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A new equation for intelligence 2020-04-2824707

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Intelligence, what is it?If we take a look back at the history of how intelligence has been viewed,one seminal example has been Edsger Dijkstras famous quote that "the question of whether a machine can think is aboutas interesting as the question of whether a submarine can swim."Now, Edsger Dijkstra,when he wrote this,intended it as a criticism of the early pioneers of computer science,like Alan Turing.However, if you take a look back,and think about what have been the most empowering innovationsthat enabled us to build artificial machines that swim,and artificial machines that fly,you find that it was only through understandingthe underlying physical mechanisms of swimming and flight,that we were able to build these machines.And so, several years ago,I undertook a program to try to understand the fundamental physical mechanisms underlying intelligence.
智能,它是什么?当我们回顾在历史上智能是如何被看待的,一个开创性的例子是艾兹格·迪杰斯特拉的著名引述——关于一台机器能否思考的问题与关于一艘潜艇是否会游泳的问题几乎同样有趣。当艾兹格·迪杰斯特拉写下这句话的时候,他的用意是去批判那些早年间开辟了计算机科学的先锋,比如阿兰·图灵。然而,如果你回顾过去并予以思考,有哪些最有利于发展的创新,让我们有机会能够制造出会游泳的机器和会飞的机器,你会发现,只有通过了解游泳和飞行背后的物理机制,我们才有能力去制造这些机器。所以说,在几年前,我着手了一个项目,试图去了解智能背后的基础物理机制。
Lets take a step back.Lets first begin with a thought experiment.Pretend that youre an alien race,that doesnt know anything about Earth biology,or Earth neuroscience or Earth intelligence,but you have amazing telescopes and youre able to watch the Earth,and you have amazingly long lives,so youre able to watch the Earth over millions,even billions of years.And you observe a really strange effect.You observe that,over the course of the millennia,Earth is continually bombarded with asteroids up until a point,and that at some point,corresponding roughly to our year, 2000 AD,asteroids that are on a collision course with the Earththat otherwise would have collided mysteriously get deflected,or they detonate before they can hit the Earth.Now of course, as earthlings,we know the reason would be that were trying to save ourselves.Were trying to prevent an impact.But if youre an alien race who doesnt know any of this,doesnt have any concept of Earth intelligence,youd be forced to put together a physical theory that explains how,up until a certain point in time,asteroids that would demolish the surface of a planet mysteriously stop doing that.And so I claim that this is the same question as understanding the physical nature of intelligence.
我们先退一步说。首先,让我们从一个思维实验开始。假装你是一个外星人,你对地球上的生物学、神经科学和智能一无所知,但你有绝佳的望远镜,因此你能观望地球,你的寿命也惊人地长,所以你可以观察地球超过数百万年,甚至几十亿年。然后你观察到一个很奇怪的现象。你观察到,几千年来,地球不断地与小行星发生碰撞直到某一刻,而在那一刻,大约对应的是公元2000年,那些在地球撞击轨道上的小行星,本该相撞但却被神秘地弹开了,或者在碰到地球之前就引爆了。当然,作为地球人,我们知道其中的原因是我们正试图自我拯救。我们要防止撞击发生。但如果你是一个外星人,对这些一无所知,对地球上的智能也没有任何概念,这就迫使你去总结一种物理理论,去解释其原因,直到在某一刻,本应摧毁一个星球表面的小行星,神秘地停止了这种行为。因此我声称这个问题与理解智能的物理本质的问题是相同的。
So in this program that I undertook several years ago,I looked at a variety of different threads across science,across a variety of disciplines,that were pointing, I think,towards a single,underlying mechanism for intelligence.In cosmology, for example,there have been a variety of different threads of evidence,that our universe appears to be finely tuned for the development of intelligence, and, in particular,for the development of universal states that maximize the diversity of possible futures.In game play, for example,in Go everyone remembers in 1997,when IBMs Deep Blue beat Garry Kasparov at chess,fewer people are aware that in the past 10 years or so,the game of Go,arguably a much more challenging game,because it has a much higher branching factor,has also started to succumb to computer game players for the same reason:the best techniques right now for computers playing Go are techniquesthat try to maximize future options during game play.Finally, in robotic motion planning,there have been a variety of recent techniquesthat have tried to take advantage of abilities of robots,to maximize future freedom of action in order to accomplish complex tasks.And so, taking all of these different threads and putting them together, I asked,starting several years ago,is there an underlying mechanism for intelligencethat we can factor out of all of these different threads?Is there a single equation for intelligence?
因此,在我几年前着手的这个项目中,我研究了许多不同的线程,跨越科学界,跨越多个学科,在我看来,他们都指向一个统一的、潜在的智能机制。例如在宇宙学中,就存在着各种各样的线索,它们显示我们的宇宙就为了智能的开发,而被精准地调试过,特别是,对于发展世界各国去实现有最大多样化可能性的未来。在棋牌界,举个例子,围棋,大家都记得在1997年的时候IBM制作的机器人“深蓝”打败了世界象棋冠军加里·卡斯帕罗夫,很少有人意识到在过去10年左右的时间里,围棋,可以说是一个更具挑战性的游戏,因为它具有更高的分支系数,也已开始屈服于电脑这个游戏对手,出于同样的原因:现在,电脑下围棋的最佳技术方法是在下棋的过程中,试图最大化未来的各种可能性。最后,在机器人的运动规划中,有各种各样的新颖技术,它们有试图利用机器人的能力去将未来的行动自由最大化,从而完成复杂的任务。因此,考虑所有这些不同的线程并把它们放在一起,从几年前开始,我就在问,有没有一种潜在的智能机制可以让我们分解出所有这些不同的线程?是否存在一个关于智能的公式?
And the answer, I believe, is yes.What youre seeing is probably the closest equivalentto an E = mc2 for intelligence that Ive seen.So what youre seeing here is a statement of correspondence that intelligence is a force, F,that acts so as to maximize future freedom of action.It acts to maximize future freedom of action,or keep options open,with some strength T,with the diversity of possible accessible futures, S,up to some future time horizon, tau.In short, intelligence doesnt like to get trapped.Intelligence tries to maximize future freedom of action and keep options open.And so, given this one equation,its natural to ask,so what can you do with this?How predictive is it?Does it predict human-level intelligence?Does it predict artificial intelligence?So Im going to show you now a video that will, I think,demonstrate some of the amazing applications of just this single equation.
而我相信答案是有。你看到的可能是我所见过最接近于E=mc2的智慧。所以你在这里看到的是一张对应表,其中智能是一种力量,F,它的作用是为了便于将未来的行动自由最大化。它的作用是将未来的行动自由最大化,或是保留灵活的选择权,与一种力量T,和有多种可能性的、可实现的未来,S,一直到某个未来的开始,tau(希腊字母)。简而言之,智能不喜欢被困住。智能试图将未来的行动自由最大化,并保留选择权。所以,鉴于这一公式,你自然会问,那么这些可以让你做什么?它的预测性有多高?它能否能预测人类的智能水平?它能够预测人工智能吗?因此,我将要展示给你们一段视频,我认为,它会展示出单是这一个公式的一些惊人的应用。
Recent research in cosmology has suggested that universes that produce more disorder, or entropy,over their lifetimes should tend to have more favorable conditionsfor the existence of intelligent beings such as ourselves.But what if that tentative cosmological connectionbetween entropy and intelligence hints at a deeper relationship?What if intelligent behavior doesnt just correlate with the production of long-term entropy,but actually emerges directly from it?To find out,we developed a software engine called Entropica,designed to maximize the production of long-term entropy,of any system that it finds itself in.Amazingly, Entropica was able to pass multiple animal intelligence tests,play human games,and even earn money trading stocks,all without being instructed to do so.Here are some examples of Entropica in action.
宇宙学的最近研究反应了那些产生更多混乱、或者"熵"的宇宙,在他们的生命中应该倾向于产生更多有利的情况,让像我们这样的智慧生物得以存在。但假如那个在熵与智能之间暂定的宇宙链接暗示着更深层的关系呢?如果智能的行为不仅只与长期熵的生产相关,而是直接由其产生的呢?为了找到答案,我们开发了一个软件引擎称为Entropica,设计的意图是将长期熵的生产最大化,无论它身在任何系统内。惊人的是,Entropica通过了多个动物的智能测验、玩人类的游戏、甚至在股票交易中赚钱,而且完全没有被给出那些指示。下面是一些Entropica的行动实例。
Just like a human standing upright without falling over,here we see Entropica automatically balancing a pole using a cart.This behavior is remarkable in part,because we never gave Entropica a goal.It simply decided on its own to balance the pole.This balancing ability will have applicationsfor humanoid robotics and human assistive technologies.Just as some animals can use objects in their environmentsas tools to reach into narrow spaces,here we see that Entropica,again on its own initiative,was able to move a large disk representing an animal around,so as to cause a small disk,representing a tool,to reach into a confined space holding a third disk,and release the third disk from its initially fixed position.This tool use ability will have applications for smart manufacturing and agriculture.In addition, just as some other animals are able to cooperateby pulling opposite ends of a rope at the same time to release food,here we see that Entropica is able to accomplish a model version of that task.This cooperative ability has interesting implicationsfor economic planning and a variety of other fields.
就像人类站立不会跌到,这里我们可以看到Entropica自动地使用购物车去平衡棍子。这种行为可以说是非常卓越的,因为我们从未给Entropica设定一个目标。它自己就决定去平衡那根棍子。这种平衡能力将能应用于人形机器人和人类的辅助科技。正如一些动物可以使用环境中的物体作为工具去伸入狭窄的空间,这里我们可以看到Entropica,同样是自主的,能够移动一个表示动物的大圆盘去把一个表示工具的小圆盘,去深入一个狭窄的空间,那里有第三个圆盘,并把第三个圆盘从它初始的静态解放出来。这种工具的使用能力将能运用于智能制造业和农业。此外,正如其他一些动物能够合作起来同时去拉一根绳子的两端从而释放食物,这里我们可以看到Entropica有能力完成这项任务的模型版本。这种合作能力能够带来有趣的影响,在经济规划和各种其他领域中。
Entropica is broadly applicable to a variety of domains.For example, here we see it successfully playing a game of pong against itself,illustrating its potential for gaming.Here we see Entropica orchestrating new connections on a social network,where friends are constantly falling out of touch,and successfully keeping the network well connected.This same network orchestration ability also has applications in health care, energy, and intelligence.Here we see Entropica directing the paths of a fleet of ships,successfully discovering and utilizing the Panama Canalto globally extend its reach from the Atlantic to the Pacific.By the same token,Entropica is broadly applicable to problems in autonomous defense,logistics and transportation.
Entropica可以广泛适用于各种各样的领域。例如,在这里我们看到它成功的与自己玩乒乓球游戏,说明其在游戏界的潜力。在这里我们看到Entropica指挥着社交网络上新的关系,在这朋友们不断的失去联系并成功地保持有效的网络连接。这种相同的网络指挥能力在医疗保健、能源、和智能方面都有相关的应用。这里我们可以看到Entropica指挥一支舰队的路径,成功地发现并利用巴拿马运河,然后将其范围从大西洋到太平洋全球性地扩大。同样的,Entropica可以广泛地适用于自主防御、物流和运输的应用。
Finally, here we see Entropica spontaneously discovering and executing a buy-low,sell-high strategy on a simulated range traded stock,successfully growing assets under management exponentially.This risk management ability will have broad applications in finance and insurance.
最后,在这里我们看到Entropica自主地发现和执行一个低买高卖的策略,这是在模拟的范围交易股票上,它成功地将其管理的资产成指数升涨。这种风险管理的能力将在金融和保险领域有广泛的应用。
So what youve just seen is that a variety of signature human intelligent cognitive behaviors,such as tool use and walking upright,and social cooperation all follow from a single equation,which drives a system to maximize its future freedom of action.
你刚看到的是各种具有代表性的人类智能的认知行为,例如工具的使用、直立行走和社会合作,它们都遵循一个公式,该公式所驱动的系统是要将其未来的行动自由最大化。
Now, theres a profound irony here.Going back to the beginning of the usage of the term robot,the play "RUR,"there was always a concept that,if we developed machine intelligence,there would be a cybernetic revolt.The machines would rise up against us.One major consequence of this work is that maybe all of these decades,weve had the whole concept of cybernetic revolt in reverse.Its not that machines first become intelligent and then megalomaniacal,and try to take over the world.Its quite the opposite,that the urge to take control of all possible futuresis a more fundamental principle than that of intelligencethat general intelligence may in fact emerge directly from this sort of control-grabbing,rather than vice versa.
现在,这里存在一个深刻的讽刺。回到最初,机器人这个术语的用法,RUR,这出戏,总存在一种概念,就是如果我们开发了机器智能,就会产生一个人工智能的叛变。机器会奋起反抗我们。这项工作的主要成果之一就是也许这几十年间,我们对于人工智能的叛变的整个概念是颠倒的。机器不是先有了智慧然后才变得狂妄并试图接管世界的。其实几乎是相反的,那种迫切的欲望,想要控制所有未来的所有可能是比智能更基本的一个原则,综合智能事实上可能是从这种控制欲中直接产生的,而不是反之。
Another important consequence is goal seeking.Im often asked,how does the ability to seek goals follow from this sort of framework?And the answer is,the ability to seek goals will follow directlyfrom this in the following sense:just like you would travel through a tunnel,a bottleneck in your future path space,in order to achieve many other diverse objectives later on,or just like you would invest in a financial security,reducing your short-term liquidity,in order to increase your wealth over the long term,goal seeking emerges directly from a long-term driveto increase future freedom of action.
另一个重要的成果是寻找目标。我经常被问道,寻找目标的能力怎么会遵循这种框架结构呢?答案是,寻找目标的能力将直接遵循它,道理是这样的:就像你要穿过一条隧道,你未来道路空间中的一个瓶颈,为了在以后实现许多其他的各种目标,或者就像你会投资于金融证券,减少你的短期流动性,从而长远的增加你的财富,目标的寻求直接涌现于长期的驱动,为了增加未来的行动自由。
Finally, Richard Feynman, famous physicist,once wrote that if human civilization were destroyed,and you could pass only a single concept on to our descendants to help them rebuild civilization,that concept should be that all matter around us is made out of tiny elementsthat attract each other when theyre far apart,but repel each other when theyre close together.My equivalent of that statement to pass on to descendants,to help them build artificial intelligences,or to help them understand human intelligence,is the following:Intelligence should be viewed as a physical process,that tries to maximize future freedom of action,and avoid constraints in its own future.
最后,理查德·费曼,这位著名的物理学家,曾经写道,如果人类文明被摧毁,并且你只能将一个概念传承给我们的后代,来帮助他们重建文明,这个概念应该是我们身边的一切物质都是由微小的元素组成的,它们之间距离远的时候会相互吸引,但在靠的很近时它们会互相排斥。我与这句话等同的声明,来传递给后代,帮助他们建立人工智能,或是帮助他们理解人类的智慧,是如下的话:智能应该被看作是一个物理过程,它试图将未来的行动自由最大化,并且避免在自己的未来中的约束。
Thank you very much.
非常感谢。

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