HTM系统(分层时态记忆)。

人工智能的一种新方法，由杰夫·霍金斯通过《论智能》一书发起。

现在是一家名为Numenta的公司，通过开发“真正的”人工智能来测试这些想法，并邀请社区通过sdk使用该系统来参与。

它更多的是从头开始构建机器智能，而不是试图模仿人类的推理。

现代阴影语言和现代gpu的流行。

GPU也是一个低成本的并行超级计算机，拥有CUDA和OpenCL等工具，可以快速编写高级并行代码。感谢所有在那里压低这些越来越令人印象深刻的硬件奇迹价格的玩家。在接下来的五年里，我希望每台售出的新电脑(iphone也一样)都能基本具备运行大量并行代码的能力，就像24位彩色或32位保护模式一样。

我认为自20世纪80年代以来发明的最好的想法将是我们不知道的。要么是因为它们很小，无处不在，以至于不引人注意，要么是因为它们的受欢迎程度还没有真正起飞。

前者的一个例子是单击并拖动以选择文本的一部分。我相信这是1984年首次出现在麦金塔电脑上。在此之前，您有单独的按钮用于选择选择的开始和结束。相当繁重。

后者的一个例子是(可能是)可视化编程语言。我不是说像hypercard，我是说像Max/MSP, Prograph, Quartz Composer, yahoo pipes等。目前它们确实是小众的，但我认为，除了思想分享之外，没有什么能阻止它们像标准编程语言一样具有表现力和强大的功能。

可视化编程语言有效地加强了引用透明性的函数式编程范式。这对于代码来说是一个非常有用的属性。他们执行这一点的方式也不是人为的——这只是由于他们使用的比喻。

VPL让那些本来不会编程的人也能编程，比如有语言障碍的人，比如阅读困难的人，甚至只是需要简单节省时间的门外汉。专业程序员可能会对此嗤之以鼻，但就我个人而言，我认为如果编程成为一种真正无处不在的技能，就像识字一样，那就太好了。

就目前来看，VPL只是一个小众的兴趣，还没有真正成为主流。

我们应该做些什么不同的事情

all computer science majors should be required to double major- coupling the CS major with one of the humanities. Painting, literature, design, psychology, history, english, whatever. A lot of the problem is that the industry is populated with people that have a really narrow and unimaginative understanding of the world, and therefore can't begin to imagine a computer working any significantly differently than it already does. (if it helps, you can imagine that I'm talking about someone other than you, the person reading this.) Mathematics is great, but in the end it's just a tool for achieving. we need experts who understand the nature of creativity, who also understand technology.

But even if we have them, there needs to be an environment where there's a possibility that doing something new would be worth the risk. It's 100 times more likely that anything truly new gets rejected out of hand, rather viciously. (the newton is an example of this). so we need a much higher tolerance for failure. We should not be afraid to try an idea which has failed in the past. We should not fully reject our own failures- and we should learn to recognize when we have failed. We should not see failure as a bad thing, and so we shouldn't lie to ourselves or to others about it. We should just get used to it, because it is just about the only constant in this ever changing industry. Post mortems are useful in this regard.

One of the more interesting things, about smalltalk, I think, was not the language itself, but the process that was used to arrive at the design of smalltalk. The iterative design process, going through many many revisions- But also very carefully and critically identifying the flaws of the existing system, and finding solutions in the next one. The more perspectives, and the broader the perspectives we have on the situation, the better we can judge where the mistakes and problems are. So don't just study computer science. Study as many other academic subjects as you can get yourself to be interested in.

我认为没有什么重要的东西被发明出来。但自80年代以来，人们对软件的看法发生了很大变化。那时有更多的理论家参与其中，现在你在一个程序员论坛上问这个问题。

当时的大多数想法都没有得到实施，或者即使实施了，它们也没有任何真正的重要性，因为当时的软件行业还不存在，市场营销、人力资源、开发阶段或alpha版本也不存在:)。

Another reason for this lack of inventions is the fact that most people use Windows:) dont get me wrong, i do hate M$, but look at it this way: you have a perfectly working interface, with nothing new to add to it, maybe just some new colored buttons. Its also closed enough so you wont be able to to anything with it without breaking it. Thats why i prefer open apps, this way you get more "open" people, to whom yo can actually talk, ask then questions, propose new ideeas that actually gets implemented, or at least put on an open todo-list, thus you get some kind of "evolution". You dont really see anything new because you are stuck with the same basic interface "invented" lots of years ago... did anyone actually tried ION window-manager in a production environment? It has a new kind of interface, and actually lets you do things faster, event it it looks quirky

M$, Adobe..you name it,holds lots of patents so you wont be able to base your work on them, or derivatives(you also wont know what kind of undeveloped tehnologies they hold). Look at MP3 and GIF as examples( i belive that they are both free formats now, but they are also kinda dead..) MP3 is the 'king' of audio evend if there are few algorithms out there much better that it..but didnt get enough traction because they weren't pushed on the consumer market. The GIF... come on, 256 colors??? From this point of voew i'm curios how many people from this thread are working on something "open" that will get to be reused in some other projects, and how many on "closed", protected by NDA's projects?

即使这听起来有点像“免费的威利”，但在80年代，软件是免费的，所有东西都有文档，所有硬件都更简单，更容易使用……同时也更加有限，所以人们并没有浪费时间去执行3d游戏或网页，而是致力于真正的算法。

上世纪八十年代初，施乐帕洛阿尔托研究中心对计算机蠕虫进行了研究。

摘自John Shoch和Jon Hupp的“蠕虫”程序——分布式计算的早期经验”(ACM通讯，1982年3月，第25卷第3期，172-180页，1982年3月):

In The Shockwave Rider, J. Brunner developed the notion of an omnipotent "tapeworm" program running loose through a network of computers - an idea which may seem rather disturbing, but which is also quite beyond our current capabilities. The basic model, however, remains a very provocative one: a program or a computation that can move from machine to machine, harnessing resources as needed, and replicating itself when necessary. In a similar vein, we once described a computational model based upon the classic science-fiction film, The Blob: a program that started out running in one machine, but as its appetite for computing cycles grew, it could reach out, find unused machines, and grow to encompass those resources. In the middle of the night, such a program could mobilize hundreds of machines in one building; in the morning, as users reclaimed their machines, the "blob" would have to retreat in an orderly manner, gathering up the intermediate results of its computation. Holed up in one or two machines during the day, the program could emerge again later as resources became available, again expanding the computation. (This affinity for nighttime exploration led one researcher to describe these as "vampire programs.")

引用艾伦·凯的话:“预测未来最好的方法就是创造未来。”

基础设施的改变使家庭和办公室都能接入互联网。

记录并接受了从W3C到api的标准

除此之外，我们所认为的大多数新事物都比你想象的要久远得多(例如GUI, OOP)。