人工智慧英文版論文

　　人工智慧AI系統被認為是神經網路，可以識別圖片，翻譯，甚至精通古老的遊戲。以下是小編精心整理的的相關資料，希望對你有幫助!

　　篇一

　　Google's AI Reasons Its Way around the London

　　Underground

　　谷歌人工智慧推匯出環繞

　　倫敦地鐵系統的路線

　　DeepMind‟s latest technique uses external memory to solve tasks that require logic and reasoning—a

　　step toward more humanlike AI

　　維和推理能力的任務

　　By Elizabeth Gibney, Nature magazine on October 14, 2016

　　伊麗莎白.吉布尼2016年10月14日發表於《自然》雜誌

　　深度思維最新技術使用了外部儲存來解決需要邏輯思

　　Artificial-intelligence AI systems known as neural networks can recognize images, translate languages and even master the ancient game of Go. But their limited ability to represent complex relationships between data or variables has prevented them from conquering tasks that require logic and reasoning.

　　人工智慧AI系統被認為是神經網路，可以識別圖片，翻譯，甚至精通古老的遊戲。但他們描繪資料或變數之間的複雜關係的能力有限，這妨礙了他們克服需要邏輯思維和推理能力的任務。

　　In a paper published in Nature on October 12, the

　　Google-owned company DeepMind in London reveals that it has taken a step towards overcoming this hurdle by creating a neural

　　network with an external memory. The combination allows the neural network not only to learn, but to use memory to store and recall facts to make inferences like a conventional algorithm. This in turn enables it to tackle problems such as navigating the London Underground without any prior knowledge and solving logic puzzles. Though solving these problems would not be impressive for an algorithm programmed to do so, the hybrid system manages to accomplish this without any predefined rules.

　　在10月12日《自然》雜誌中發表的一篇論文中，谷歌在倫敦的子公司深度思維展示了他們通過結合外部儲存創造了一個神經網路，來進一步克服這些障礙。這種和外部儲存的結合不僅允許神經網路學習，還可以通過儲存器來儲存和回憶事件，並以此來像正常情況那樣做推斷。這反過來能夠讓它解決難題，比如在沒有任何經驗的情況下操控倫敦地鐵，比如解決邏輯謎題。儘管對於一個演算法程式來說做到這點並不會令人印象深刻，但這個混合系統在沒有任何先決條件的情況下做到了這點。

　　Although the approach is not entirely new—DeepMind itself reported attempting a similar feat in a preprint in 2014—“the progress made in this paper is remarkable”, says Yoshua Bengio, a computer scientist at the University of Montreal in Canada.

　　雖然這個方法不是一個全新的技術——深度思維自己就在2014年報告過他們嘗試了一種相似的技術——但“在論文中的這個進步是非凡的”，加拿大蒙特利爾的計算機學家本吉奧.本希奧讚歎道。

　　MEMORY MAGIC

　　記憶魔法

　　A neural network learns by strengthening connections between virtual neuron-like units. Without a memory, such a network might need to see a specific London Undeground map thousands of times to learn the best way to navigate the tube.

　　神經網路通過加強虛擬神經元之間的聯絡來學習。如果沒有儲存器，這樣一個網路可能需要看一副特定的倫敦地鐵地圖數千次來學習最佳路線。

　　DeepMind's new system—which they call a 'differentiable

　　neural computer'—can make sense of a map it has never seen before. It first trains its neural network on randomly generated map-like structures which could represent stations connected by lines, or

　　other relationships, in the process learning how to store descriptions of these relationships in its external memory as well as answer questions about them. Confronted with a new map, the DeepMind system can write these new relationships—connections between Underground stations, in one example from the paper—to memory, and recall it to plan a route.

　　深度思維的新系統——他們稱它為微分神經計算機——可以理解它從未見過的地圖。第一次訓練神經網路是在隨機生成的類似結構的地圖上被鐵路線連結的車站，或者其他關係，在這個過程中學習如何將這些關係的描述儲存在它的外部儲存器並且回答問題。面對一個新的地圖，深度思維的系統可以把這些新關係——按照一個圖紙上例子來連線各地鐵站之間的關係——寫到儲存器，並能夠回憶這些關係然後計劃路線。

　　DeepMind‟s AI system used the same technique to tackle

　　puzzles that require reasoning. After training on 20 different types of question-and-answer problems, it learnt to make accurate deductions.

　　For example, the system deduced correctly that a ball is in a

　　playground, having been informed that “John picked up the football” and “John is in the playground”. It got such problems right more than 96% of the time. The system performed better than „recurrent neural networks‟, which also have a memory, but one that is in the fabric of the network itself, and so is less flexible than an external memory.

　　深度思維的人工智慧系統使用同樣的方法來處理需要推理能力的智力遊戲。在通過20種不同型別的問答訓練之後，它學會了做出準確的推論。例如，系統通過被告之“約翰抓著足球”和“約翰在操場上”準確的推斷出一個球在操場上。答對問題的概率超過了96%。這個系統的效率比擁有一個內部儲存器的週期神經網路更高，也更靈活。

　　Although the DeepMind technique has proven itself on only artificial problems, it could be applied to real-world tasks that involve making inferences from huge amounts of data. This could solve

　　questions whose answers are not explicitly stated in the data set, says Alex Graves, a computer scientist at DeepMind and a co-author on the paper. For example, to determine whether two people lived in the same country at the same time, the system might collate facts from their respective Wikipedia pages.

　　雖然深度思維的技術已被證明只針對人工問題，但它能夠被應用到需要通過海量資料來進行推斷的真實世界的工作。這能夠解決那些在資料中沒有明確答案的問題。來自深度思維的電腦科學家，研究報告的合著者，亞歷克斯·格雷夫斯介紹說。例如，對於判斷兩人是否在同一時間住在同一個國家，系統可能會核對他們各自在維基百科上的事項。

　　Although the puzzles tackled by DeepMind‟s AI are simple, Bengio sees the paper as a signal that neural networks are advancing beyond mere pattern recognition to human-like tasks such as

　　reasoning. “This extension is very important if we want to approach human-level AI.”

　　雖然對於深度思維的人工智慧來說，智力遊戲很簡單，但本希奧認為該論文是一個訊號，它表明神經網路正在跨越單純的模式識別，成長到能夠做人類才能做的任務，例如推理。“如果我們想實現像人一樣的人工智慧，這次突破是非常重要的。”

　　This article is reproduced with permission and was first

　　published on October 13, 2016.

　　篇二

　　The mid-21st century, as a result of climate warming, melting ice caps north and south poles, the Earth many cities have been submerged in a vast expanse of water in the. At this point, the human science and technology has reached a very high level of artificial intelligence is that human beings invented the robot to cope with the worst one of the natural environment of scientific and technological means.

　　觀後感 Today finally put admire already a long time in the 2001 science fiction film finished, couldn't help exclaim 1 "god is!!!" I don't talk nonsense, plot is too touching! When David abandoned by mother, when he and machine teddy bear together, through the tough time, when he believed in fairy tales, Pinocchio, the blue fairy can turn themselves into reality, so my mother would love him, when he from she fell into the ocean at the end of the world at that moment, when he saw the blue fairy, at the bottom of the sea constantly pray for her, this is two thousand... Two thousand years later, the human existence, as a friendly alien saved him from being frozen sea, he's still pray... Every moment, it is so touching. Every picture is so shock aestheticism, every scene, is so touching... A robot of artificial intelligence can actually "love" interpretation so deep, touched, Thorough, incisively and vividly, touching

　　When he saw the real blue fairy illusion aliens, the blue fairy promised he could put the mother to life, but must have the wreckage, and only a day! This day is the happiest day of David life!