using NVIDIA technology.
“The world has never seen a robotics company like this before,” said Huang. “Zoox started out solely as a sustainable robotics company that delivers robots into the world as a fleet.”
Since 2014, Zoox has been on a mission to create fully autonomous, bidirectional vehicles purpose-built for ride-hailing services. This sets it apart in an industry largely focused on retrofitting existing cars with self-driving technology.
A decade later, the company is operating its robotaxi, powered by NVIDIA GPUs, on public roads.
Computing at the Core
Zoox robotaxis are, at their core, supercomputers on wheels. They’re built on multiple NVIDIA GPUs dedicated to processing the enormous amounts of data generated in real time by their sensors.
The sensor array includes cameras, lidar, radar, long-wave infrared sensors and microphones. The onboard computing system rapidly processes the raw sensor data collected and fuses it to provide a coherent understanding of the vehicle’s surroundings.
The processed data then flows through a perception engine and prediction module to planning and control systems, enabling the vehicle to navigate complex urban environments safely.
NVIDIA GPUs deliver the immense computing power required for the Zoox robotaxis’ autonomous capabilities and continuous learning from new experiences.
Using Simulation as a Virtual Proving Ground
Key to Zoox’s AV development process is its extensive use of simulation. The company uses NVIDIA GPUs and software tools to run a wide array of simulations, testing its autonomous systems in virtual environments before real-world deployment.
These simulations range from synthetic scenarios to replays of real-world scenarios created using data collected from test vehicles. Zoox uses retrofitted Toyota Highlanders equipped with the same sensor and compute packages as its robotaxis to gather driving data and validate its autonomous technology.
This data is then fed back into simulation environments, where it can be used to create countless variations and replays of scenarios and agent interactions.
Zoox also uses what it calls “adversarial simulations,” carefully crafted scenarios designed to test the limits of the autonomous systems and uncover potential edge cases.
The company’s comprehensive approach to simulation allows it to rapidly iterate and improve its autonomous driving software, bolstering AV safety and performance.
“We’ve been using NVIDIA hardware since the very start,” said Levinson. “It’s a huge part of our simulator, and we rely on NVIDIA GPUs in the vehicle to process everything around us in real time.”
A Neat Way to Seat
Zoox’s robotaxi, with its unique bidirectional design and carriage-style seating, is optimized for autonomous operation and passenger comfort, eliminating traditional concepts of a car’s “front” and “back” and providing equal comfort and safety for all occupants.
“I came to visit you when you were zero years old, and the vision was compelling,” Huang said, reflecting on Zoox’s evolution over the years. “The challenge was incredible. The technology, the talent — it is all world-class.”
Using NVIDIA GPUs and tools, Zoox is poised to redefine urban mobility, pioneering a future of safe, efficient and sustainable autonomous transportation for all.
From Testing Miles to Market Projections
As the AV industry gains momentum, recent projections highlight the potential for explosive growth in the robotaxi market. Guidehouse Insights forecasts over 5 million robotaxi deployments by 2030, with numbers expected to surge to almost 34 million by 2035.
The regulatory landscape reflects this progress, with 38 companies currently holding valid permits to test AVs with safety drivers in California. Zoox is currently one of only six companies permitted to test AVs without safety drivers in the state.
As the industry advances, Zoox has created a next-generation robotaxi by combining cutting-edge onboard computing with extensive simulation and development.
In the image at top, NVIDIA founder and CEO Jensen Huang stands with Zoox CEO Aicha Evans and Zoox cofounder and CTO Jesse Levinson in front of a Zoox robotaxi.
NVIDIA researchers used NVIDIA Edify, a multimodal architecture for visual generative AI, to build a detailed 3D desert landscape within a few minutes in a live demo at SIGGRAPH’s Real-Time Live event on Tuesday.
During the event — one of the prestigious graphics conference’s top sessions — NVIDIA researchers showed how, with the support of an AI agent, they could build and edit a desert landscape from scratch within five minutes. The live demo highlighted how generative AI can act as an assistant to artists by accelerating ideation and generating custom secondary assets that would otherwise have been sourced from a repository.
By drastically decreasing ideation time, these AI technologies will empower 3D artists to be more productive and creative — giving them the tools to explore concepts faster and expedite parts of their workflows. They could, for example, generate the background assets or 360 HDRi environments that the scene needs in minutes, instead of spending hours finding or creating them.
From Idea to 3D Scene in Three Minutes
Creating a full 3D scene is a complex, time-consuming task. Artists must support their hero asset with plenty of background objects to create a rich scene, then find an appropriate background and an environment map to light it. Due to time constraints, they’ve often had to make a trade-off between rapid results and creative exploration.
With the support of AI agents, creative teams can achieve both goals: quickly bring concepts to life and continue iterating to achieve the right look.
In the Real-Time Live demo, the researchers used an AI agent to instruct an NVIDIA Edify-powered model to generate dozens of 3D assets, including cacti, rocks and the skull of a bull — with previews produced in just seconds.
They next directed the agent to harness other models to create potential backgrounds and a layout of how the objects would be placed in the scene — and showcased how the agent could adapt to last-minute changes in creative direction by quickly swapping the rocks for gold nuggets.
With a design plan in place, they prompted the agent to create full-quality assets and render the scene as a photorealistic image in NVIDIA Omniverse USD Composer, an app for virtual world-building.
NVIDIA Edify Accelerates Environment Generation
NVIDIA Edify models can help creators focus on hero assets while accelerating the creation of background environments and objects using AI-powered scene generation tools. The Real-Time Live demo showcased two Edify models:
Edify 3D generates ready-to-edit 3D meshes from text or image prompts. Within seconds, the model can generate previews, including rotating animations of each object, to help creators rapidly prototype before committing to a specific design.
Edify 360 HDRi uses text or image prompts to generate up to 16K high-dynamic range images (HDRi) of nature landscapes, which can be used as backgrounds and to light scenes.
During the demo, the researchers also showcased an AI agent powered by a large language model, and USD Layout, an AI model that generates scene layouts using OpenUSD, a platform for 3D workflows.
At SIGGRAPH, NVIDIA also announced that two leading creative content companies are giving designers and artists new ways to boost productivity with generative AI using tools powered by NVIDIA Edify.
Shutterstock has launched in commercial beta its Generative 3D service, which lets creators quickly prototype and generate 3D assets using text or image prompts. Its 360 HDRi generator based on Edify also entered early access.
Getty Images updated its Generative AI by Getty Images service with the latest version of NVIDIA Edify. Users can now create images twice as fast, with improved output quality and prompt adherence, and advanced controls and fine-tuning.
Harnessing Universal Scene Description in NVIDIA Omniverse
The 3D objects, environment maps and layouts generated using Edify models are structured with USD, a standard format for describing and composing 3D worlds. This compatibility allows artists to immediately import Edify-powered creations into Omniverse USD Composer.
Within Composer, they can use popular digital content creation tools to further modify the scene by, for example, changing the position of objects, modifying their appearance or adjusting lighting.
Real-Time Live is one of the most anticipated events at SIGGRAPH, featuring about a dozen real-time applications including generative AI, virtual reality and live performance capture technology. Watch the replay below.
Enterprises are rapidly adopting generative AI, large language models (LLMs), advanced graphics and digital twins to increase operational efficiencies, reduce costs and drive innovation.
However, to adopt these technologies effectively, enterprises need access to state-of-the-art, full-stack accelerated computing platforms. To meet this demand, Oracle Cloud Infrastructure (OCI) today announced NVIDIA L40S GPU bare-metal instances available to order and the upcoming availability of a new virtual machine accelerated by a single NVIDIA H100 Tensor Core GPU. This new VM expands OCI’s existing H100 portfolio, which includes an NVIDIA HGX H100 8-GPU bare-metal instance.
Paired with NVIDIA networking and running the NVIDIA software stack, these platforms deliver powerful performance and efficiency, enabling enterprises to advance generative AI.
NVIDIA L40S Now Available to Order on OCI
The NVIDIA L40S is a universal data center GPU designed to deliver breakthrough multi-workload acceleration for generative AI, graphics and video applications. Equipped with fourth-generation Tensor Cores and support for the FP8 data format, the L40S GPU excels in training and fine-tuning small- to mid-size LLMs and in inference across a wide range of generative AI use cases.
The L40S GPU also has best-in-class graphics and media acceleration. Its third-generation NVIDIA Ray Tracing Cores (RT Cores) and multiple encode/decode engines make it ideal for advanced visualization and digital twin applications.
The L40S GPU delivers up to 3.8x the real-time ray-tracing performance of its predecessor, and supports NVIDIA DLSS 3 for faster rendering and smoother frame rates. This makes the GPU ideal for developing applications on the NVIDIA Omniverse platform, enabling real-time, photorealistic 3D simulations and AI-enabled digital twins. With Omniverse on the L40S GPU, enterprises can develop advanced 3D applications and workflows for industrial digitalization that will allow them to design, simulate and optimize products, processes and facilities in real time before going into production.
OCI will offer the L40S GPU in its BM.GPU.L40S.4 bare-metal compute shape, featuring four NVIDIA L40S GPUs, each with 48GB of GDDR6 memory. This shape includes local NVMe drives with 7.38TB capacity, 4th Generation Intel Xeon CPUs with 112 cores and 1TB of system memory.
These shapes eliminate the overhead of any virtualization for high-throughput and latency-sensitive AI or machine learning workloads with OCI’s bare-metal compute architecture. The accelerated compute shape features the NVIDIA BlueField-3 DPU for improved server efficiency, offloading data center tasks from CPUs to accelerate networking, storage and security workloads. The use of BlueField-3 DPUs furthers OCI’s strategy of off-box virtualization across its entire fleet.
OCI Supercluster with NVIDIA L40S enables ultra-high performance with 800Gbps of internode bandwidth and low latency for up to 3,840 GPUs. OCI’s cluster network uses NVIDIA ConnectX-7 NICs over RoCE v2 to support high-throughput and latency-sensitive workloads, including AI training.
“We chose OCI AI infrastructure with bare-metal instances and NVIDIA L40S GPUs for 30% more efficient video encoding,” said Sharon Carmel, CEO of Beamr Cloud. “Videos processed with Beamr Cloud on OCI will have up to 50% reduced storage and network bandwidth consumption, speeding up file transfers by 2x and increasing productivity for end users. Beamr will provide OCI customers video AI workflows, preparing them for the future of video.”
Single-GPU H100 VMs Coming Soon on OCI
The VM.GPU.H100.1 compute virtual machine shape, accelerated by a single NVIDIA H100 Tensor Core GPU, is coming soon to OCI. This will provide cost-effective, on-demand access for enterprises looking to use the power of NVIDIA H100 GPUs for their generative AI and HPC workloads.
A single H100 provides a good platform for smaller workloads and LLM inference. For example, one H100 GPU can generate more than 27,000 tokens per second for Llama 3 8B (up to 4x more throughput than a single A100 GPU at FP16 precision) with NVIDIA TensorRT-LLM at an input and output sequence length of 128 and FP8 precision.
The VM.GPU.H100.1 shape includes 2×3.4TB of NVMe drive capacity, 13 cores of 4th Gen Intel Xeon processors and 246GB of system memory, making it well-suited for a range of AI tasks.
“Oracle Cloud’s bare-metal compute with NVIDIA H100 and A100 GPUs, low-latency Supercluster and high-performance storage delivers up to 20% better price-performance for Altair’s computational fluid dynamics and structural mechanics solvers,” said Yeshwant Mummaneni, chief engineer of data management analytics at Altair. “We look forward to leveraging these GPUs with virtual machines for the Altair Unlimited virtual appliance.”
GH200 Bare-Metal Instances Available for Validation
OCI has also made available the BM.GPU.GH200 compute shape for customer testing. It features the NVIDIA Grace Hopper Superchip and NVLink-C2C, a high-bandwidth, cache-coherent 900GB/s connection between the NVIDIA Grace CPU and NVIDIA Hopper GPU. This provides over 600GB of accessible memory, enabling up to 10x higher performance for applications running terabytes of data compared to the NVIDIA A100 GPU.
Optimized Software for Enterprise AI
Enterprises have a wide variety of NVIDIA GPUs to accelerate their AI, HPC and data analytics workloads on OCI. However, maximizing the full potential of these GPU-accelerated compute instances requires an optimized software layer.
Optimized for NVIDIA GPUs, NIM pre-built containers offer developers improved cost of ownership, faster time to market and security. NIM microservices for popular community models, found on the NVIDIA API Catalog, can be deployed easily on OCI.
Performance will continue to improve over time with upcoming GPU-accelerated instances, including NVIDIA H200 Tensor Core GPUs and NVIDIA Blackwell GPUs.
Editor’s note: This post is part of the AI Decoded series, which demystifies AI by making the technology more accessible, and showcases new hardware, software, tools and accelerations for RTX PC users.
NVIDIA is spotlighting the latest NVIDIA RTX-powered tools and apps at SIGGRAPH, an annual trade show at the intersection of graphics and AI.
These AI technologies provide advanced ray-tracing and rendering techniques, enabling highly realistic graphics and immersive experiences in gaming, virtual reality, animation and cinematic special effects. RTX AI PCs and workstations are helping drive the future of interactive digital media, content creation, productivity and development.
ACE’s AI Magic
During a SIGGRAPH fireside chat, NVIDIA founder and CEO Jensen Huang introduced “James” — an interactive digital human built on NVIDIA NIM microservices — that showcases the potential of AI-driven customer interactions.
Using NVIDIA ACE technology and based on a customer-service workflow, James is a virtual assistant that can connect with people using emotions, humor and contextually accurate responses. Soon, users will be able to interact with James in real time at ai.nvidia.com.
James is a virtual assistant in NVIDIA ACE.
NVIDIA also introduced the latest advancements in the NVIDIA Maxine AI platform for telepresence, as well as companies adopting NVIDIA ACE, a suite of technologies for bringing digital humans to life with generative AI. These technologies enable digital human development with AI models for speech and translation, vision, intelligence, realistic animation and behavior, and lifelike appearance.
Maxine features two AI technologies that enhance the digital human experience in telepresence scenarios: Maxine 3D and Audio2Face-2D.
Developers can harness Maxine and ACE technologies to drive more engaging and natural interactions for people using digital interfaces across customer service, gaming and other interactive experiences.
Tapping advanced AI, NVIDIA ACE technologies allow developers to design avatars that can respond to users in real time with lifelike animations, speech and emotions. RTX GPUs provide the necessary computational power and graphical fidelity to render ACE avatars with stunning detail and fluidity.
With ongoing advancements and increasing adoption, ACE is setting new benchmarks for building virtual worlds and sparking innovation across industries. Developers tapping into the power of ACE with RTX GPUs can build more immersive applications and advanced, AI-based, interactive digital media experiences.
RTX Updates Unleash AI-rtistry for Creators
NVIDIA GeForce RTX PCs and NVIDIA RTX workstations are getting an upgrade with GPU accelerations that provide users with enhanced AI content-creation experiences.
For video editors, RTX Video HDR is now available through Wondershare Filmora and DaVinci Resolve. With this technology, users can transform any content into high dynamic range video with richer colors and greater detail in light and dark scenes — making it ideal for gaming videos, travel vlogs or event filmmaking. Combining RTX Video HDR with RTX Video Super Resolution further improves visual quality by removing encoding artifacts and enhancing details.
RTX Video HDR requires an RTX GPU connected to an HDR10-compatible monitor or TV. Users with an RTX GPU-powered PC can send files to the Filmora desktop app and continue to edit with local RTX acceleration, doubling the speed of the export process with dual encoders on GeForce RTX 4070 Ti or above GPUs. Popular media player VLC in June added support for RTX Video Super Resolution and RTX Video HDR, adding AI-enhanced video playback.
In addition, 3D artists are gaining more AI applications and tools that simplify and enhance workflows, including Replikant, Adobe, Topaz and Getty Images.
Replikant, an AI-assisted 3D animation platform, is integrating NVIDIA Audio2Face, an ACE technology, to enable improved lip sync and facial animation. By taking advantage of NVIDIA-accelerated generative models, users can enjoy real-time visuals enhanced by RTX and NVIDIA DLSS technology. Replikant is now available on Steam.
Adobe Substance 3D Modeler has added Search Asset Library by Shape, an AI-powered feature designed to streamline the replacement and enhancement of complex shapes using existing 3D models. This new capability significantly accelerates prototyping and enhances design workflows.
New AI features in Adobe Substance 3D integrate advanced generative AI capabilities, enhancing its texturing and material-creation tools. Adobe has launched the first integration of its Firefly generative AI capabilities into Substance 3D Sampler and Stager, making 3D workflows more seamless and productive for industrial designers, game developers and visual effects professionals.
For tasks like text-to-texture generation and prompt descriptions, Substance 3D users can generate photorealistic or stylized textures. These textures can then be applied directly to 3D models. The new Text to Texture and Generative Background features significantly accelerate traditionally time-consuming and intricate 3D texturing and staging tasks.
Powered by NVIDIA RTX Tensor Cores, Substance 3D can significantly accelerate computations and allows for more intuitive and creative design processes. This development builds on Adobe’s innovation with Firefly-powered Creative Cloud upgrades in Substance 3D workflows.
Topaz AI has added NVIDIA TensorRT acceleration for multi-GPU workflows, enabling parallelization across multiple GPUs for supercharged rendering speeds — up to 2x faster with two GPUs over a single GPU system, and scaling further with additional GPUs.
Getty Images has updated its Generative AI by iStock service with new features to enhance image generation and quality. Powered by NVIDIA Edify models, the latest enhancement delivers generation speeds set to reach around six seconds for four images, doubling the performance of the previous model, with speeds at the forefront of the industry. The improved Text-2-Image and Image-2-Image functionalities provide higher-quality results and greater adherence to user prompts.
Generative AI by iStock users can now also designate camera settings such as focal length (narrow, standard or wide) and depth of field (near or far). Improvements to generative AI super-resolution enhances image quality by using AI to create new pixels, significantly improving resolution without over-sharpening the image.
LLM-azing AI
ChatRTX — a tech demo that connects a large language model (LLM), like Meta’s Llama, to a user’s data for quickly querying notes, documents or images — is getting a user interface (UI) makeover, offering a cleaner, more polished experience.
ChatRTX also serves as an open-source reference project that shows developers how to build powerful, local, retrieval-augmented applications (RAG) applications accelerated by RTX.
ChatRTX is getting a interface (UI) makeover.
The latest version of ChatRTX, released today, uses the Electron + Material UI framework, which lets developers more easily add their own UI elements or extend the technology’s functionality. The update also includes a new architecture that simplifies the integration of different UIs and streamlines the building of new chat and RAG applications on top of the ChatRTX backend application programming interface.
End users can download the latest version of ChatRTX from the ChatRTX web page. Developers can find the source code for the new release on the ChatRTX GitHub repository.
Meta Llama 3.1-8B models are now optimized for inference on NVIDIA GeForce RTX PCs and NVIDIA RTX workstations. These models are natively supported with NVIDIA TensorRT-LLM, open-source software that accelerates LLM inference performance.
Dell’s AI Chatbots: Harnessing RTX Rocket Fuel
Dell is presenting how enterprises can boost AI development with an optimized RAG chatbot using NVIDIA AI Workbench and an NVIDIA NIM microservice for Llama 3. Using the NVIDIA AI Workbench Hybrid RAG Project, Dell is demonstrating how the chatbot can be used to converse with enterprise data that’s embedded in a local vector database, with inference running in one of three ways:
Locally on a Hugging Face TGI server
In the cloud using NVIDIA inference endpoints
On self-hosted NVIDIA NIM microservices
Learn more about the AI Workbench Hybrid RAG Project. SIGGRAPH attendees can experience this technology firsthand at Dell Technologies’ booth 301.
HP AI Studio: Innovate Faster With CUDA-X and Galileo
At SIGGRAPH, HP is presenting the Z by HP AI Studio, a centralized data science platform. Announced in October 2023, AI Studio has now been enhanced with the latest NVIDIA CUDA-X libraries as well as HP’s recent partnership with Galileo, a generative AI trust-layer company. Key benefits include:
Deploy projects faster: Configure, connect and share local and remote projects quickly.
Collaborate with ease: Access and share data, templates and experiments effortlessly.
Work your way: Choose where to work on your data, easily switching between online and offline modes.
Designed to enhance productivity and streamline AI development, AI Studio allows data science teams to focus on innovation. Visit HP’s booth 501 to see how AI Studio with RAPIDS cuDF can boost data preprocessing to accelerate AI pipelines. Apply for early access to AI Studio.
An RTX Speed Surge for Stable Diffusion
Stable Diffusion 3.0, the latest model from Stability AI, has been optimized with TensorRT to provide a 60% speedup.
A NIM microservice for Stable Diffusion 3 with optimized performance is available for preview on ai.nvidia.com.
There’s still time to join NVIDIA at SIGGRAPH to see how RTX AI is transforming the future of content creation and visual media experiences. The conference runs through Aug. 1.
Generative AI is transforming graphics and interactive experiences of all kinds. Make sense of what’s new and what’s next by subscribing to the AI Decoded newsletter.
In a highly anticipated fireside chat at SIGGRAPH 2024, NVIDIA founder and CEO Jensen Huang and Meta founder and CEO Mark Zuckerberg discussed the transformative potential of open source AI and AI assistants.
Zuckerberg kicked off the discussion by announcing the launch of AI Studio, a new platform that allows users to create, share and discover AI characters, making AI more accessible to millions of creators and small businesses.
“Every single restaurant, every single website will probably, in the future, have these AIs …” Huang said.
“…just like every business has an email address and a website and a social media account, I think, in the future, every business is going to have an AI,” Zuckerberg responded.
Zuckerberg has gotten it right before. Huang credited Zuckerberg and Meta with being leaders in AI, even if only some have noticed until recently.
“You guys have done amazing AI work,” Huang said, citing advancements from Meta in computer vision, language models, real-time translation. “We all use Pytorch, that comes out of Meta.”
The Importance of Open Source in Advancing AI
Zuckerberg highlighted the importance of open source in advancing AI — with the two business leaders emphasizing the importance of open platforms for innovation.
Meta has rapidly emerged as a leader in AI, putting it to work throughout its businesses — most notably with Meta AI, which is used across Facebook, Instagram and WhatsApp — and advancing open-source AI throughout the industry, most recently with the release of Llama 3.1.
The open-source model represents a significant investment of time and training resources. The largest version of Llama boasts 405 billion parameters and was trained on over 16,000 NVIDIA H100 GPUs.
“One of the things that drives quality improvements is it used to be that you have a different model for each type of content,” Zuckerberg explained.
“A the models get bigger and more general, that gets better and better. So, I kind of dream of one day like you can almost imagine all of Facebook or Instagram being like a single AI model that has unified all these different content types and systems together,” he added.
Zuckerberg sees collaboration as key to more advancements. In a blog post released last week, Zuckerberg wrote that the release of Llama 3.1 promises to be an “inflection point” in adopting open source in AI.
These advancements promise more tools to foster engagement, create compelling and personalized content — such as digital avatars — and build virtual worlds.
More broadly, the advancement of AI across a broad ecosystem promises to supercharge human productivity, for example, by giving every human on earth a digital assistant — or assistants — allowing people to live richer lives that they can interact with quickly and fluidly.
“I feel like I’m collaborating with WhatsApp,” Huang said. “Imagine I’m sitting here typing, and it’s generating the images as I’m going. I go back and change my words, and it’s generating other images.”
Vision for the Future
Looking ahead, both CEOs shared their visions for the future.
Zuckerberg expressed optimism about bringing AI together with the real world through eyeglasses — nothing his company’s collaboration with eyewear maker Luxotic — that can be used to help transform education, entertainment and work.
Huang emphasized how interacting with AIs is becoming more fluid, moving beyond just text-based interactions.
“Today’s AI is kind of turn-based. You say something, it says something back to you,” Huang said. In the future, AI could contemplate multiple options, or come up with a tree of options and simulate outcomes, making it much more powerful.”
Throughout the conversation, the two leaders playfully bantered about everything from fashion to steak sandwiches, ending the discussion by exchanging leather jackets.
Zuckerberg give Huang with a black leather shearling jacket with an enormous hood.
Huang gave Zuckerberg his own leather jacket, which he got from his wife, Lori, just for SIGGRAPH, quipping that it was just “two hours old.”
“Well this one’s yours,” Zuckerberg said with a smile. “This is worth more because it’s used.”
NVIDIA GeForce NOW (@NVIDIAGFN) 
