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Exploring Improved Transparency and Responsibility: Introducing the ‘AI Foundation Model Transparency Act’

The integration of AI across multiple industries has raised many questions surrounding transparency in the training and data-usage of AI systems. Without the necessary level of clarity, AI models can lead to unreliable, inaccurate, and biased outcomes, particularly in critical areas such as healthcare, cybersecurity, elections, and financial decisions. In an effort to address these…

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OpenVoice’s New AI Tool Makes Voice Cloning Easy and Free

We're thrilled to announce the launch of OpenVoice, an open-source voice cloning model developed through a collaboration between the Massachusetts Institute of Technology (MIT), Tsinghua University, and Canadian AI startup MyShell! Experience it now: https://t.co/zHJpeVpX3t. OpenVoice stands out with its near-instant cloning capabilities and detailed control options. It enables users to adjust various aspects of…

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Introducing LoRAMoE: A Plugin Mixture of Experts (Moe) Version for Aligning World Knowledge in Language Models

We are truly excited to share the groundbreaking research from the Fudan University and Hikvision Inc. team, which has developed a powerful new architecture, LoRAMoE, that helps Large Language Models (LLMs) match human instructions while preserving world knowledge. This remarkable achievement is an important step forward in the field of Artificial Intelligence and Machine Learning.…

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Exploring Improved Transparency and Responsibility: Introducing the ‘AI Foundation Model Transparency Act’

The integration of AI across multiple industries has raised many questions surrounding transparency in the training and data-usage of AI systems. Without the necessary level of clarity, AI models can lead to unreliable, inaccurate, and biased outcomes, particularly in critical areas such as healthcare, cybersecurity, elections, and financial decisions. In an effort to address these…

Read More

OpenVoice’s New AI Tool Makes Voice Cloning Easy and Free

We're thrilled to announce the launch of OpenVoice, an open-source voice cloning model developed through a collaboration between the Massachusetts Institute of Technology (MIT), Tsinghua University, and Canadian AI startup MyShell! Experience it now: https://t.co/zHJpeVpX3t. OpenVoice stands out with its near-instant cloning capabilities and detailed control options. It enables users to adjust various aspects of…

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Mete’s AI Paper Introduces Hyper-VolTran: A Novel Neural Network for 3D Reconstruction and Rendering Transformation

Enthusiasm abounds in the rapidly evolving domain of computer vision with the groundbreaking discovery of transforming a single image into a 3D object structure. This technology, indicative of the future of novel view synthesis and robotic vision, is faced with a unique challenge: reconstructing 3D objects from limited perspectives, particularly from a single viewpoint. Such…

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University of Oxford Researchers Create Deep Learning-Based Program for Accurately Monitoring Fish Movement in Complex Settings

It's no secret that deep learning and traditional computer vision techniques have revolutionized automated animal tracking, particularly across neuroscience, medicine, and biomechanics. The recent development of a UK-based research team only further proves this, introducing a remarkable hybrid method for precise tracking of fish movement in complex environments. This method employs both deep learning and…

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Exploring a Revolutionary Technique of Causal Reasoning: Evaluating the Capabilities of Language Models with CLadder and CausalCoT

We are thrilled to introduce CLADDER and CausalCOT, a revolutionary approach to causal reasoning in language models! CLADDER, a dataset with more than 10,000 causal questions covering diverse queries across the three rungs of the Ladder of Causation, is designed to test formal causal reasoning in LLMs through symbolic questions and ground truth answers. Additionally,…

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Introducing UniRef++: An AI Model Revolutionizing Object Segmentation with a Unified Network Architecture and Improved Multi-Task Performance

Object segmentation across images and videos is a complex yet pivotal task, and one that has traditionally seen little integration or collaboration. Different tasks such as referring image segmentation (RIS), few-shot image segmentation (FSS), referring video object segmentation (RVOS), and video object segmentation (VOS) have evolved independently, resulting in inefficient methods and an inability to…

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Exploring a Revolutionary Technique of Causal Reasoning: Evaluating the Capabilities of Language Models with CLadder and CausalCoT

We are thrilled to introduce CLADDER and CausalCOT, a revolutionary approach to causal reasoning in language models! CLADDER, a dataset with more than 10,000 causal questions covering diverse queries across the three rungs of the Ladder of Causation, is designed to test formal causal reasoning in LLMs through symbolic questions and ground truth answers. Additionally,…

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