Scikit-learn, the most widely used ML library, is popular for processing tabular data because of its simple API, diversity of algorithms, and compatibility with popular Python libraries such as pandas and NumPy. NVIDIA cuML now enables you to continue using familiar scikit-learn APIs and Python libraries while enabling data scientists and machine learning engineers to harness the power of CUDA on…
]]>NVIDIA LLM Developer Day is a virtual event providing hands-on guidance for developers exploring and building LLM-based applications and services. You can gain an understanding of key technologies, their pros and cons, and explore example applications. The sessions also cover how to create, customize, and deploy applications using managed APIs, self-managed LLMs…
]]>At NVIDIA GTC 2023, NVIDIA unveiled notable updates to its suite of NVIDIA AI software for developers to accelerate computing. The updates reduce costs in several areas, such as data science workloads with NVIDIA RAPIDS, model analysis with NVIDIA Triton, AI imaging and computer vision with CV-CUDA, and many more. To keep up with the newest SDK advancements from NVIDIA, watch the GTC keynote…
]]>Real-time natural language understanding will transform how we interact with intelligent machines and applications.
]]>NVIDIA revealed major updates to its suite of AI software for developers including JAX, NVIDIA CV-CUDA, and NVIDIA RAPIDS. To learn about the latest SDK advancements from NVIDIA, watch the keynote from CEO Jensen Huang. Just today at GTC 2022, NVIDIA introduced JAX on NVIDIA AI, the newest addition to its GPU-accelerated deep learning frameworks. JAX is a rapidly growing…
]]>Major updates to Riva, an SDK for building speech AI applications, and a paid Riva Enterprise offering were announced at NVIDIA GTC 2022 last week. Several key updates to the NeMo framework, a framework for training Large Language Models, were also announced. Riva offers world-class accuracy for real-time automatic speech recognition (ASR) and text-to-speech (TTS) skills across multiple…
]]>At GTC 2022, NVIDIA announced major updates to its suite of NVIDIA AI software, for developers to build real-time speech AI applications, create high-performing recommenders at scale and optimize inference in every application, and more. Watch the keynote from CEO, Jensen Huang, to learn about the latest advancements from NVIDIA. Today, NVIDIA announced Riva 2.0…
]]>At NVIDIA GTC this November, new software tools were announced that help developers build real-time speech applications, optimize inference for a variety of use-cases, optimize open-source interoperability for recommender systems, and more. Watch the keynote from CEO, Jensen Huang, to learn about the latest NVIDIA breakthroughs. Today, NVIDIA unveiled a new version of NVIDIA Riva with a…
]]>NVIDIA recently unveiled new breakthroughs in NVIDIA Riva for speech AI, and NVIDIA NeMo for large-scale language modeling (LLM). Riva is a GPU-accelerated Speech AI SDK for enterprises to generate expressive human-like speech for their brand and virtual assistants. NeMo is an accelerated training framework for speech and NLU, that now has the capabilities to develop large-scale language models…
]]>NVIDIA CUDA-X AI is a deep learning software stack for researchers and software developers to build high performance GPU-accelerated applications for conversational AI, recommendation systems, and computer vision. Learn what’s new in the latest releases of the CUDA-X AI tools and libraries. For more information on NVIDIA’s developer tools, join live webinars, training, and “Connect with the…
]]>This post was originally published in August 2019 and has been updated for NVIDIA TensorRT 8.0. Join the NVIDIA Triton and NVIDIA TensorRT community to stay current on the latest product updates, bug fixes, content, best practices, and more. Large-scale language models (LSLMs) such as BERT, GPT-2, and XL-Net have brought exciting leaps in accuracy for many natural language processing…
]]>This post was updated July 20, 2021 to reflect NVIDIA TensorRT 8.0 updates. NVIDIA TensorRT is an SDK for deep learning inference. TensorRT provides APIs and parsers to import trained models from all major deep learning frameworks. It then generates optimized runtime engines deployable in the datacenter as well as in automotive and embedded environments. This post provides a simple…
]]>At GTC 2021, NVIDIA announced new software tools to help developers build optimized conversational AI, recommender, and video solutions. Watch the keynote from CEO, Jensen Huang, for insights on all of the latest GPU technologies. Today NVIDIA announced major conversational AI capabilities in NVIDIA Riva that will help enterprises build engaging and accurate applications for their…
]]>Conversational AI is opening new ways for enterprises to interact with customers in every industry using applications like real-time transcription, translation, chatbots, and virtual assistants. Building domain-specific interactive applications requires state-of-the-art models, optimizations for real-time performance, and tools to adapt those models with your data. This week at GTC…
]]>Large scale language models (LSLMs) such as BERT, GPT-2, and XL-Net have brought about exciting leaps in state-of-the-art accuracy for many natural language understanding (NLU) tasks. Since its release in Oct 2018, BERT1 (Bidirectional Encoder Representations from Transformers) remains one of the most popular language models and still delivers state of the art accuracy at the time of writing2.
]]>Object detection remains the primary driver for applications such as autonomous driving and intelligent video analytics. Object detection applications require substantial training using vast datasets to achieve high levels of accuracy. NVIDIA GPUs excel at the parallel compute performance required to train large networks in order to generate datasets for object detection inference.
]]>Neural machine translation exists across a wide variety consumer applications, including web sites, road signs, generating subtitles in foreign languages, and more. TensorRT, NVIDIA’s programmable inference accelerator, helps optimize and generate runtime engines for deploying deep learning inference apps to production environments. NVIDIA released TensorRT 4 with new features to accelerate…
]]>NVIDIA has released TensorRT 4 at CVPR 2018. This new version of TensorRT, NVIDIA’s powerful inference optimizer and runtime engine provides: Additional features include the ability to execute custom neural network layers using FP16 precision and support for the Xavier SoC through NVIDIA DRIVE AI platforms. TensorRT 4 speeds up deep learning inference applications such as neural machine…
]]>Update, May 9, 2018: TensorFlow v1.7 and above integrates with TensorRT 3.0.4. NVIDIA is working on supporting the integration for a wider set of configurations and versions. We’ll publish updates when these become available. Meanwhile, if you’re using , simply download TensorRT files for Ubuntu 14.04 not16.04, no matter what version of Ubuntu you’re running.
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