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Some parents will buy any high-tech toy if they think it will help their child, but researchers said puzzles help children with math-related skills.
一些家长只要认为对孩子有益，他们就会购买任何高科技玩具，但研究人员认为拼图有助于提高孩子们的数学相关技能。
Psychologist Susan Levine, an expert on mathematics development in young children the University of Chicago, found children who play with puzzles between ages 2 and 4 later develop better spatial skills. Puzzle play was found to be a significant predictor of cognition after controlling for differences in parents’ income, education and the amount of parent talk, Levine said.
芝加哥大学儿童数学发展专家心理学家苏珊·莱文发现，在2岁到4岁之间玩拼图游戏的孩子们随后会发展出更好的空间技能。莱文说，在避免了父母收入、教育程度和父母交谈量的差异后，拼图游戏被认为是认知能力的一个重要预测因素。
The researchers analyzed video recordings of 53 child-parent pairs during everyday activities at home and found children who play with puzzles between 26 and 46 months of age have better spatial skills when assessed at 54 months of age.
研究人员分析了53对父母与子女在家庭日常活动中的视频记录，发现26至46个月之间玩拼图游戏的孩子在54个月大时空间技能更好。
“The children who played with puzzles performed better than those who did not, on tasks that assessed their ability to rotate and translate shapes,” Levine said in a statement.
“玩拼图游戏的孩子在评估他们旋转和变换形状能力要比没有玩拼图游戏的孩子好，”莱文在一份声明中说。
The parents were asked to interact with their children as they normally would, and about half of children in the study played with puzzles at one time. Higher-income parents tended to have children play with puzzles more frequently, and both boys and girls who played with puzzles had better spatial skills. However, boys tended to play with more complex puzzles than girls, and the parents of boys provided more spatial language and were more active during puzzle play than parents of girls.
研究人员要求父母像平时一样与孩子互动，研究中约有一半的孩子曾玩过拼图游戏。高收入的父母往往让孩子多玩些拼图，玩拼图的男孩和女孩都会有更好的空间技能。不过，男孩往往玩的拼图比女孩的更复杂，男孩的父母在玩拼图游戏时比女孩的父母提供了更多的空间语言，也更活跃。
The findings were published in the journalDevelopmental Science.
研究结果发表在《发展科学》杂志上。
For the past five years, Paula Smith, a historian of science, has devoted herself to re-creating long-forgotten techniques. While doing research for her new book, she came across a 16th-century French manuscript consisting of nearly 1,000 sets of instructions, covering subjects from tool making to finding the best sand.
在过去五年里，科学历史学家保拉·史密斯一直致力于重现人们早已遗忘的技术。在为她的新书做研究时，她偶然发现了一本16世纪的法国手稿，包括近1000份说明书，涵盖范围从工具制作到如何寻找最佳沙子。
The author's intention remains as mysterious as his name; he may have been simply taking notes for his own records. But Smith was struck mainly by the fact that she didn't truly grasp any of the skills the author described. "You simply can't get an understanding of that handwork by reading about it," she says.
作者的意图如同他的名字一样神秘；他可能只是在为自己的记录做笔记。但让史密斯备受打击的是，她并没有真正掌握作者描述的任何技能。“你根本无法通过阅读来理解手工作品”，她说。
Though Smith did get her hands on the best sand, doing things the old-fashioned way isn't just about playing around with French mud. Reconstructing the work of the craftsmen who lived centuries ago can reveal how they viewed the world, what objects filled their homes, and what went on in the workshops that produced them. It can even help solve present-day problems: In 2015, scientists discovered that a 10th-century English medicine for eve problems could kill a drug-resistant virus.
尽管史密斯确实得到了最好的沙子，但用传统的方法做事情并不只是玩法国泥。重建生活在几个世纪前的工匠作品可以揭示他们是如何看待世界，他们的家中装满的物品，以及这些物品在作坊里如何进行生产。它甚至可以帮助解决当代问题：2021年，科学家发现，一种用于解决女性问题的10世纪英国药物可以杀死耐药病毒。
The work has also brought insights for museums, Smith says. One must know how on object was made in order to preserve it. What's more, reconstructions might be the only way to know what treasures looked like before time wore them down. Scholars have seen this idea in practice with ancient Greek and Roman statues. These sculptures were painted a rainbow of striking colours. We can't appreciate these kinds of details without seeing works of art as they originally appeared-something Smith believes you can do only when you have a road map.
史密斯说，这项工作也为博物馆带来了启发。为了保存文物，人们必须知道这个物体是如何制作的。更重要的是，重建可能是了解宝藏在时间磨损之前是什么样子的唯一途径。学者们在古希腊和古罗马雕像的实践中看到了这种想法，这些雕塑被漆成了鲜艳的彩虹色。如果不看艺术作品最初出现的样子，我们无法欣赏这些细节——史密斯认为，只有当你有路线图时，你才能做到这一点。
Smith has put the manuscript's ideas into practice. Her final goal is to link the worlds of art and science back together: She believes that bringing the old recipes to life can help develop a kind of learning that highlights experimentation, teamwork, and problem solving.
史密斯把手稿的想法付诸实践。她最终的目标是将艺术和科学的世界重新联系起来：她相信，将古老的食谱带到生活中有助于发展一种强调实验、团队合作和解决问题的学习方式。
Back when science—then called “the new philosophy”—took shape, academics looked to craftsmen for help in understanding the natural world. Microscopes and telescopes were invented by way of artistic tinkering, as craftsmen experimented with glass to better bend light.
当科学——也就是所谓的“新哲学”——初具雏形时，学术界寻求工匠帮助理解自然世界。正如工匠尝试用玻璃更好地弯曲光线，显微镜和望远镜因为艺术修补而发明。
If we can rediscover the values of hands-on experience and craftwork, Smith says, we can marry the best of our modern insights with the handiness of our ancestors.
某些形式的AI （人工智能）确实正变得无处不在。例如，金融市场上进行大量交易的算法，出现在城市街道上的自动驾驶汽车，智能手机将一种语言翻译成另一种语言。这些系统有时比我们人类更快、更敏锐。但到目前为止，这些只适用于系统所设计的特定任务，一些AI开发者正在期待改变。
Some of today's AI pioneers want to move on from today's world of “weak” or “narrow” AI, to create “strong” or “full” AI, or what is often called artificial general intelligence (A GI). In some respects, today's powerful computing machines already make our brains look weak. A GI could, its advocates say, work for us around the clock, and drawing on all available data, could suggest solutions to many problems. DM, a company focused on the development of A GI, has an ambition to “solve intelligence”. “If we're successful,” their mission statement reads, “we believe this will be one of the most important and widely beneficial scientific advances ever made.”
当代一些AI先驱希望从今天的“弱”或“窄”的AI世界中走出来，创造“强”或“全”的AI，也就是通常所说的A GI（人工通用智能）。在某些方面，今天强大的计算机已经让我们的大脑看起来很弱。A GI的支持者认为A GI可以24小时为我们工作，利用所有可用的数据，可以为许多问题提供解决方案。DM是一家专注于A GI开发的公司，有着“解决智能问题”的雄心。“如果我们成功了，”他们的任务声明写道，“我们相信这将是有史以来最重要、最广泛有益的科学进步之一。”
Since the early days of AI, imagination has outpaced what is possible or even probable. In 1965, an imaginative mathematician called Irving Good predicted the eventual creation of an "ultra-intelligent machine…that can far surpass all the intellectual activities of any man, however clever." Good went on to suggest that “the first ultra-intelligent machine" could be “the last invention that man need ever make."
自AI诞生之初，想象力的发展速度已经超过了你的想象。1965年，一位富有想象力的数学家欧文·古德预言，最终将创造出一台“超智能机器……它将远远超过人类的所有智能活动，无论多么聪明。”古德接着表示，“第一台超智能机器”可能是“人类需要创造的最后一项发明”。
Fears about the appearance of bad, powerful, man-made intelligent machines have been reinforced by many works of fiction—Mary Shelley's Frankenstein and the Terminator film series, for example. But if AI does eventually prove to be our downfall, it is unlikely to be at the hands of human-shaped forms like these, with recognisably human motivations such as aggression. Instead, I agree with Oxford University philosopher Nick Bostrom, who believes that the heaviest risks from A GI do not come from a decision to turn against mankind but rather from a dogged pursuit of set objectives at the expense of everything else.
人们对于出现强大而又邪恶的人造智能机器的担忧已经加剧，例如，玛丽·雪莱的《弗兰肯斯坦》科幻小说和《终结者》系列电影。但如果最终证明AI 是我们的垮台，它就不太可能掌握在这样的人形形态手中，而这些形态具有明显的人类动机，比如敌对行为。相反，我同意牛津大学哲学家尼克·博斯特罗姆的观点，他认为，A GI带来的最大风险不是来自于反对人类的决定，而是来自于不惜牺牲一切代价执着地追求既定目标。
The promise and danger of true A GI are great. But all of today's excited discussion about these possibilities presupposes the fact that we will be able to build these systems. And, having spoken to many of the world's foremost AI researchers, I believe there is good reason to doubt that we will see A GI any time soon, if ever.
真正的A GI的前景和危险都是巨大的，但是今天所有关于这些可能性的激动人心的讨论都是以我们能够建立这些系统为前提。而且，在与许多世界上最重要的AI研究人员交谈后，我相信有充分的理由怀疑我们是否会很快看到A GI，如果有的话。
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