Posts in category: nVidia AI

NVIDIA is joining the U.S. government’s launch of the Partnership for Global Inclusivity on AI (PGIAI), providing Deep Learning Institute training, GPU credits and hardware and software grants in developing countries.

The partnership was announced today in New York at the U.N. General Assembly by U.S. Secretary of State Antony Blinken. The effort aims to harness the potential of artificial intelligence to advance sustainable development around the world.

“Artificial Intelligence is driving the next industrial revolution, offering incredible potential to contribute meaningful progress on sustainable development goals,” said Ned Finkle, VP of NVIDIA government affairs. “NVIDIA is committed to empowering communities to use AI to innovate through support for research, education and small and medium size enterprises.”

NVIDIA is joined by Amazon, Anthropic, Apple,  Google, IBM, Meta, Microsoft and OpenAI in the initiative.

Members of the partnership have pledged to provide access to training, compute and other AI tools to drive sustainable development and improved quality of life in developing countries.

The PGIAI initiative recognizes that equitable AI requires understanding and respect for the diverse cultures, languages and traditions of the communities where services are provided. With that criteria, PGIAI members will focus on increasing access to AI models, APIs, compute credit and other AI tools, as well as technical training and access to local datasets.

Under this partnership, NVIDIA will provide approximately $10 million in free training to universities and developers to help support AI for local solutions and development goals.

NVIDIA’s global Inception program supports nearly 5,000 start-ups in emerging economies with technical expertise, go-to-market support, hardware and software discounts, and access to free cloud computing credits provided by NVIDIA partners.

In 2024, Inception provided access to more than $60 million worth of free cloud compute credits through partners to start-ups in emerging economies.

CTA: Learn more about the NVIDIA Inception program for startups. Learn more about the NVIDIA Deep Learning Institute.

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The Wellcome Sanger Institute, a key contributor to the international Human Genome Project, is turning to NVIDIA accelerated computing to save energy while saving lives.

With one of the world’s largest sequencing facilities, the U.K.-based institute has read more than 48 petabases — or 48 quadrillion base pairs — of DNA and RNA sequences to uncover crucial insights into health and disease.

Its Cancer, Ageing and Somatic Mutation (CASM) program sequences and analyzes tens of thousands of cancer genomes a year to study the mutational processes driving cancer formation, as well as genetic variations that determine treatment effectiveness.

To tackle such large-scale initiatives, the Sanger Institute is exploring the use of an NVIDIA DGX system with NVIDIA Parabricks, a scalable genomics analysis software suite that taps into accelerated computing to process data in just minutes.

“The Sanger Institute handles hundreds of thousands of somatic samples annually,” said Jingwei Wang, principal software developer for CASM at the Wellcome Sanger Institute. “NVIDIA accelerated computing and Parabricks will save us considerable time, cost and energy when analyzing samples, and we’re excited to explore NVIDIA’s advanced architectures, such as NVIDIA Grace and Grace Hopper, for even higher performance and efficiency.”

Reducing Runtime and Energy Consumption

The Sanger Institute develops high-throughput models of cancer samples for genome-wide functional screens and drug testing.

NVIDIA accelerated computing and software drastically reduce the institute’s analysis runtime and energy consumption per genome.

To accelerate genomic analysis with Burrows-Wheeler Aligner (BWA), a software package for mapping DNA sequences against a large reference genome, Sanger uses its proprietary CaVEMan workflow running on CPUs and is tapping into Parabricks on NVIDIA GPUs.

The institute reduced runtime 1.6x, costs 24x and energy consumption up to 42x — using one NVIDIA DGX system compared with 128 dual-socket CPU servers.

About 125 million CPU hours are consumed per 10,000 genomes sequenced by the institute annually.

This means that the Sanger Institute could, each year, save $1 million and 1,000 megawatt-hours by switching to using BWA with Parabricks on GPUs. That’s about the amount of energy needed to power an average American home for a century.

Collaborating With Industry Leaders

The Sanger Institute’s NVIDIA-accelerated sequencing lab can be considered an AI factory, where data comes in and intelligence comes out.

AI factories are next-generation data centers that host advanced, full-stack accelerated computing platforms for the most computationally intensive tasks.

As it explores crucial scientific questions to discover new cancer genes and mutational processes, the Sanger Institute is boosting operational and energy efficiency by using NVIDIA infrastructure for its AI factory.

In addition, companies and organizations building AI factories are participating in cross-industry collaborations with leaders like Schneider Electric, an energy management and automation company, to optimize data center designs for running demanding workloads in the most energy-efficient way.

The Sanger Institute is collaborating with Schneider Electric to minimize data center downtime and equip the DNA sequencing lab’s data center with uninterruptible power supplies and cooling equipment, among other technologies pivotal to reducing energy consumption.

At the NVIDIA GTC conference in March, Schneider Electric announced it’s helping organizations across industries optimize infrastructure by releasing AI data center reference designs tailored for NVIDIA accelerated computing clusters.

The reference designs — built for data processing, engineering simulation, electronic design automation, computer-aided drug design and generative AI — will focus on high-power distribution, liquid-cooling systems and other aspects of scalable, high-performance, sustainable data centers.

In an NYC Climate Week panel this week hosted by The Economist, representatives from Sanger, Schneider Electric and NVIDIA will talk about their work.

Learn more about sustainable computing and the Sanger Institute’s potentially life-saving work.

Featured image courtesy of the Wellcome Sanger Institute.

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A committee of experts from top U.S. medical centers and research institutes is harnessing NVIDIA-powered federated learning to evaluate the impact of federated learning and AI-assisted annotation to train AI models for tumor segmentation.

Federated learning is a technique for developing more accurate, generalizable AI models trained on data across diverse data sources without mitigating data security or privacy. It allows several organizations to collaborate on the development of an AI model without sensitive data ever leaving their servers.

“Due to privacy and data management constraints, it’s growing more and more complicated to share data from site to site and aggregate it in one place — and imaging AI is developing faster than research institutes can set up data-sharing contracts,” said John Garrett, associate professor of radiology at the University of Wisconsin–Madison. “Adopting federated learning to build and test models at multiple sites at once is the only way, practically speaking, to keep up. It’s an indispensable tool.”

Garrett is part of the Society for Imaging Informatics and Medicine (SIIM) Machine Learning Tools and Research Subcommittee, a group of clinicians, researchers and engineers that aims to advance the development and application of AI for medical imaging. NVIDIA is a member of SIIM, and has been collaborating with the committee on federated learning projects since 2019.

“Federated learning techniques allow enhanced data privacy and security in compliance with privacy regulations like GDPR, HIPAA and others,” said committee chair Khaled Younis. “In addition, we see improved model accuracy and generalization.”

To support their latest project, the team — including collaborators from Case Western, Georgetown University, the Mayo Clinic, the University of California, San Diego, the University of Florida and Vanderbilt University — tapped NVIDIA FLARE (NVFlare), an open-source framework that includes robust security features, advanced privacy protection techniques and a flexible system architecture.

Through the NVIDIA Academic Grant Program, the committee received four NVIDIA RTX A5000 GPUs, which were distributed across participating research institutes to set up their workstations for federated learning. Additional collaborators used NVIDIA GPUs in the cloud and in on-premises servers, highlighting the flexibility of NVFLare.

Cracking the Code for Federated Learning

Each of six participating medical centers provided data from around 50 medical imaging studies for the project, focused on renal cell carcinoma, a kind of kidney cancer.

“The idea with federated learning is that during training we exchange the model rather than exchange the data,” said Yuankai Huo, assistant professor of computer science and director of the Biomedical Data Representation and Learning Lab at Vanderbilt University.

In a federated learning framework, an initial global model broadcasts model parameters to client servers. Each server uses those parameters to set up a local version of the model that’s trained on the organization’s proprietary data. Then, updated parameters from each of the local models are sent back to the global model, where they’re aggregated to produce a new global model. The cycle repeats until the model’s predictions no longer improve with each training round.

The group experimented with model architectures and hyperparameters to optimize for training speed, accuracy and the number of imaging studies required to train the model to the desired level of precision.

AI-Assisted Annotation With NVIDIA MONAI 

In the first phase of the project, the training data used for the model was labeled manually. For the next phase, the team is using NVIDIA MONAI for AI-assisted annotation to evaluate how model performance differs with training data segmented with the help of AI compared to traditional annotation methods.

“The biggest struggle with federated learning activities is typically that the data at different sites is not tremendously uniform. People use different imaging equipment, have different protocols and just label their data differently,” said Garrett. “By training the federated learning model a second time with the addition of MONAI, we aim to find if that improves overall annotation accuracy.”

The team is using MONAI Label, an image-labeling tool that enables users to develop custom AI annotation apps, reducing the time and effort needed to create new datasets. Experts will validate and refine the AI-generated segmentations before they’re used for model training.

Data for both the manual and AI-assisted annotation phases is hosted on Flywheel, a leading medical imaging data and AI platform that has integrated NVIDIA MONAI into its offerings.

Once the project is complete, the team plans to publish their methodology, annotated datasets and pretrained model to support future work.

“We’re interested in not just exploring these tools,” Garrett said, “but also publishing our work so others can learn and use these tools throughout the medical field.”

Apply for an NVIDIA Academic Grant

The NVIDIA Academic Grant Program advances academic research by providing world-class computing access and resources to researchers. Applications are now open for full-time faculty members at accredited academic institutions who are using NVIDIA technology to accelerate projects in simulation and modeling, generative AI and large language models.

Future application cycles will focus on projects in data science, graphics and vision, and edge AI — including federated learning.

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In a surprise appearance at T-Mobile’s Capital Markets Day, NVIDIA founder and CEO Jensen Huang shared a bold vision for the future of telecommunications.

“We’ve fused signal processing and AI,” Huang declared during a fireside chat with T-Mobile CEO Mike Sievert, speaking to an audience of press, analysts and investors. “This is going to be a great new growth opportunity for the telecommunications industry.”

Huang’s remarks came alongside NVIDIA’s announcement of its groundbreaking AI Aerial platform, which promises to reshape wireless networks by integrating AI and radio access networks, AI-RAN.

The platform is designed to optimize network performance, efficiency and new revenue potential, such as AI-computing-as-a-service during periods when network infrastructure is underutilized, maximizing the return on assets.

During the conversation, Huang emphasized the importance of AI in shaping the future of telecommunications, particularly highlighting the role of AI-RAN in optimizing and scaling network performance.

Fusing radio computing and AI computing into one architecture allows companies to apply AI models to optimize signal quality across diverse environments, Huang explained.

He emphasized that this fusion would lead to improved network efficiency and new growth opportunities for the telecommunications industry,

“We could teach these AI models how to optimize signal quality in hundreds of thousands of virtual cities,” Huang said.

AI-RAN aligns with NVIDIA’s broader vision to make AI an integral part of network infrastructure, enabling telecommunications providers to unlock new revenue streams and deliver enhanced experiences through generative AI, robotics and autonomous technologies.

Huang underscored the synergies between NVIDIA and T-Mobile, particularly their collaboration on the newly announced AI-RAN Innovation Center, as co-authors of transformation. The AI-RAN Innovation Center, developed with T-Mobile, Ericsson and Nokia, is set to accelerate the commercialization of AI-RAN technologies.

Every radio operates in a unique and constantly changing world environment. This is where deep reinforcement learning algorithms embedded into radio signal processing make complex computations simpler with AI to help deliver a customer-centric network experience.

Sievert emphasized how virtualizing RAN into the cloud will create new business opportunities. He explained that AI workloads will increasingly require compute power located close to the customer, leveraging underutilized network resources.

Huang also highlighted the crucial role AI will play in making networks more energy-efficient, emphasizing the need for sustainable technology as the demand for data and connectivity grows.

“We have to use AI to reduce energy consumption,” Huang said. “Everything that we accelerate, everything that we teach an AI model to do [we] will do a lot more energy efficiently.”

As Huang explained, by simulating  AI models in virtual environments with accurate physics and then emulating them in the real world, NVIDIA maximizes energy efficiency. This approach underpins the NVIDIA AI Aerial suite of platforms for designing, training and deploying AI-driven cellular networks for AI.

With NVIDIA AI Aerial now supporting a growing ecosystem of partners this collaboration marks a milestone in the telecom industry’s journey toward a future powered by AI.

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GeForce NOW makes gamers’ fantasies a reality by bringing top titles to the cloud. This week, the award-winning FINAL FANTASY XVI is available for members to stream at launch.

Catch 11 bit studios’ city-survival game Frostpunk 2 before it launches with early access on GeForce NOW.

It’s part of seven new games joining the expansive GeForce NOW library.

Eikonic Adventure 

Dive into the richly crafted world of Valisthea in FINAL FANTASY XVI, the latest mainline entry in Square Enix’s renowned role-playing game series. This epic action RPG unfolds in a once-glorious land blessed by the light of the Mothercrystals that’s now slowly succumbing to the mysterious Blight.

Play as Clive Rosfield as he navigates a dark fantasy filled with political intrigue and magical battles against Eikons, powerful manifestations of elemental forces. Eikons are wielded by Dominants, individuals who possess incredible strength and abilities.

Featuring exhilarating real-time combat, the game allows players to unleash devastating moves by chaining together attack combos with seamless fluidity. With its gripping story, stunning visuals and intense gameplay, FINAL FANTASY XVI offers an unforgettable experience for new and longtime fans of the series alike.

Streaming the game with GeForce NOW, explore the captivating world of Valisthea without needing to worry about hardware specs or download space. Ultimate members can even stream at up to 4K resolution to experience the full visual splendor of the game, making every battle and cinematic moment even more engaging and memorable. Series newcomers can try the demo on GeForce NOW before purchasing the full game.

Winter Is Coming

The sequel to the hit title Frostpunk will be available for members to stream at launch on Friday, Sept. 20. Members can dive into the frigid dystopia now with Advanced Access to Frostpunk 2 on GeForce NOW for those that preorder the Deluxe Edition on Steam and Xbox.

Frostpunk 2 builds on the critically acclaimed original, challenging newcomers and veterans of the series to lead a resource-starved civilization in a world locked in an eternal winter. The sequel brings more complex and expanded city-building mechanics and intricate political scenarios. Make tough choices to keep citizens alive — and somewhat happy — while navigating the harsh realities of this frozen world.

Experience Frostpunk 2 in all its icy glory on GeForce NOW and brave the eternal winter without breaking a sweat over hardware specs. Chill out with a Priority or Ultimate membership for longer gaming sessions over free users to develop intricate, sprawling cities.

Let’s Get Greedy

Dive into the high-stakes world of PAYDAY 3 as the latest downloadable content and final Year 1 chapter of the game, Fear and Greed, is available for members to stream now. Drop into the heart of Wall Street to pull off the ultimate insider trading scheme, uncover conspiracies and lead the Payday Gang to hit Concord’s stocks and bring it all crumbling to the ground.

Members can look for the following games available to stream in the cloud this week:

• Frostpunk 2 (New release on Steam and Xbox available on PC Game Pass, Sept. 20)
• FINAL FANTASY XVI (New release on Steam and Epic Games Store, Sept. 17)
• The Plucky Squire (New release on Steam, Sept. 17)
• Dead Rising Deluxe Remaster (New release on Steam, Sept. 18)
• Romancing SaGa 2: Revenge of the Seven (Demo releases on Steam, Sept. 18)
• The Legend of Heroes: Trails Through Daybreak (Steam)
• REKA (Steam)

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

Ever feel like you’re just one challenge away from a total game-changer?

…or is it just us living in an action-packed fantasy?

— NVIDIA GeForce NOW (@NVIDIAGFN) September 18, 2024

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All the electricity that powers NVIDIA’s global operations will come from renewable sources by the end of January.

It’s the right fuel for the company’s mission: to help customers and partners harness AI and accelerated computing for sustainable growth.

This week, world leaders gather in New York City to mark Climate Week 2024. It’s a good time to take stock of recent gains in energy efficiency in fields from manufacturing and cloud computing to healthcare and beyond.

Foxconn Saves Energy With Digital Twins

Foxconn, the world’s largest electronics manufacturer, is using accelerated computing and AI to build a digital twin of a new factory in Mexico, where it will train its robots and define production processes.

“Our digital twin will guide us to new levels of automation and industrial efficiency, saving time, cost and energy,” said Young Liu, chairman of Foxconn, which estimates a 30% annual energy savings.

It’s the latest company to employ software from the Siemens Xcelerator portfolio including Teamcenter and NVIDIA Omniverse, a platform for developing 3D workflows and applications based on OpenUSD.

“We will revolutionize how products and experiences are designed, manufactured and serviced,” said Roland Busch, president and CEO of Siemens AG. “In collaboration with NVIDIA, we will bring accelerated computing, generative AI and Omniverse integration across the Siemens Xcelerator portfolio.”

Siemens and NVIDIA executives will talk about their sustainability efforts in a Sept. 25 Climate Week event moderated by TIME magazine.

Cloud Services Increase Efficiency  

Cloud computing services are also racking up advances in energy efficiency.

An e-commerce website uses NVIDIA AI to connect hundreds of millions of shoppers a day to the products they need. After migrating from CPUs to GPUs, it achieved significantly lower latency with a 33x speedup and nearly 12x energy-efficiency improvement.

A popular video conferencing application captions several hundred thousand virtual meetings an hour. By switching from CPUs to GPUs, throughput increased from just three to 200 queries per second — a 66x speedup and 25x energy-efficiency improvement.

To meet sustainability goals, service providers and their customers are increasingly turning to renewable energy sources.

For example, Equinix is the first global data center provider to publish targets to become climate neutral using 100% renewable energy by 2030. Currently, renewables make up 96% of the energy it uses, giving customers access to technologies such as NVIDIA DGX systems for sustainable, private AI.

The DGX systems use NVIDIA H100 Tensor Core GPUs, which offer up to 4x more energy efficiency than previous models. Equinix employs advanced liquid cooling to reduce power and water consumption.

The evolution of the data center will be discussed at a Climate Week event hosted by NVIDIA and Crusoe Energy Systems, a company that builds and operates clean computing infrastructure.

Decoding Cancer While Saving Energy

Healthcare companies are adopting AI and accelerated computing to help them understand and treat diseases.

For instance, the Wellcome Sanger Institute runs one of the largest genome sequencing facilities in the world. Its cancer program sequences and analyzes tens of thousands of cancer samples.

Using NVIDIA Parabricks software on NVIDIA DGX systems reduces its run times by 1.6x, capital costs by 24x and energy consumption by up to 42x. That amounts to potential savings of $1 million and 1,000 megawatt-hours a year.

The latest version of Parabricks, released in mid-September, can further enhance such work.

“The Sanger Institute handles hundreds of thousands of samples annually,” said Jingwei Wang, a principal software developer at Wellcome Sanger in a profile describing its work. “With NVIDIA GPUs and Parabricks accelerated genomic analysis software, we will save considerable time, cost and energy analyzing them.”

Expanding the Sustainability Ecosystem 

In addition to enabling efficiency gains for customers, NVIDIA is nurturing a broad ecosystem focused on sustainability.

For example, a collaboration with the United Nations announced last year has already trained more than 14,000 data scientists on how to design AI models for early flood detection.

Entrepreneurs increasingly see opportunities here, too.

Sustainable Futures, a member of the NVIDIA Inception program, now includes more than a thousand startups pioneering new paths to energy efficiency. They apply a mix of AI, accelerated computing and open platforms like NVIDIA Earth-2 to speed climate and weather predictions.

Savings Span Global Industries

These examples provide a taste of what’s happening and what’s to come.

“The generative AI revolution is poised to impact every industry and enable a new era of productivity and sustainability by unlocking efficiencies and resource optimization across sectors,” said NVIDIA founder and CEO Jensen Huang in the company’s latest sustainability report.

It’s a reality independent analysts recognize.

“Even if the predictions that data centers will soon account for 4% of global energy consumption become a reality, AI is having a major impact on reducing the remaining 96% of energy consumption,” said a report from Lisbon Council Research, a nonprofit formed in 2003 that studies economic and social issues.

45,000x Efficiency Gain in AI Inference

NVIDIA works continuously to expand and optimize its full stack of technologies to enable greater efficiencies.

In the last eight years, the NVIDIA platform has gotten 45,000x more energy efficient when processing large language models. If the efficiency of cars improved that much, cars would get 280,000 miles per gallon — enough to drive to the moon on less than a gallon of gas.

Speedups over CPUs from 20x to 160x — and their associated energy savings — are available across the gamut of workloads from data processing to computer vision the NVIDIA accelerated computing platform serves. That’s why accelerated computing is often called sustainable computing.

Expanding Climate Week’s Agenda

Rallying support for sustainability, NVIDIA and partners are taking part in a handful of other Climate Week events.

They include a Climate AI Summit with Salesforce and a Climate Science Fair with about 30 startups, many using NVIDIA technologies. The Science Fair will give attendees an up-close look at how Earth-2 enables simulation on a planetary scale.

It’s another small step toward helping people understand how to use AI and accelerated computing to address climate change.

“Accelerated computing is how to meet the massive demand for computing power sustainably and cost-effectively,” Huang said.

Learn more about how NVIDIA’s technologies support corporate sustainability.

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Telecommunications providers are transforming beyond voice and data services with an AI computing infrastructure to optimize wireless networks and serve the next-generation needs of generative AI on mobile, robots, autonomous vehicles, smart factories, 5G and much more.

Launched today, NVIDIA AI Aerial is a suite of accelerated computing software and hardware for designing, simulating, training and deploying AI radio access network technology (AI-RAN) for wireless networks in the AI era.

The platform will become a critical foundation to allow network optimization at scale to serve the demands of a host of new services. This will provide significant savings in total cost of ownership and open telecom operators to new revenue opportunities for enterprise and consumer services.

NVIDIA AI Aerial enables telecommunications service providers to support teleoperations for manufacturing robots and autonomous vehicles, computer vision in manufacturing and agriculture, logistics, generative AI-driven co-pilots and personal assistants, emerging spatial computing applications, robotic surgery, 3D collaboration, and 5G and 6G advances.

Driving Networks of the Future With AI-RAN

NVIDIA AI Aerial is the world’s first AI-RAN platform capable of hosting generative AI and RAN traffic, as well as integrating AI into network optimization.

AI-RAN offers high-performance and energy-efficient software-defined RAN, improved network experience and new revenue opportunities with edge AI applications to host internal and third-party generative AI applications.

AI-RAN is foundational to the multipurpose networks of tomorrow that rely on AI-powered telecommunications capabilities.

Harnessing NVIDIA AI Aerial for Telecom Industry

The NVIDIA AI Aerial platform offers access to a full suite of capabilities, including a high-performance, software-defined RAN along with training, simulation and inference so that telecom operators can participate at any stage of development to deployment for next-generation wireless networks.

Some capabilities in the NVIDIA AI Aerial platform include:

• NVIDIA Aerial CUDA-Accelerated RAN includes software libraries to enable partners to develop and deploy high-performance virtualized RAN workloads on NVIDIA-accelerated compute platforms.
• NVIDIA Aerial AI Radio Frameworks include PyTorch- and TensorFlow-based software libraries to develop and train models for improving spectral efficiency and adding new capabilities to 5G and 6G radio signal processing. This also includes NVIDIA Sionna, a link-level simulator that provides development and training of neural network-based 5G and 6G radio algorithms.
• NVIDIA Aerial Omniverse Digital Twin (AODT) is a system-level network digital twin development platform. AODT enables physically accurate simulations of wireless systems — from a single base station to a comprehensive network with a large number of base stations covering an entire city. It incorporates software-defined RAN (Aerial-CUDA Accelerated RAN) and user-equipment simulators, along with realistic terrain and object properties of the physical world.

NVIDIA AI Aerial and AI RAN Innovation Center  

NVIDIA is collaborating with T-Mobile, Ericsson and Nokia to accelerate the commercialization of AI-RAN with the establishment of the AI-RAN Innovation Center.

The center will tap into key capabilities of the NVIDIA AI Aerial platform. The collaboration is focused on bringing RAN and AI innovation closer together to deliver transformational network experiences for customers through the development of AI-RAN [link to the TMUS PR release on AI-RAN].

“AI-RAN is set to revolutionize the telecom industry, and the opening of the AI-RAN Innovation Center will help to take us on this journey by driving industry collaboration,” said Tommi Uitto, president of Mobile Networks at Nokia. “By bringing together leading companies in the telecom and AI industries, we can unlock the full potential of AI in our networks, improving performance, reducing costs and creating new opportunities for our customers. We are confident that AI-RAN will be a key driver of innovation in the future, and we are excited to be part of this revolution together with NVIDIA.”

“Ericsson has invested in our AI-RAN solution, allowing communications service providers to deploy portable RAN software running across multiple platforms. We are now evaluating the performance and cost of NVIDIA accelerated computing in this context”, said Fredrik Jejdling, EVP and head of Business Area Networks at Ericsson

NVIDIA AI Aerial Ecosystem

Key partners of the growing ecosystem of NVIDIA AI Aerial include Softbank and Fujitsu.

Ansys and Keysight are using NVIDIA Aerial Omniverse Digital Twin for testing and simulation systems, while partners and academia such as Deepsig, ETH-Zurich, Northeastern University and Samsung are collaborating on 6G research and NVIDIA Aerial AI Radio Frameworks.

Cloud stack software providers such as Aarna Networks, Canonical, Red Hat and Wind River; networking stack providers like Arrcus network and server infrastructure providers like Dell Technologies, Hewlett Packard Enterprise and Supermicro are key partners for NVIDIA AI Aerial. Edge Solution providers like Vapor.io, and system integrators like World Wide Technology, with its AI Proving Ground, [insert link to their blog] are accelerating decision-making for AI solutions.

Learn more about NVIDIA AI Aerial

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Companies in the US spend $15bn annually on talent acquisition. The most important metric in recruitment advertising is the conversion from the paid click on the job platform to the application the employer receives. Industry-wide, apply conversion is just 5%. Redirection of the candidate from the job platform to the company site is the biggest cause of abandonment; this step has a 70% bounce rate. In this episode of NVIDIA’s AI Podcast, host Noah Kravitz speaks with Mikhil Raja, Cofounder and CEO of SonicJobs, about how they have built AI Agents to enable candidates to complete applications directly on job platforms, without redirection, boosting completion rates to 26% from 5%. Raja delves deep into SonicJobs’ cutting-edge technology, which merges traditional AI with large language models (LLMs) to understand and interact with job application web flows. He also emphasizes the importance of fine-tuning foundational models to achieve more impactful and scalable innovations.

SonicJobs is a member of the NVIDIA Inception program for startups.

Time Stamps

1:19: Why applying for a job remains a Web 1.0 experience — and how SonicJobs’ AI Agents are changing this

6:06: Explanation of SonicJobs’ technology and the benefits to users and companies

9:03: The evolution of AI Agents from AutoGPT to Verticalized B2B solutions

11:33: How SonicJobs realized the approach it should take with Agentic AI

15:18: Scaling SonicJobs’ AI Agent and the adaptive learning flywheel

17:45: Raja discusses the need for accuracy including fine-tuning foundational models

20:45: Framework for how SonicJobs’ Verticalized AI Agent solution  can be applied to further Verticals

23:23: Advice Raja would give to a company that’s currently trying to hire

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At TwitchCon — a global convention for the Twitch livestreaming platform—livestreamers and content creators this week can experience the latest technologies for accelerating creative workflows and improving video quality.

That includes the beta release of Twitch Enhanced Broadcasting support for HEVC when using the NVIDIA encoder.

Content creators can also use the NVIDIA Broadcast app, eighth-generation NVIDIA NVENC and RTX-powered optimizations in streaming and video editing apps to enhance their productions.

Plus, the September NVIDIA Studio Driver, designed to optimize creative apps, is now ready for download. Studio Drivers undergo extensive testing to ensure seamless compatibility while enhancing features, automating processes and accelerating workflows.

Twitch Enhanced Broadcasting With HEVC

The tradeoff between higher-resolution video quality and reliable streaming is a common issue livestreamers struggle with.

Higher-quality video provides more enjoyable viewing experiences but can cause streams to buffer for viewers with lower bandwidth or older devices. Streaming lower-bitrate video allows more people to watch content seamlessly but introduces artifacts that can interfere with viewing quality.

To address this issue, NVIDIA and Twitch collaborated to develop Twitch Enhanced Broadcasting. The feature adds the capability to send multiple streams — different versions of encoded video with different resolutions or bitrates — directly from NVIDIA GeForce RTX-equipped PCs or NVIDIA RTX workstations to deliver the highest-quality video a viewer’s internet connection can handle.

Twitch supports HEVC (H.265) in the Enhanced Broadcasting closed beta. With the NVIDIA encoder, Twitch streamers get 25% improved efficiency and quality over H.264.

This means that video will look as if it were being streamed with 25% more bitrate — in higher quality and with reduced artifacts or encoding errors. The feature is ideal for streaming fast-paced gameplay, enabling cleaner, sharper video with minimal lag.

Because all stream versions are generated with a dedicated hardware encoder on GeForce RTX GPUs, the rest of the system’s GPU and CPU are free to focus on running games more smoothly to maximize performance.

Learn how to get started on twitch.com.

AI-Enhanced Microphones and Webcams

Streaming is easier than ever with NVIDIA technologies.

For starters, PC performance and video quality are incredibly high quality thanks to NVIDIA’s dedicated encoder. And, NVIDIA GPUs include Tensor Cores that efficiently run AI.

Livestreamers can use AI to enhance their hardware peripherals and devices, which is especially helpful for those who haven’t had the time or resources to assemble extensive audio and video setups.

NVIDIA Broadcast transforms any home office or dorm room into a home studio — without the need to purchase specialized equipment. Its AI-powered features include Noise and Echo Removal for microphones, and Virtual Background, Auto Frame, Video Noise Removal and Eye Contact for cameras.

Livestreamers can download the Broadcast app or access its effects across popular creative apps, including Corsair iCUE, Elgato Camera Hub, OBS, Streamlabs, VTube Studio and Wave Link.

Spotlight the Highlights

GeForce RTX GPUs make it lightning-fast to edit and enhance video footage on the most popular video editing apps, from Adobe Premiere Pro to CapCut Pro.

Streamers can use AI-powered, RTX-accelerated features like Enhance Speech to remove noise and improve the quality of dialogue clips; Auto Reframe to automatically size social media videos; and Scene Edit Detection to break up long videos, like B-roll stringouts, into individual clips.

NVIDIA encoders help turbocharge the export process. For those looking for extreme performance, the GeForce RTX 4070 Ti GPU and up come equipped with dual encoders that can be used in parallel to halve export times on apps like CapCut, the most widely used video editing app on TikTok.

Clearer, Sharper Viewing Experiences With RTX Video

NVIDIA RTX Video — available exclusively for NVIDIA and GeForce RTX GPU owners — can turn any online and native video into pristine 4K high dynamic range (HDR) content with two technologies: Video Super Resolution and Video HDR.

RTX Video Super Resolution de-artifacts and upscales streamed video to remove errors that occur during encoding or transport, then runs an AI super-resolution effect. The result is cleaner, sharper video that’s ideal for streaming on platforms like YouTube and Twitch.

Many users have HDR displays, but there isn’t much HDR content online. RTX Video HDR addresses this by turning any standard dynamic range (SDR) video into HDR10 quality that delivers a wider range of brights and darks and makes visuals more vibrant and colorful. This feature is especially helpful when watching dark-lit scenes in video games.

RTX Video HDR requires an RTX GPU connected to an HDR10-compatible monitor or TV. For more information, see the RTX Video FAQ.

Check out TwitchCon — taking place in San Diego and online from Sept. 20-22 — for the latest streaming updates. 

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A new AI innovation hub for developers across Tunisia launched today in Novation City, a technology park that’s designed to cultivate a vibrant, innovation ecosystem in mechatronics — an industry encompassing IT, mechanics and electronics — and to foster synergy between education, research and industry in the North African country.

Built in collaboration with the NVIDIA Deep Learning Institute (DLI), the hub offers the training, technologies and business networks needed to help drive AI adoption across the continent.

The hub’s launch is part of NVIDIA’s efforts to train 100,000 developers across Africa through the DLI over the next three years — a goal that’s about a quarter complete today.

Located in Sousse — a coastal city in central Tunisia that’s surrounded by universities, startups and other organizations with a strong focus on STEM and AI — the hub includes complimentary access to NVIDIA DLI courses on topics such as generative AI, accelerated computing and data science.

Through its AI, industry 4.0 and smart transport centers of excellence, Novation City provides cutting-edge resources and access to NVIDIA DGX infrastructure for AI startups and researchers. Novation City also hosts organized activities to drive ecosystem growth, such as hackathons and specialized training sessions. It’s all brought together in this new environment conducive to AI learning, experimentation and deployment.

“Novation City has launched several key AI initiatives to strengthen the ecosystem, with NVIDIA’s support being instrumental in empowering AI startups and advancing AI skills,” said Anas Rochdi, chief innovation officer at Novation City. “This year, we deployed Tunisia’s first NVIDIA DGX system and launched major academic initiatives in collaboration with the NVIDIA Deep Learning Institute, aiming to train more than 1,000 developers in one year.”

Novation City also runs several startup accelerator programs, and more than 10 participating companies are members of NVIDIA Inception, a free program that nurtures cutting-edge startups.

Tunisia Drives Innovation in STEM and AI Education

Tunisia’s education system has traditionally emphasized STEM, especially mathematics and the sciences, according to Wei Xiao, who leads NVIDIA’s developer relations team for startups, enterprises and universities in the Middle East and Africa.

“Tunisia has a rich history of valuing knowledge and scholarship, dating back to ancient Carthage and the Islamic Golden Age,” Xiao said. “And the nation’s curriculum is rigorous, creating a solid foundation for advanced studies in STEM fields.”

This has made the country — well-situated to serve as a gateway between Europe, Africa and the Middle East (EMEA) — a thriving ecosystem for innovation, entrepreneurship and research. Novation City and NVIDIA aim to bolster the ecosystem even further through the new AI innovation hub.

Fostering collaboration between academia, industry and government, the initiative is funded by French and German development agencies, the Tunisian government, the World Bank and the European Union, as well as several enterprises.

And the hub comes at a time when Tunisia has adopted a national strategy for AI and digitalization — which includes promoting AI education and research — as part of a broader vision to position the nation as a digital leader in Africa. For example, the University of Tunis this month launched the nation’s first public institute specializing in AI.

Partners Foster Sovereign AI in Tunisia and Beyond

A key part of sovereign AI is a nation’s ability to produce artificial intelligence using its own workforce — along with its own infrastructure, data and business networks. Free DLI training offered through Tunisia’s AI innovation hub is poised to enable just that, helping upskill the next generation of African AI experts.

Plus, Novation City already offers a wide range of facilities designed to support technological and scientific advancement.

In February, Novation City deployed an NVIDIA DGX system, among the first in Africa, that has empowered about 30 startups across the continent in climate AI, transportation, manufacturing, agtech and other industries to develop accelerated computing-based solutions.

In addition, ESPRIT University — a specialized university in Tunisia with more than 10,000 engineering students — boasts nine NVIDIA DLI ambassadors who are delivering training to students and contributing to the broader tech ecosystem across the country. This makes ESPRIT University one of the most active DLI organizations across EMEA.

Since 2018, ESPRIT has been tapping into DLI to advance AI education. The university has also acquired an NVIDIA DGX system to support research and product development.

NVIDIA has planned similar AI education initiatives in Kenya and Nigeria to further upskill and enhance African technology ecosystems.

Learn more about the NVIDIA Deep Learning Institute.

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