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Manta Network announced its Moon Mission Meme Grants. The $10 million grant will be used to promote meme culture on the platform. This initiative is a part of the larger $50 million EcoFund that supports various projects in the Manta eco-system.

Encouraging Meme Innovation

Manta Network’s Moon Mission Meme Grants are designed to encourage the creation of memes, memcoins and other related projects. Manta Network wants to use the power of memes to increase engagement on Manta Pacific.

Why Apply?

Moon Mission Meme Grants offers participants several benefits:

• Community Building - Memes are a powerful tool for creating vibrant communities. Manta Network seeks projects that can help to lead the charge.
• Unforeseen Potencial: Memes can be viralized, used to support causes and create change. The grants are awarded to projects that have a meaningful impact.
• Experimentation & Innovation: This program encourages breaking boundaries, pushing the limits and offering resources for experimentation and innovation.

Application Process

The official Manta Grant Program is open to all interested parties. The $50 million EcoFund was created to support many projects. This specific grant is intended to have a significant impact on Manta Pacific meme culture.

Manta Network grant program: Moon Mission Meme grants

About Manta Network

Manta Network, a modular blockchain, is focused on applications that require zero-knowledge. Manta Pacific is a modular ecosystem designed for EVM native ZK applications and dApps. It offers low gas fees, and high quality user experience. The platform uses Manta’s Universal Circuits to provide ZK-as a Service and Celestia’s data availability in order to be modular.

Manta Network, founded by alumni of Harvard, MIT and Algorand has received investments from top web3 funds such as Binance Labs, Polychain Capital, and others. It has also taken part in web3 accelerators such as Alliance DAO, Berkeley Blockchain Xcelerator and Polychain Capital.

Visit the official announcement for more information.

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.