Category: Misc

What is the metaverse? The metaverse is a shared virtual 3D world, or worlds, that are interactive, immersive, and collaborative. Just as the physical universe is a collection of worlds that are connected in space, the metaverse can be thought of as a bunch of worlds, too. Massive online social games, like battle royale juggernaut Read article >

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With its powerful real-time ray tracing and AI acceleration capabilities, NVIDIA RTX technology has transformed design and visualization workflows for the most complex tasks, like designing airplanes and automobiles, visual effects in movies and large-scale architectural design. The new NVIDIA RTX A2000 — our most compact, power-efficient GPU for a wide range of standard and Read article >

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Life in the metaverse is getting more real.  Starting today, developers can create and share realistic simulations in a standard way. Apple, NVIDIA and Pixar Animation Studios have defined a common approach for expressing physically accurate models in Universal Scene Description (USD), the common language of virtual 3D worlds.  Pixar released USD and described it in 2016 at SIGGRAPH. It was originally designed so artists could Read article >

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Talk about a magic trick. One moment, NVIDIA CEO Jensen Huang was holding forth from behind his sturdy kitchen counter. The next, the kitchen and everything in it slid away, leaving Huang alone with the audience and NVIDIA’s DGX Station A100, a glimpse at an alternate digital reality. For most, the metaverse is something seen Read article >

The post From Our Kitchen to Yours: NVIDIA Omniverse Changes the Way Industries Collaborate appeared first on The Official NVIDIA Blog.

NVIDIA today announced a major expansion of NVIDIA Omniverse™ — the world’s first simulation and collaboration platform that is delivering the foundation of the metaverse — through new integrations with Blender and Adobe that will open it to millions more users.

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Using machine learning and visual psychophysics, researchers are developing AI models capable of transcribing ancient manuscripts.

Looking to reveal secrets of days past, historical scholars across the globe spend their life’s work translating ancient manuscripts. A team at the University of Notre Dame looks to help in this quest, with a newly developed machine learning model for translating and recording handwritten documents centuries old.  

Using digitized manuscripts from the Abbey Library of Saint Gall, and a machine learning model that takes into account human perception, the study offers a notable improvement in the capabilities of deep learning transcription.

“We’re dealing with historical documents written in styles that have long fallen out of fashion, going back many centuries, and in languages like Latin, which are rarely ever used anymore. You can get beautiful photos of these materials, but what we’ve set out to do is automate transcription in a way that mimics the perception of the page through the eyes of the expert reader and provides a quick, searchable reading of the text,” Walter Scheirer, senior author and an associate professor at Notre Dame said in a press release. 

Founded in 719, the Abbey Library of Saint Gall holds one of the oldest and richest library collections in the world. The library houses approximately 160,000 volumes and 2,000 manuscripts, dating back to the eighth century. Hand-written on parchment paper in languages rarely used today, many of these materials have yet to be read—a potential fortune of historical archives, waiting to be unearthed.

Machine learning methods capable of automatically transcribing these types of historical documents have been in the works, however challenges remain. 

Up until now, large datasets have been necessary to boost the performance of these language models. With the vast number of volumes available, the work takes time, and relies on a relatively small number of expert scholars for annotation. Missing knowledge, such as the Medieval Latin dictionary that has never been compiled, poses even greater obstacles. 

The team combined traditional machine learning methods with the science of visual psychophysics, which studies the relationship between the physical world and human behavior, to create more information-rich annotations. In this case, they incorporated the measurements of human vision into the training process of the neural networks when processing the ancient texts.

“It’s a strategy not typically used in machine learning. We’re labeling the data through these psychophysical measurements, which comes directly from psychological studies of perception—by taking behavioral measurements. We then inform the network of common difficulties in the perception of these characters and can make corrections based on those measurements,” Scheirer said.

To train, validate, and test the models the researchers used a set of digitized handwritten Latin manuscripts from St. Gall dating back to the ninth century. They asked experts to read and enter manual transcriptions from lines of text into custom designed software. Measuring the time for each transcription, gives insight into the difficulty of words, characters, or passages. According to the authors, this data helps reduce errors in the algorithm and provides more realistic readings.  

All of the experiments were run using the cuDNN-accelerated PyTorch deep learning framework and GPUs. “We definitely could not have accomplished what we did without NVIDIA hardware and software,” said Scheirer.

The research introduces a novel loss formulation for deep learning that incorporates measurements of human vision, which can be applied to different processing pipelines for handwritten document transcription. Credit: Scheirer et al/IEEE

There are still areas the team is working to improve. Damaged and incomplete documents, along with illustrations and abbreviations pose a special challenge for the models. 

“The inflection point AI reached thanks to Internet-scale data and GPU hardware is going to benefit cultural heritage and the humanities just as much as other fields. We’re just scratching the surface of what we can do with this project,” said Scheirer.

  

Read the full article in IEEE Transactions on Pattern Analysis and Machine Intelligence  >>
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Talk about a signal boost. Creative Technology is tackling 4K and 8K signals, as well as new broadcast workflows, with the latest NVIDIA networking technologies. The London-based firm is one of the world’s leading suppliers of audio visual equipment for broadcasting and online events. Part of global production company NEP Group, CT helps produce high-quality Read article >

The post On the Air: Creative Technology Elevates Broadcast Workflows for International Sporting Event with NVIDIA Networking appeared first on The Official NVIDIA Blog.

Enterprises challenged with running accelerated workloads have an answer: NVIDIA-Certified Systems. Available from nearly 20 global computer makers, these servers have been validated for running a diverse range of accelerated workloads with optimum performance, reliability and scale. Now NVIDIA-Certified Systems are expanding to the desktop with workstations that undergo the same testing to validate their Read article >

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