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NVIDIA Research will present more than fifty papers at the Computer Vision and Pattern Recognition conference (CVPR), which takes place in Seattle from June 17-21 2024. These papers will highlight significant advances in visual generative AI. According to NVIDIA blog, the research has potential applications in creative industries, autonomous vehicles development, healthcare and robotics.

Generative AI: Diverse Applications

Two papers on training dynamics for diffusion models and high definition maps for autonomous cars are among the projects that deserve special mention. They are finalist for the CVPR Best Paper Awards. NVIDIA won the CVPR Autonomous Grand Challenge’s End-to–End Driving At Scale Track, which showcased comprehensive self-driving systems that outperformed more than 450 global entries, earning the CVPR Innovation Award.

NVIDIA has developed a text to image model that is easily customizable, a model for estimating the pose of an object, techniques for editing neural radiance (NeRFs), as well as a model for visual language capable of understanding memes. These innovations are designed to empower creators and accelerate robot training. They also aim to assist healthcare professionals with processing radiology reports.

Jan Kautz is vice president of NVIDIA's learning and perception research. He said that generative AI, in particular, represents an important technological advance. NVIDIA Research shares at CVPR how it is pushing the limits of what is possible, from powerful image-generation models that can supercharge professional creators up to autonomous driving software which could enable next-generation driverless cars.

JeDi: Custom Image Creation Made Simple

JeDi is one of the papers that stands out. It proposes a technique to allow users to customize diffusion model outputs by using reference images in seconds. This method beats existing methods for fine-tuning. This innovation was developed in collaboration between Johns Hopkins University and Toyota Technological Institute at Chicago. It could be useful for creators who need specific character or product depictions.

FoundationPose & NeRFDeformer

FoundationPose is another highlight of research. It's a foundational model for tracking and estimating object poses. This model can be used to track 3D objects across videos even under difficult conditions, by using 3D images or reference images. This model can enhance industrial applications as well as augmented reality.

NeRFDeformer is a tool developed in collaboration with the University of Illinois Urbana-Champaign that simplifies the transformation of NeRFs using a single RGB-D picture, allowing for a faster update of 3D scenes captured on 2D images.

VILA: Advancing Visual Language Models

NVIDIA, in collaboration with Massachusetts Institute of Technology (MIT), introduced VILA. This family of visual language model outperforms previous models when answering questions about pictures. VILA's pretraining enhances world-knowledge, in context learning, and reasoning over multiple images. It is a powerful tool that can be used for a variety of applications.

Generative AI for Autonomous Driving, Smart Cities and Intelligent Transportation

NVIDIA contributed 12 papers to CVPR that focused on autonomous vehicle research. NVIDIA also provided the largest indoor synthetic dataset ever to the AI City Challenge. This data will help develop smart city solutions as well as industrial automation. These datasets were created using NVIDIA Omniverse. This platform allows developers to create Universal Scene Description (OpenUSD-based) applications and workflows.

NVIDIA Research continues to push boundaries in AI, computer vision, self driving cars, and robotics with the help of hundreds of scientists and engineers around the world. NVIDIA's blog has more information about the groundbreaking work they did at CVPR 2024.

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The technology of Streaming Speech to Text, or live transcription, has revolutionized the way various industries work by converting audio streams in real time into accurate text. AssemblyAI says that this technology improves accessibility and interactions in a variety of sectors including healthcare, financial services, customer service, and market research.

What is Live Transcription?

Live transcription is a process that converts spoken language to written text in real time. Humans would traditionally manually transcribing live content with delays. Artificial intelligence and machine-learning enable speech-to text solutions to automatically translate and transcribe content without requiring human intervention. This process involves audio recording, speech recognition and real-time text display.

Benefits of live transcription

Live transcription has many benefits.

• Accessibility Improvement: Allows individuals with hearing impairments to hear spoken content.
• Increased Engagement: Facilitates participation, particularly in noisy environments and when speakers use strong accents.
• Improved Record-Keeping: Provides instant and accurate recordings of spoken content. This is essential for meeting minutes or legal documents, as well as educational notes.
• Improved Searchability: Enables users to search for specific information and topics when reviewing content, creating summaries or extracting key points.
• Language translation: can be used in conjunction with a translation service to provide subtitles for real-time viewing of different languages.
• Regulatory compliance: Provides an accurate record of interactions.
• Analytics Provides structured data to enable advanced analytics, such as extracting insights, identifying patterns, and measuring performance.

Ten Real-World Use Cases for Live Transcription

1. Live Broadcasting

The live transcription of broadcasts allows for the creation of subtitles and captions that appear on screen, making it easier to follow live events such as sporting events, concerts and social media streams.

2. Virtual Meetings and Conferences

Live transcription is a great way to enhance focus and participation at team meetings, all-hands meetings, virtual conferences and hybrid events.

3. Customer Support and Service

Live transcription helps customer service agents to provide better customer service by providing text in real time of the customer interaction. This allows for immediate analysis, documentation and follow-up.

4. Education and Online Learning

Live transcription is used by schools and online learning programs to accurately and timely provide notes for seminars, lectures, and workshops. This helps students focus on understanding the material and participating.

5. Legal Proceedings

Live transcription of legal proceedings allows for the real-time conversion of text from courtroom discussions, depositions and other legal documents.

6. Telemedicine and Healthcare

Live transcription is used by healthcare organizations to convert spoken medical consultations in real time into text. This reduces the risk of mistakes and improves documentation.

7. Financial Services

Financial services use live transcriptions for client meetings and earnings calls. This improves transparency, compliance and accessibility.

8. Government and Public Sector

Live transcription is used by government organizations for public hearings and press conferences. This makes proceedings more accessible, while creating accurate documentation.

9. Market Research and Focus Groups

Live transcription is used by market research companies for focus groups and real-time discussions. This allows immediate analysis, and reduces human error.

10. AI-Powered Live Assistants

AI-powered live assistants respond to questions and inputs from users during live events and customer service interactions using live transcription and natural languages processing.

Visit the source for more information on AssemblyAI.

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