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…
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…
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.…
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…
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…
The researchers from the University of Michigan have discovered something remarkable - prompting Large Language Models (LLM) with gender-neutral or male roles can elicit better responses than female roles! By experimenting with different prompts such as "You are a lawyer," "You are speaking to a father," and "You are speaking to your girlfriend," the research…
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…
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…
ClimateAi is revolutionizing the way businesses are preparing for climate change. By combining AI with advanced machine learning and data points from multiple sources, their ClimateLens platform can generate actionable insights on a timescale of 1 to 6 months and identify risks and opportunities in supply chains caused by future climate scenarios on a timescale…
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,…
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…
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,…