With emerging use cases such as digital humans, agents, podcasts, images, and video generation, generative AI is changing the way we interact with PCs. This paradigm shift calls for new ways of interfacing with and programming generative AI models. However, getting started can be daunting for PC developers and AI enthusiasts. Today, NVIDIA released a suite of NVIDIA NIM microservices on��
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Generative AI has revolutionized how people bring ideas to life, and agentic AI represents the next leap forward in this technological evolution. By leveraging sophisticated, autonomous reasoning and iterative planning, AI agents can tackle complex, multistep problems with remarkable efficiency. As AI continues to revolutionize industries, the demand for running AI models locally has surged.
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Microsoft Bing Visual Search enables people around the world to find content using photographs as queries. The heart of this capability is Microsoft��s TuringMM visual embedding model that maps images and text into a shared high-dimensional space. Operating on billions of images across the web, performance is critical. This post details efforts to optimize the TuringMM pipeline using NVIDIA��
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The NVIDIA RTX AI for Windows PCs platform offers a thriving ecosystem of thousands of open-source models for application developers to leverage and integrate into Windows applications. Notably, llama.cpp is one popular tool, with over 65K GitHub stars at the time of writing. Originally released in 2023, this open-source repository is a lightweight, efficient framework for large language model��
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Today��s large language models (LLMs) achieve unprecedented results across many use cases. Yet, application developers often need to customize and tune these models to work specifically for their use cases, due to the general nature of foundation models. Full fine-tuning requires a large amount of data and compute infrastructure, resulting in model weights being updated.
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NVIDIA ACE��a suite of generative AI-enabled digital human technologies��is now generally available for developers. Packaged as NVIDIA NIM microservices, ACE enables developers to deliver high-quality natural language understanding, speech synthesis, and facial animation for gaming, customer service, healthcare, and more. NVIDIA is also introducing ACE PC NIM microservices for deployment��
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NVIDIA today launched the NVIDIA RTX AI Toolkit, a collection of tools and SDKs for Windows application developers to customize, optimize, and deploy AI models for Windows applications. It��s free to use, doesn��t require prior experience with AI frameworks and development tools, and delivers the best AI performance for both local and cloud deployments. The wide availability of generative��
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Large language models (LLMs) are fundamentally changing the way we interact with computers. These models are being incorporated into a wide range of applications, from internet search to office productivity tools. They are advancing real-time content generation, text summarization, customer service chatbots, and question-answering use cases. Today, LLM-powered applications are running��
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Generative AI and large language models (LLMs) are changing human-computer interaction as we know it. Many use cases would benefit from running LLMs locally on Windows PCs, including gaming, creativity, productivity, and developer experiences. This post discusses several NVIDIA end-to-end developer tools for creating and deploying both text-based and visual LLM applications on NVIDIA RTX AI-ready��
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