回答“为什么新思想会消亡”和“如何应对”这两个问题?

I suspect a lot of the lack of progress is due to the massive influx of capital and entrenched wealth in the industry. Sounds counterintuitive, but I think it's become conventional wisdom that any new idea gets one shot; if it doesn't make it at the first try, it can't come back. It gets bought by someone with entrenched interests, or just FAILs, and the energy is gone. A couple examples are tablet computers, and integrated office software. The Newton and several others had real potential, but ended up (through competitive attrition and bad judgment) squandering their birthrights, killing whole categories. (I was especially fond of Ashton Tate's Framework; but I'm still stuck with Word and Excel).

怎么办呢?首先想到的是Wm。莎士比亚的建议:“让我们杀了所有的律师。”但恐怕他们现在装备太精良了。实际上，我认为最好的选择是找到某种开源计划。它们似乎比其他选择更好地保持可访问性和增量改进。但是这个行业已经变得足够大了，所以某种有机的合作机制是必要的。

I also think that there's a dynamic that says that the entrenched interests (especially platforms) require a substantial amount of change - churn - to justify continuing revenue streams; and this absorbs a lot of creative energy that could have been spent in better ways. Look how much time we spend treading water with the newest iteration from Microsoft or Sun or Linux or Firefox, making changes to systems that for the most part work fine already. It's not because they are evil, it's just built into the industry. There's no such thing as Stable Equilibrium; all the feedback mechanisms are positive, favoring change over stability. (Did you ever see a feature withdrawn, or a change retracted?)

关于SO的另一个讨论线索是臭鼬工厂综合症(参考:Geoffrey Moore):在大型组织中，真正的创新几乎总是(90%以上)出现在自发出现的未经授权的项目中，这些项目完全由个人或小团队的主动性推动(通常会受到正式的管理等级的反对)。所以:质疑权威，反抗体制。

我不知道是否有人已经回答了，“机器学习”作为一个重要的新发展，正在迅速发展。智能垃圾邮件过滤、股市预测、机器人等智能机器……

也许，机器智能会是下一个大事件。

我相信单元测试、TDD和持续集成是1980年之后的重大发明。

在操作系统核心开发中使用函数式编程/语言。

来回答一个稍微不同的问题。我认为我们需要在隐私、信任和声誉方面有大的想法。我的电脑几乎能捕捉到关于我的一切，我在哪里，我说了什么，我打了什么，我看到了什么……大量的信息和同等数量的实体(人、商店、网站、服务)，我可能想与他们共享其中的一些信息，即使它只是一个数据块。

我的信息需要挖掘(不是谷歌的，Facebook的或苹果的)。我的计算机需要代表我使用它，因此信任需要端到端。这样我们就可以将新的信息中间商去中介化。

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