脑机接口能否复制AI成功路径？MIND项目构建全球最大脑机交互数据集

Core Insights - The CIFAR datasets (CIFAR-10 and CIFAR-100) have significantly contributed to the advancement of convolutional neural networks (CNNs) and deep learning applications in computer vision, marking a new phase in artificial intelligence technology [1][2] - MaschineRobot has launched the MIND project to create the world's largest brain-computer interaction dataset, aiming to transition human-computer interaction from traditional physical methods to advanced thought-based interactions [1][2] Group 1: MIND Project Overview - The MIND project plans to collect data from over 100,000 participants across more than 100 different brain-computer interaction tasks over the next five years, creating an unprecedented and detailed data repository [2][3] - The dataset will be open for sharing in the fields of neuroscience, machine learning, and human-computer interaction research, providing a strong impetus for the industrial application of brain-computer interface technology [2][3] Group 2: Core Data Categories - The MIND dataset will include five core categories: 1. State Task Dataset: Focused on recording and analyzing brain activity patterns in different states [3] 2. Interaction Task Dataset: Collecting EEG signals from users performing specific tasks [3] 3. Neurobiological Feedback Dataset: Studying brain responses to specific stimuli and their feedback mechanisms [3] 4. Multimodal Interaction Dataset: Combining various sensory inputs and outputs to support more complex interaction scenarios [3] 5. Mental and Neural Health Dataset: Aiming to improve and monitor mental and neural health conditions through brain-computer interface technology [3] - The project supports various types of brain-computer interface devices for data collection and aims for high precision in data labeling and granularity to ensure data quality and usability [3]