NVIDIA AI Aerial Launches to Optimize Wireless Networks, Deliver New Generative AI Experiences on One Platform

NVIDIA AI Aerial Launches to Optimize Wireless Networks, Deliver New Generative AI Experiences on One Platform

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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How SonicJobs Uses AI Agents to Connect the Internet, Starting with Jobs

How SonicJobs Uses AI Agents to Connect the Internet, Starting with Jobs

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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