$NVIDIA (NVDA.US)$ 💡 NVIDIA, innovative evolution of AI tec...
💡 NVIDIA, innovative evolution of AI technology: from 3D world building to Generative Physical AI $NVDA
NVIDIA made a series of announcements showcasing the new evolution of AI technology at the SIGGRAPH 2024 conference. These innovations span a wide range of fields, from building 3D worlds to practical applications of Generative Physical AI.
1️⃣ fVDB: High-precision digitization of the real world
NVIDIA announced a new deep learning framework called Fast Voxel Database (fVDB). fVDB is a groundbreaking technology for generating AI-capable virtual representations of the real world.
Key features of fVDB:
Built on the industry standard sparse volumetric data simulation rendering library OpenVDB.
4 times the spatial scale and 3.5 times the performance compared to conventional frameworks.
Provides more than 10 times the operators, integrating the functionality of multiple deep learning libraries.
Applications:
Virtual environments of real-scale training for autonomous agents.
3D model generation at city scale for climate science and disaster planning.
AI for 3D generation for smart city and urban planning.
2️⃣ Evolution of generative physics AI.
NVIDIA announces advances in Generative Physical AI technology. This includes the NVIDIA Metropolis reference workflow for building interactive visual AI agents and the new NVIDIA NIM microservices to support training of physical machines.
Key Features:
- Advanced decision-making, accuracy, interactivity, and performance leveraging Visual Language Models (VLMs)
- Deployment in various environments such as hospitals, factories, warehouses, retail stores, airports, traffic intersections, etc.
Example: Utilization in Palermo, Italy
- K2K (NVIDIA's Metropolis partner) integrates NVIDIA NIM microservices and VLMs
- Analyzing traffic cameras in real-time to support road management optimization
3️⃣ Expansion of NVIDIA NIM microservices
NVIDIA has announced a significant expansion of the NIM microservice, simplifying the deployment and operation of AI models.
Newly added NIM microservices:
- fVDB-related: fVDB Mesh Generation, fVDB NeRF-XL, fVDB Physics Super-Res
- USD (Universal Scene Description)-related: USD Code, USD Search, USD Validate
These microservices make it easy to integrate Generative AI into the OpenUSD workflow, greatly expanding the possibilities of the 3D world.
4️⃣ Collaboration with Shutterstock and Getty Images: Innovation in the creative industry
NVIDIA has announced new Generative AI services for the creative industry through a partnership with Shutterstock and Getty Images.
Shutterstock's new service "Generative 3D":
- Rapid prototyping of 3D assets using text and image prompts.
- Lighting setup for virtual environments through the generation of 360-degree HDRi backgrounds.
Upgrade to Getty Images' "Generative AI by Getty Images":
- Image generation speed improved by 2 times.
- Improved output quality and added advanced control functions.
- Customization features tailored to brand-specific styles.
Both services utilize NVIDIA Edify (a multimodal architecture for visual generation AI) and are optimized with NVIDIA NIM.
5️⃣ Partnership between Hugging Face and NVIDIA: Strengthening AI infrastructure for developers.
Hugging Face and NVIDIA have announced a new inference-as-a-service for a developer community of over 4 million people.
Key features:
- Optimization of Llama 3 family and Mistral AI models utilizing NVIDIA NIM microservices
- Operates on NVIDIA DGX Cloud and achieves up to 5 times the token processing efficiency
- Improved flexibility and minimized infrastructure overhead through serverless inference
This collaboration enables developers on Hugging Face to easily access NVIDIA-accelerated infrastructure for experimenting and deploying the latest AI models.
📍 Conclusion: Comprehensive advancement of the AI ecosystem
NVIDIA's series of announcements indicate the rapid evolution of AI technology and the blurring of boundaries between the physical and digital worlds. Progress in fVDB and generative physics AI technology has the potential to accelerate the development of AI systems that operate in the real world, such as self-driving cars and robotics.
At the same time, partnerships with Shutterstock and Getty Images can accelerate the practical application of AI in the creative industry, significantly improve the efficiency of designers and artists. Collaboration with Hugging Face simplifies the process of developing and deploying AI models, making AI technology more accessible to a larger number of developers.
The combination of these technologies is likely to accelerate the adoption of AI across the entire industry, potentially leading to a wave of new innovations. At the same time, attention must be paid to the ethical and social issues associated with the rapid evolution of AI, calling for responsible technological development and deployment.
NVIDIA's initiatives clearly demonstrate the vision of a next-generation computing ecosystem centered around AI, indicating the direction of future technological innovation and industrial transformation. Companies and developers will need to strategically leverage these new technologies to enhance competitiveness and foster innovation.
NVIDIA made a series of announcements showcasing the new evolution of AI technology at the SIGGRAPH 2024 conference. These innovations span a wide range of fields, from building 3D worlds to practical applications of Generative Physical AI.
1️⃣ fVDB: High-precision digitization of the real world
NVIDIA announced a new deep learning framework called Fast Voxel Database (fVDB). fVDB is a groundbreaking technology for generating AI-capable virtual representations of the real world.
Key features of fVDB:
Built on the industry standard sparse volumetric data simulation rendering library OpenVDB.
4 times the spatial scale and 3.5 times the performance compared to conventional frameworks.
Provides more than 10 times the operators, integrating the functionality of multiple deep learning libraries.
Applications:
Virtual environments of real-scale training for autonomous agents.
3D model generation at city scale for climate science and disaster planning.
AI for 3D generation for smart city and urban planning.
2️⃣ Evolution of generative physics AI.
NVIDIA announces advances in Generative Physical AI technology. This includes the NVIDIA Metropolis reference workflow for building interactive visual AI agents and the new NVIDIA NIM microservices to support training of physical machines.
Key Features:
- Advanced decision-making, accuracy, interactivity, and performance leveraging Visual Language Models (VLMs)
- Deployment in various environments such as hospitals, factories, warehouses, retail stores, airports, traffic intersections, etc.
Example: Utilization in Palermo, Italy
- K2K (NVIDIA's Metropolis partner) integrates NVIDIA NIM microservices and VLMs
- Analyzing traffic cameras in real-time to support road management optimization
3️⃣ Expansion of NVIDIA NIM microservices
NVIDIA has announced a significant expansion of the NIM microservice, simplifying the deployment and operation of AI models.
Newly added NIM microservices:
- fVDB-related: fVDB Mesh Generation, fVDB NeRF-XL, fVDB Physics Super-Res
- USD (Universal Scene Description)-related: USD Code, USD Search, USD Validate
These microservices make it easy to integrate Generative AI into the OpenUSD workflow, greatly expanding the possibilities of the 3D world.
4️⃣ Collaboration with Shutterstock and Getty Images: Innovation in the creative industry
NVIDIA has announced new Generative AI services for the creative industry through a partnership with Shutterstock and Getty Images.
Shutterstock's new service "Generative 3D":
- Rapid prototyping of 3D assets using text and image prompts.
- Lighting setup for virtual environments through the generation of 360-degree HDRi backgrounds.
Upgrade to Getty Images' "Generative AI by Getty Images":
- Image generation speed improved by 2 times.
- Improved output quality and added advanced control functions.
- Customization features tailored to brand-specific styles.
Both services utilize NVIDIA Edify (a multimodal architecture for visual generation AI) and are optimized with NVIDIA NIM.
5️⃣ Partnership between Hugging Face and NVIDIA: Strengthening AI infrastructure for developers.
Hugging Face and NVIDIA have announced a new inference-as-a-service for a developer community of over 4 million people.
Key features:
- Optimization of Llama 3 family and Mistral AI models utilizing NVIDIA NIM microservices
- Operates on NVIDIA DGX Cloud and achieves up to 5 times the token processing efficiency
- Improved flexibility and minimized infrastructure overhead through serverless inference
This collaboration enables developers on Hugging Face to easily access NVIDIA-accelerated infrastructure for experimenting and deploying the latest AI models.
📍 Conclusion: Comprehensive advancement of the AI ecosystem
NVIDIA's series of announcements indicate the rapid evolution of AI technology and the blurring of boundaries between the physical and digital worlds. Progress in fVDB and generative physics AI technology has the potential to accelerate the development of AI systems that operate in the real world, such as self-driving cars and robotics.
At the same time, partnerships with Shutterstock and Getty Images can accelerate the practical application of AI in the creative industry, significantly improve the efficiency of designers and artists. Collaboration with Hugging Face simplifies the process of developing and deploying AI models, making AI technology more accessible to a larger number of developers.
The combination of these technologies is likely to accelerate the adoption of AI across the entire industry, potentially leading to a wave of new innovations. At the same time, attention must be paid to the ethical and social issues associated with the rapid evolution of AI, calling for responsible technological development and deployment.
NVIDIA's initiatives clearly demonstrate the vision of a next-generation computing ecosystem centered around AI, indicating the direction of future technological innovation and industrial transformation. Companies and developers will need to strategically leverage these new technologies to enhance competitiveness and foster innovation.
Reference
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