Nvidia, the leading graphics processing unit (GPU) manufacturer, has recently introduced new artificial intelligence (AI) tools that enable anyone to program with ease. These tools are designed to make it easier for developers, data scientists, and researchers to build and deploy AI applications.
The new tools include the Nvidia Merlin, a framework for building large-scale recommendation systems, and the Nvidia Jarvis, a framework for building conversational AI applications. These tools are built on top of Nvidia’s existing AI platform, which includes the Nvidia CUDA parallel computing platform and the Nvidia TensorRT inference engine.
Merlin is designed to help developers build recommendation systems that can handle massive amounts of data. It includes pre-built models for common recommendation tasks, such as product recommendations and content recommendations. Developers can also use Merlin to build custom models that are tailored to their specific needs.
Jarvis, on the other hand, is designed to help developers build conversational AI applications, such as chatbots and virtual assistants. It includes pre-built models for common conversational tasks, such as natural language understanding and speech recognition. Developers can also use Jarvis to build custom models that are tailored to their specific needs.
Both Merlin and Jarvis are built on top of Nvidia’s existing AI platform, which includes the Nvidia CUDA parallel computing platform and the Nvidia TensorRT inference engine. This platform is designed to make it easier for developers to build and deploy AI applications by providing a set of tools and libraries that can be used across a wide range of hardware platforms.
One of the key benefits of these new AI tools is that they make it easier for developers to build and deploy AI applications without requiring a deep understanding of the underlying technology. This means that more people can get involved in building AI applications, which could lead to faster innovation and more widespread adoption of AI technology.
Another benefit of these new AI tools is that they are designed to work seamlessly with Nvidia’s existing hardware platforms. This means that developers can take advantage of the performance and efficiency benefits of Nvidia’s GPUs without having to worry about the underlying technology.
Overall, Nvidia’s new AI tools are a significant step forward in making AI technology more accessible to a wider range of developers, data scientists, and researchers. By providing a set of easy-to-use tools and libraries, Nvidia is helping to democratize AI and accelerate innovation in this exciting field.
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