论文标题
人工智能浏览器体系结构（AIBA）以及其他人：语音名称系统语音实施，具有两个认股权证，唤醒中立性和价值保存个人身份信息
An Artificial Intelligence Browser Architecture (AIBA) For Our Kind and Others: A Voice Name System Speech implementation with two warrants, Wake Neutrality and Value Preservation of Personally Identifiable Information
论文作者
论文摘要
对话贸易首先由Apple的Siri开创，是5月的第一个申请，基于始终在人工智能系统的何时决定与环境互动，可能会收集通常是个人身份信息（PII）的24x7纵向培训数据。根据简单的Google Scholar搜索，大量的学术论文，按照一百万的范围，这表明，如果数据集在其他域中发生的情况足够大，则可以通过该数据对许多健康状况（包括Covid-19和痴呆症）进行大大改进（例如GPT3）。相比之下，当前的主要系统是没有唤醒中性的封闭式园林解决方案，由于IRB和人群构成的约束，因此无法完全利用它们拥有的PII数据。 我们提出了语音浏览器和服务器架构，旨在通过提供尾流中立性以及处理PII的可能性来解决这两个限制，以最大程度地提高其价值。我们已经实施了此浏览器以收集语音样本，并成功证明它可以捕获超过200.000个Covid-19-19咳嗽。我们提出的架构是设计的，因此它可以超越我们的其他领域，例如从车辆中收集声音样本，来自自然界的视频图像，可设备的机器人技术，多模式信号（EEG，EKG，...），甚至与狗和猫等其他类型的相互作用。
Conversational commerce, first pioneered by Apple's Siri, is the first of may applications based on always-on artificial intelligence systems that decide on its own when to interact with the environment, potentially collecting 24x7 longitudinal training data that is often Personally Identifiable Information (PII). A large body of scholarly papers, on the order of a million according to a simple Google Scholar search, suggests that the treatment of many health conditions, including COVID-19 and dementia, can be vastly improved by this data if the dataset is large enough as it has happened in other domains (e.g. GPT3). In contrast, current dominant systems are closed garden solutions without wake neutrality and that can't fully exploit the PII data they have because of IRB and Cohues-type constraints. We present a voice browser-and-server architecture that aims to address these two limitations by offering wake neutrality and the possibility to handle PII aiming to maximize its value. We have implemented this browser for the collection of speech samples and have successfully demonstrated it can capture over 200.000 samples of COVID-19 coughs. The architecture we propose is designed so it can grow beyond our kind into other domains such as collecting sound samples from vehicles, video images from nature, ingestible robotics, multi-modal signals (EEG, EKG,...), or even interacting with other kinds such as dogs and cats.
