News from the AI & ML world
DeeperML
@developer.nvidia.com
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NVIDIA Research is making significant strides in multimodal generative AI and robotics, as showcased at the International Conference on Learning Representations (ICLR) 2025 in Singapore. The company is focusing on a full-stack approach to AI development, optimizing everything from computing infrastructure to algorithms and applications. This approach supports various industries and tackles real-world challenges in areas like autonomous vehicles, healthcare, and robotics.
NVIDIA has introduced a new plug-in builder for G-Assist, which enables the integration of AI with large language models (LLMs) and various software programs. This allows users to customize NVIDIA's AI to fit their specific needs, expanding G-Assist's functionality by adding new commands and connecting external tools. These plug-ins can perform a wide range of functions, from connecting with LLMs to controlling music, and can be built using coding languages like JSON and Python. Developers can also submit their plug-ins for potential inclusion in the NVIDIA GitHub repository.
NVIDIA Research is also addressing the need for adaptable robotic arms in various industries with its R²D² (Robotics Research and Development Digest) workflows and models. These innovations aim to enable robots to make decisions and adjust their behavior based on real-time data, improving flexibility, safety, and collaboration in different environments. NVIDIA is developing models and workflows for dexterous grasping and manipulation, addressing challenges like handling reflective objects and generalizing to new objects and dynamic environments. DextrAH-RGB, for example, is a workflow that performs dexterous arm-hand grasping from stereo RGB input, trained at scale in simulation using NVIDIA Isaac Lab.
ImgSrc: developer-blogs
References :
NVIDIA has introduced a new plug-in builder for G-Assist, which enables the integration of AI with large language models (LLMs) and various software programs. This allows users to customize NVIDIA's AI to fit their specific needs, expanding G-Assist's functionality by adding new commands and connecting external tools. These plug-ins can perform a wide range of functions, from connecting with LLMs to controlling music, and can be built using coding languages like JSON and Python. Developers can also submit their plug-ins for potential inclusion in the NVIDIA GitHub repository.
NVIDIA Research is also addressing the need for adaptable robotic arms in various industries with its R²D² (Robotics Research and Development Digest) workflows and models. These innovations aim to enable robots to make decisions and adjust their behavior based on real-time data, improving flexibility, safety, and collaboration in different environments. NVIDIA is developing models and workflows for dexterous grasping and manipulation, addressing challenges like handling reflective objects and generalizing to new objects and dynamic environments. DextrAH-RGB, for example, is a workflow that performs dexterous arm-hand grasping from stereo RGB input, trained at scale in simulation using NVIDIA Isaac Lab.
ImgSrc: developer-blogs
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References :
- blogs.nvidia.com: Advancing AI requires a full-stack approach, with a powerful foundation of computing infrastructure — including accelerated processors and networking technologies — connected to optimized compilers, algorithms and applications.
- developer.nvidia.com: Robotic arms are used today for assembly, packaging, inspection, and many more applications. However, they are still preprogrammed to perform specific and often...
Classification:
- HashTags: #NVIDIA #GenerativeAI #Robotics
- Company: NVIDIA
- Target: AI Researchers, developers
- Product: NIM
- Feature: Multimodal Generative AI
- Type: AI
- Severity: Informative