Computation servers for automatic learning of higher level representations

这笔赠款将允许购买两台计算服务器，每台服务器有16个核心(处理单元)，这是进行“学习更高级别的表示和不变变换”项目所需的密集计算机模拟所必需的。这个项目旨在开发一种方法，通过这种方法，自动适应系统可以从它接收的低级别(感官)信息中发现和学习更有用的、更高级别的表征。允许这样的系统对复杂的观测现象形成更高水平的、不那么肤浅的理解，预计将产生对未来观测的更准确的预测。因此，这种方法的成功将为在许多领域立即应用打开大门，在这些领域，来自过去观测数据的准确预测非常有用：工程、商业金融、商业决策和医学。

This grant will allow the purchase of two computation servers with 16 cores (processing units) each, necessary to carry out the intensive computer simulations required for the "Learning higher level representations and invariant transformations" project. This project aims at developing methods by which an automated adaptive system can discover and learn more useful, higher level representations from the low level (sensory) informations it receives. Allowing such a system to form a higher level, less superficial understanding of complex observed phenomena, is expected to yield far more accurate predictions of future observations. A success in this approach will thus open the door to immediate applications in a wide range of fields where accurate predictions from past observed data are immensely useful: engineering,  finance, business decision making and medecine.