Researchers from the University of Chicago and Snap Research have developed a 3D paintbrush that can automatically texture local semantic regions on meshes using text descriptions. The method produces texture maps that seamlessly integrate into standard graphics pipelines. The team also developed a technique called cascaded score distillation (CSD) to enhance details and resolution. The…

Recent advances in Neural Radiance Fields (NeRFs) have demonstrated advancements in 3D graphics and perception. The 3D Gaussian Splatting (GS) framework has further enhanced these improvements. However, more applications are needed to create new dynamics. A research team has developed PhysGaussian, a physics-integrated 3D Gaussian method that allows for realistic generative dynamics in various materials.…

Inflection AI has developed Inflection-2, a highly capable language model that aims to outperform existing solutions such as those from Google and Meta. The model excels in common sense and mathematical reasoning, showcasing its abilities in these domains despite not being its main focus during training. Inflection-2 has outperformed Google and Meta’s models in benchmark…

Stanford researchers have developed BLASTNet-2, a revolutionary dataset that aims to advance the understanding and application of fluid dynamics in various fields. With five terabytes of data derived from over 30 different configurations, BLASTNet-2 offers a centralized platform for fluid dynamics data and promotes interdisciplinary collaborations. It has potential applications in areas such as renewable…

Researchers from UC Berkeley, Toyota Technological Institute at Chicago, ShanghaiTech University, and other institutions propose a new deep network design called CRATE, which stands for “coding-rate” transformer. CRATE aims to bridge the gap between theory and practice in deep learning by providing a white-box architecture that is interpretable and performs well on various learning tasks.…

Researchers from Meta have introduced a new approach called System 2 Attention (S2A) to improve the reasoning capabilities of Large Language Models (LLMs). LLMs often make simple mistakes due to weak reasoning and sycophancy. S2A mitigates these issues by identifying and extracting relevant parts of the input context. It also improves factuality, objectivity, and performance…

The rise of AI has created new career opportunities, such as prompt engineering. Prompt engineers specialize in crafting text-based prompts for AI systems to ensure accurate responses. This field is experiencing job growth and offers competitive salaries, with over 7,000 jobs requiring generative AI expertise in the US alone. Technical, linguistic, and analytical skills are…

Student of Games (SoG) is a general-purpose algorithm developed by EquiLibre Technologies, Sony AI, Amii, Midjourney, and Google’s DeepMind project. It combines search, learning, and game-theoretic reasoning to achieve high performance in both perfect and imperfect information games. SoG demonstrates the potential for creating artificial general intelligence by teaching computers to master a wide range…

Jason Eshraghian from UC Santa Cruz has developed snnTorch, an open-source Python library for implementing spiking neural networks. The library aims to address the inefficiency and environmental impact of traditional neural networks by emulating the brain’s processing mechanisms. With over 100,000 downloads, snnTorch has gained traction and is being used in various applications, including NASA’s…

This text discusses the HyperHuman framework, which aims to generate realistic and diverse human images. It highlights the challenges faced by previous models in creating coherent anatomical structures and proposes a unified framework that incorporates structural information like body skeletons and spatial geometry. The paper introduces the HumanVerse dataset and describes two modules, the Latent…