母亲的心

    ①熬过六岁那年漫长的严冬，我终于从一场大病中清醒了过来。

    ②春日的阳光映着窗外的夹竹桃，投下斑驳的树影，母亲却明显地憔悴了，瘦弱的样子差点让我不敢认，但她的精神状态却很好，仿佛拣回了珍贵的珠宝一般小心地守护着我。

    ③久病初愈的我没胃口，家人总会变着法子哄我吃饭。那一天，我告诉母亲，很想吃螃蟹，却让家人犯了难：在物质条件极差的偏远山村，怎么可能买得到螃蟹呢！

    ④好在爱子心切的母亲自有她的法子，她很快拎着竹篓出去了。我们村子外面有很多纵横交错的溪流，六月天若翻开小溪里一块块大石头，可以找得到螃蟹。可是，在溪水还寒冽的春天，螃蟹躲在岩洞里是翻不到的。

    ⑤母亲不死心，沿着溪流一路上行，在一块块或大或小的石头下面翻找着。春天的溪水冰凉彻骨，却冻不住她心里涌动的希望。

    ⑥或许上天也怜惜母亲那深切的舐犊之情吧，在母亲双手肿胀发抖，几近绝望的时候，她终于发现了一只个头肥大的螃蟹，正在一块大石头下面迟缓地爬动着。

    ⑦母亲的惊喜可想而知，她赶忙迅捷地双手捞起了螃蟹，可是望着手里那只惶惑无措的螃蟹，母亲的手却止不住颤抖！因为那是一只母蟹，它鼓鼓的肚皮底下正围着无数只细如蚊子的小蟹，有的还爬到了母亲的手背上……

    ⑧母亲思忖了很久，把螃蟹又轻轻地放回了水里，可是刚放下，她又想起什么似的，赶紧再一次捞起了螃蟹，如是者数次。在那个春寒料峭的日子里，一向坚强能干的母亲想必正面临着她人生中一次重大的选择罢！在抓起与放下的动作的重复间，她的内心经历了怎样的一次又一次的自我交战与折磨。

    ⑨这个经过，我并没有亲眼看到，是母亲回来后坐在我床头，抚摩着我的额头细细讲给我听的。母亲说，最后一次她干脆咬咬牙，闭起双眼把螃蟹放进了竹篓，甚至已经带出了十几步路。可是竹篓里那不停的“沙沙沙”的挣扎声，最终还是让她彻底丧失了往家走的勇气，再一次跑回到溪边。放下母蟹的那一刹那，她潸然泪下！

    ⑩母亲最终是空着手回家的，在那个还带着寒意的春日里，母亲再也没能翻到第二只螃蟹。坐在溪水中间的石块上，望着那不停地欢快前行的溪流，她止不住放声大哭。母亲擦着眼睛说，她并没有后悔放了那只母蟹，因为她也是一位母亲，天底下所有母亲的心是一样的。

    ⑪窗外是涌动的暮色，借着昏暗的灯光，我仔细看着母亲不再光洁红润的面孔，心里忽然生出了一阵与我七岁年龄绝不相称的苍凉。

    ⑫那是多么不幸而又幸运的一只螃蟹啊，它碰上的恰好是一位母亲，这世上也只有母亲才能最懂得做母亲的心罢！

（选文略有改动）

母亲的心

    ①熬过六岁那年漫长的严冬，我终于从一场大病中清醒了过来。

    ②春日的阳光映着窗外的夹竹桃，投下斑驳的树影，母亲却明显地憔悴了，瘦弱的样子差点让我不敢认，但她的精神状态却很好，仿佛拣回了珍贵的珠宝一般小心地守护着我。

    ③久病初愈的我没胃口，家人总会变着法子哄我吃饭。那一天，我告诉母亲，很想吃螃蟹，却让家人犯了难：在物质条件极差的偏远山村，怎么可能买得到螃蟹呢！

    ④好在爱子心切的母亲自有她的法子，她很快拎着竹篓出去了。我们村子外面有很多纵横交错的溪流，六月天若翻开小溪里一块块大石头，可以找得到螃蟹。可是，在溪水还寒冽的春天，螃蟹躲在岩洞里是翻不到的。

    ⑤母亲不死心，沿着溪流一路上行，在一块块或大或小的石头下面翻找着。春天的溪水冰凉彻骨，却冻不住她心里涌动的希望。

    ⑥或许上天也怜惜母亲那深切的舐犊之情吧，在母亲双手肿胀发抖，几近绝望的时候，她终于发现了一只个头肥大的螃蟹，正在一块大石头下面迟缓地爬动着。

    ⑦母亲的惊喜可想而知，她赶忙迅捷地双手捞起了螃蟹，可是望着手里那只惶惑无措的螃蟹，母亲的手却止不住颤抖！因为那是一只母蟹，它鼓鼓的肚皮底下正围着无数只细如蚊子的小蟹，有的还爬到了母亲的手背上……

    ⑧母亲思忖了很久，把螃蟹又轻轻地放回了水里，可是刚放下，她又想起什么似的，赶紧再一次捞起了螃蟹，如是者数次。在那个春寒料峭的日子里，一向坚强能干的母亲想必正面临着她人生中一次重大的选择罢！在抓起与放下的动作的重复间，她的内心经历了怎样的一次又一次的自我交战与折磨。

    ⑨这个经过，我并没有亲眼看到，是母亲回来后坐在我床头，抚摩着我的额头细细讲给我听的。母亲说，最后一次她干脆咬咬牙，闭起双眼把螃蟹放进了竹篓，甚至已经带出了十几步路。可是竹篓里那不停的“沙沙沙”的挣扎声，最终还是让她彻底丧失了往家走的勇气，再一次跑回到溪边。放下母蟹的那一刹那，她潸然泪下！

    ⑩母亲最终是空着手回家的，在那个还带着寒意的春日里，母亲再也没能翻到第二只螃蟹。坐在溪水中间的石块上，望着那不停地欢快前行的溪流，她止不住放声大哭。母亲擦着眼睛说，她并没有后悔放了那只母蟹，因为她也是一位母亲，天底下所有母亲的心是一样的。

    ⑪窗外是涌动的暮色，借着昏暗的灯光，我仔细看着母亲不再光洁红润的面孔，心里忽然生出了一阵与我七岁年龄绝不相称的苍凉。

    ⑫那是多么不幸而又幸运的一只螃蟹啊，它碰上的恰好是一位母亲，这世上也只有母亲才能最懂得做母亲的心罢！

（选文略有改动）

    AlphaGo is a computer program that plays the board game Go.

    In March, 2016, the pride of humankind was crushed (粉碎) by a computer. Google's AlphaGo defeated the South Korean grandmaster (围棋大师) Lee Sedol four games to one, as the world looked on with shock and awe (敬畏). Artificial intelligence (AI, 人工智能) had suddenly reached a new and unexpected height.

    But as smart as AlphaGo is, it's no longer the best Go “player” in the world. Google's artificial intelligence group, DeepMind, has created the next generation of its Go-playing program, called AlphaGo Zero. The new AI program is unique in the way it learned to play Go. Instead of learning from thousands of human matches, as its predecessor (前任) did, AlphaGo Zero mastered Go in just two days without any human knowledge of the game and defeated AlphaGo by day three, reported The Guardian. It then went on to defeat AlphaGo 100 games to zero.

    To learn how to play Go, AlphaGo Zero played millions of matches against itself using only the basic rules of the game to rapidly create its own knowledge of it. Like the previous version, it used “reinforcement (增强) learning to become its own teacher,” according to DeepMind's website.

    “It's more powerful than previous approaches,” David Silver, AlphaGo's lead researcher, told The Guardian, “because by not using human data, or human expertise in any fashion, we've removed the constraints (约束) of human knowledge and it is able to create knowledge itself.”

    AlphaGo Zero's approach to self-learning is a significant advancement in AI that could be applied to help solve some of the world's biggest problems, according to a recent research report published in the journal Nature. For example, DeepMind co-founder Demis Hassabis argues that AlphaGo Zero could probably find cures for a number of serious diseases within weeks, according to The Telegraph. Indeed, the AI is now being used to study protein folding, which is connected to diseases such as Parkinson's and Alzheimer's.

    So now that AI has exceeded (超过) the bounds of human knowledge, perhaps the question is not about what AI can learn from humans, but what humans can learn from AI. We can only wait and see.

    AlphaGo is a computer program that plays the board game Go.

    In March, 2016, the pride of humankind was crushed (粉碎) by a computer. Google's AlphaGo defeated the South Korean grandmaster (围棋大师) Lee Sedol four games to one, as the world looked on with shock and awe (敬畏). Artificial intelligence (AI, 人工智能) had suddenly reached a new and unexpected height.

    But as smart as AlphaGo is, it's no longer the best Go “player” in the world. Google's artificial intelligence group, DeepMind, has created the next generation of its Go-playing program, called AlphaGo Zero. The new AI program is unique in the way it learned to play Go. Instead of learning from thousands of human matches, as its predecessor (前任) did, AlphaGo Zero mastered Go in just two days without any human knowledge of the game and defeated AlphaGo by day three, reported The Guardian. It then went on to defeat AlphaGo 100 games to zero.

    To learn how to play Go, AlphaGo Zero played millions of matches against itself using only the basic rules of the game to rapidly create its own knowledge of it. Like the previous version, it used “reinforcement (增强) learning to become its own teacher,” according to DeepMind's website.

    “It's more powerful than previous approaches,” David Silver, AlphaGo's lead researcher, told The Guardian, “because by not using human data, or human expertise in any fashion, we've removed the constraints (约束) of human knowledge and it is able to create knowledge itself.”

    AlphaGo Zero's approach to self-learning is a significant advancement in AI that could be applied to help solve some of the world's biggest problems, according to a recent research report published in the journal Nature. For example, DeepMind co-founder Demis Hassabis argues that AlphaGo Zero could probably find cures for a number of serious diseases within weeks, according to The Telegraph. Indeed, the AI is now being used to study protein folding, which is connected to diseases such as Parkinson's and Alzheimer's.

    So now that AI has exceeded (超过) the bounds of human knowledge, perhaps the question is not about what AI can learn from humans, but what humans can learn from AI. We can only wait and see.

    AlphaGo is a computer program that plays the board game Go.

    In March, 2016, the pride of humankind was crushed (粉碎) by a computer. Google's AlphaGo defeated the South Korean grandmaster (围棋大师) Lee Sedol four games to one, as the world looked on with shock and awe (敬畏). Artificial intelligence (AI, 人工智能) had suddenly reached a new and unexpected height.

    But as smart as AlphaGo is, it's no longer the best Go “player” in the world. Google's artificial intelligence group, DeepMind, has created the next generation of its Go-playing program, called AlphaGo Zero. The new AI program is unique in the way it learned to play Go. Instead of learning from thousands of human matches, as its predecessor (前任) did, AlphaGo Zero mastered Go in just two days without any human knowledge of the game and defeated AlphaGo by day three, reported The Guardian. It then went on to defeat AlphaGo 100 games to zero.

    To learn how to play Go, AlphaGo Zero played millions of matches against itself using only the basic rules of the game to rapidly create its own knowledge of it. Like the previous version, it used “reinforcement (增强) learning to become its own teacher,” according to DeepMind's website.

    “It's more powerful than previous approaches,” David Silver, AlphaGo's lead researcher, told The Guardian, “because by not using human data, or human expertise in any fashion, we've removed the constraints (约束) of human knowledge and it is able to create knowledge itself.”

    AlphaGo Zero's approach to self-learning is a significant advancement in AI that could be applied to help solve some of the world's biggest problems, according to a recent research report published in the journal Nature. For example, DeepMind co-founder Demis Hassabis argues that AlphaGo Zero could probably find cures for a number of serious diseases within weeks, according to The Telegraph. Indeed, the AI is now being used to study protein folding, which is connected to diseases such as Parkinson's and Alzheimer's.

    So now that AI has exceeded (超过) the bounds of human knowledge, perhaps the question is not about what AI can learn from humans, but what humans can learn from AI. We can only wait and see.