NVIDIA and Google Cloud Deliver Powerful New Generative AI Platform, Built on the New L4 GPU and Vertex AI
NVIDIA Studio 3D creators Jeremy Lightcap, Edward McEvenue, Rafi Nizam, Jae Solina, Pekka Varis, Shangyu Wang, Ashley Goldstein collaborate across multiple 3D design tools, time zones and RTX systems with Omniverse. The potential of a single LLM achieving exceptional outcomes across diverse tasks is due to training on an immense volume of Internet-scale data. GET3D will be available in Omniverse AI ToyBox along with existing generative AI research projects published by NVIDIA, such as GANVerse3D Image2Car and AI Animal Explorer. AI ToyBox houses all the latest NVIDIA AI projects, empowering content creators to explore new possibilities in virtual worlds. Soon, laptops and mobile workstations with RTX GPUs will get the best of both worlds. AI inference-only workloads will be optimized for Tensor Core performance while keeping power consumption of the GPU as low as possible, extending battery life and maintaining a cool, quiet system.
With innovation at every layer—the AI supercomputer, AI platform software, and AI models and services—the possibilities are infinite. You can engage the platform at any layer and anywhere, across public and private clouds. A high-level view of the AI workflow, consisting of training and inference pipelines built using NeMo, supported by Triton Management Service, and running on top of cloud-native infrastructure from NVIDIA AI Enterprise software. Developers of middleware, tools and games can use NVIDIA genrative ai ACE for Games to build and deploy customized speech, conversation, and animation AI models in their software and games across the cloud and PC. Generative AI technologies are making this a reality, and at COMPUTEX 2023 we announced the future of NPCs with the NVIDIA Avatar Cloud Engine (ACE) for Games. NVIDIA ACE for Games is a custom AI model foundry service that aims to transform games by bringing intelligence to non-playable characters (NPCs) through AI-powered natural language interactions.
Building Cloud-Native, AI-Powered Avatars with NVIDIA Omniverse ACE
Trained using only 2D images, NVIDIA GET3D generates 3D shapes with high-fidelity textures and complex geometric details. These 3D objects are created in the same format used by popular graphics software applications, allowing users to immediately import their shapes into 3D renderers and game engines for further editing. The massive virtual worlds created by growing numbers of companies and creators could be more easily populated with a diverse array genrative ai of 3D buildings, vehicles, characters and more — thanks to a new AI model from NVIDIA Research. The generative AI knowledge base chatbot AI workflow gives developers a reference to start building a KBQA AI solution. Generative AI is also driving a number of new apps that help people connect and have fun. WOMBO, which offers an AI-powered text to digital art app called Dream, has had early access to NVIDIA’s L4 inference platform on Google Cloud.
At CES, NVIDIA unveiled new generative AI technologies coming to Omniverse to help create virtual worlds faster and easier than ever. These models are available as both third-party Connectors from NVIDIA partners and internal AI projects published by the NVIDIA research team as extensions in AI ToyBox. When optimized for GeForce RTX and NVIDIA RTX GPUs, which offer up to 1,400 Tensor TFLOPS for AI inferencing, generative AI models can run up to 5x faster than on competing devices. This is thanks to Tensor Cores — dedicated hardware in RTX GPUs built to accelerate AI calculations — and regular software improvements. Enhancements introduced last week at the Microsoft Build conference doubled performance for generative AI models, such as Stable Diffusion, that take advantage of new DirectML optimizations. Use state-of-the-art pretrained Edify models from NVIDIA or bring your choice of model for building your Gen AI.
For example, popular applications like ChatGPT, which draws from GPT-3, allow users to generate an essay based on a short text request. On the other hand, Stable Diffusion allows users to generate photorealistic images given a text input. Developing generative AI models is a complex process, and AI Workbench streamlines it.
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.
Another factor in the development of generative models is the architecture underneath. While GANs can provide high-quality samples and generate outputs quickly, the sample diversity is weak, therefore making GANs better suited for domain-specific data generation. Generative AI models use neural networks to identify the patterns and structures within existing data to generate new and original content. Inception provides startups with access to the latest developer resources, preferred pricing on NVIDIA software and hardware, and exposure to the venture capital community. Our self-paced courses and instructor-led workshops are developed and taught by NVIDIA experts and cover advanced software development techniques, leading frameworks and SDKs, and GPU development.
NVIDIA Announces Generative AI Services for Language, Visual Content, and Biology Applications
Some of the challenges faced by enterprises as they begin their journey developing custom generative AI include the following. The Kairos demo leveraged NVIDIA Riva for speech-to-text and text-to-speech capabilities, NVIDIA NeMo to power the conversational AI, and Audio2Face for AI-powered facial animation from voice inputs. These modules were integrated seamlessly into the Convai services platform and fed into Unreal Engine 5 and MetaHuman to bring Jin to life. Descript offers AI-powered editing features that let creators remove filler words, add captions and make social-media clips in a few clicks. Or they can use Descript’s generative-AI voice cloning to fix audio mistakes — even create entire voiceover tracks — just by typing. GTC—NVIDIA today announced Google Cloud is integrating the newly launched L4 GPU and Vertex AI to accelerate the work of companies building a rapidly expanding number of generative AI applications.
Generative AI’s ability to summarize documents has great potential to boost the productivity of policymakers and staffers, civil servants, procurement officers and contractors. Consider a 756-page report recently released by the National Security Commission on Artificial Intelligence. These generative AI tools rely on frameworks that can integrate proprietary data into model training and fine-tuning, integrate data curation to prevent bias and use guardrails to keep conversations finance-specific. Businesses that previously dabbled in AI are now rushing to adopt and deploy the latest applications.
The companies also announced that PaxML is available immediately on the NVIDIA NGC container registry. Generative AI is primed to transform the world’s industries and to solve today’s most important challenges. To enable enterprises to take advantage of the possibilities with generative AI, NVIDIA has launched NVIDIA AI Foundations and the NVIDIA NeMo framework, powered by NVIDIA DGX Cloud. In addition, Audio2Face, Audio2Gesture and Audio2Emotion — generative AI tools that enable instant 3D character animation — are getting performance updates that make it easier for developers and creators to integrate into their current 3D pipelines. Another new panel for scene optimization lets users create USD scenes within their multi-app 3D workflows more easily and in real time.
This type of trainable foundation model enables scientists to create variants for research into specific diseases, allowing them to develop target treatments for rare conditions. AI-assisted creator tools are expanding to even more communities of creative and technical professionals. When NVIDIA Canvas was introduced, it empowered artists to seamlessly generate landscapes and iterate on them with simple brushstrokes and AI.
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