Neural network based Artificial Intelligence (AI) has reported increasing scales in experiments. However, this paper raises a rarely reported stage in such experiments called Post-Selection alter the reader to several possible protocol flaws that may result in misleading results. All AI methods fall into two broad schools, connectionist and symbolic. The Post-Selection fall into two kinds, Post-Selection Using Validation Sets (PSUVS) and Post-Selection Using Test Sets (PSUTS). Each kind has two types of post-selectors, machines and humans. The connectionist school received criticisms for its "black box" and now the Post-Selection; but the seemingly "clean" symbolic school seems more brittle because of its human PSUTS. This paper first presents a controversial view: all static "big data" are non-scalable. We then analyze why error-backprop from randomly initialized weights suffers from severe local minima, why PSUVS lacks cross-validation, why PSUTS violates well-established protocols, and why every paper involved should transparently report the Post-Selection stage. To avoid future pitfalls in AI competitions, this paper proposes a new AI metrics, called developmental errors for all networks trained, under Three Learning Conditions: (1) an incremental learning architecture (due to a "big data" flaw), (2) a training experience and (3) a limited amount of computational resources. Developmental Networks avoid Post-Selections because they automatically discover context-rules on the fly by generating emergent Turing machines (not black boxes) that are optimal in the sense of maximum-likelihood across lifetime, conditioned on the Three Learning Conditions.
翻译:以人工智能(AI) 为基础的神经网络报告实验规模的扩大。 然而, 本文在这样的实验中提出了一个很少报告的阶段, 名为“ 后选”, 将读者换成可能会导致误导结果的几个可能的协议缺陷。 所有AI 方法都分为两大类, 包括连接和象征。 后选分为两类: 使用校验设置( PSUVS ) 和 使用测试设置( PSUUTS ) 的随机初始重量的偏差偏差。 每种类型都有两种选后选择、 机器和人。 连接学校在“ 黑盒子” 和现在的后选中都受到批评; 但看起来“ 清洁” 象征性学校似乎更糟糕, 因为它的人PSUTS。 本文首先提出了一种有争议的观点: 所有静态的“ 大数据” 都无法缩放。 我们然后分析为什么随机初始化重量的偏差会受到严重的本地迷你,为什么PSUVS 缺乏交叉验证, 为何PSUTS 违反既定的协议, 为何每份文件都要透明地报告“ ” 的“ 的“ 的“ 终身” 纸” 自动报告“ 后选后选时程” 的“ 的“ 的“ 的“ 的“ 的“ 的“ ” 的“ 的“ ” ” 的“ 的“ ” ” ” 的“ 的“ ” 的“ ” 的“ 的“ 的“ 的” ” 的“ 的” 的“ 的” 的“ 的” 的“ 的“ 的” 的” 的” 的“ 的“ 的“ 的“ 的“ 的” 的” 的“ 的“ 的” ” 的“ ” ” ” ” ” ” 的“ ” ” ” 的“ 的“ ” 的“ 的“ 的“ ” ” ” 的“ 的“ ” 的“ ” ” 的“ ” ” 的“ 的“ ” ” ” ” ” ” 的“ 的“ ” ” ” ”