The current crop(一批，一群) of AI models looks to some scientists like a dead end(死胡同，绝境) when it comes to consciousness, regardless of how powerful they become. For some, this is because of their lack of wet(湿的，此处指生物性的), biological stuff; for others, because of their design structure. But they do not rule out the potential for consciousness in future versions of AI built either with living cells, or on different, more brain-like, computational architectures.(但他们并不排除未来AI产生意识的可能性，这些AI要么用活细胞构建，要么建立在更接近大脑的计算架构上。)
在当今的人工智能模型中，一些科学家认为，就意识而言，它们似乎走进了死胡同，无论它们变得多么强大。对一些人来说，这是因为它们缺乏湿漉漉的生物物质；对另一些人来说，则是因为它们的设计结构。但他们并不排除未来版本的人工智能产生意识的可能性，这些人工智能要么用活细胞构建，要么建立在不同的、更接近大脑的计算架构上。
Modern computers are based on a blueprint(蓝图，设计图) invented by John von Neumann(约翰·冯·诺依曼，计算机科学先驱), a Hungarian polymath(博学家，通才), in 1945. They feature a processing unit (for making calculations) and a memory unit (for storing instructions and data). Information has to zoom(快速移动，飞驰) back and forth between these units and, for AI applications, the energy requirements can mount up(增加，上升).
现代计算机基于约翰·冯·诺依曼（一位匈牙利博学家）于1945年发明的蓝图。它们具有处理单元（用于计算）和存储单元（用于存储指令和数据）。信息必须在这些单元之间来回穿梭，而对于人工智能应用来说，能源需求可能会急剧增加。
Brains do not work this way. Neurons process and store data in the same place, making networks of them much more energy-efficient(节能的，高效能的) at computations than their digital-computer equivalent(等同物，等价物)s. A typical brain consumes around 20 watts whereas an artificial neural network carrying out an equivalent number of parallel calculations would require a data centre that guzzles millions of watts.(一个典型的大脑消耗约20瓦，而执行同等数量并行计算的人工神经网络则需要一个耗电数百万瓦的数据中心。)
大脑不是这样工作的。神经元在同一位置处理和存储数据，这使得它们的网络在计算上比数字计算机等效网络节能得多。一个典型的大脑消耗约20瓦，而执行同等数量并行计算的人工神经网络则需要一个耗电数百万瓦的数据中心。