aiyan从点滴做起作文

要想成就大事业，必先从小事做起。正可谓是“一屋不扫，何以扫天下”。

古代著名工匠鲁班从单纯地练习将木头砍成四方形开始，经数年刻苦练习，最终成为名流千古的土木建筑发明家。

鲁班曾拜一名知识渊博的老工匠师傅向他学艺。他每天早出晚归，按师傅的旨意，从练习砍木头开始，经苦练到熟练以后，又开始进行砍木块、木条的基础训练。后来再制作各种小模型。日积月累，有一天他终于自己发明创造并制出了第一架活动小亭-------现在的伞的“雏形”。后来又成为了著名的工匠、土木建筑发明家。

我认为鲁班之所以会有昔日的辉煌，是因为他当日有恒心能从小事做起，技术、经验与日俱增，才能有此成就。我领悟到做任何事都要从小事做起。

建议你还是学习AI吧，三个软件我都用过，刚开始我也是用CDR的，后来换苹果电脑的时候没有CDR软件（有，但是没有最新版的，是很老的版本！不给力）。当时我们公司也是有人用FREEHAND的，但是与PS配合不够。而且矢量功能不够强。

AI现在是比较普遍的设计软件，不管PC还是MAC都有最新版，而且我做平面十年时间，基本上身边的朋友和公司都是用的AI，就像我们公司面试，不会AI的基本不考虑！

AI由著名的Adobe

Illustrator生成

Adobe

Illustrator

是一款矢量图编辑软件

目前的版本已经到CS3不久CS4也将在中国投放市场

EPS是封装的PS格式，可以用CorelDRRW\Illustrator\FREEHAND等软件续编

一般输出菲林或转换格式或置入其他软件多采用这种格式

CDR是由CorelDRRW生成

CorelDRRW也是一款大众矢量图编辑软件

目前的版本已经到X4但使用量最大的版本是CD9和CD12

WMF是一种矢量格式，可以由大多数的矢量图软件打开编辑

FREEHAND也是一种矢量图软件，MAC\PC机上都有，最开始应用于MAC机上

最高版为2004MXC，自从Adobe公司成功收购FREEHAND后再无新的版本

FREEHAND作为一个老牌的矢量图编辑软件从此终结简直是矢量编辑史上的一大损失

FREEHAND是所以矢量编辑软件中最小的运行最快的软件，但缺点就是在色彩显示方面太过于不尽人意了

Artificial Intelligence (AI) is the intelligence of machines and the branch of computer science which aims to create it Textbooks define the field as "the study and design of intelligent agents,"[1] where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success[2] John McCarthy, who coined the term in 1956,[3] defines it as "the science and engineering of making intelligent machines"[4]

The field was founded on the claim that a central property of human beings, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine[5] This raises philosophical issues about the nature of the mind and limits of scientific hubris, issues which have been addressed by myth, fiction and philosophy since antiquity[6] Artificial intelligence has been the subject of breathtaking optimism,[7] has suffered stunning setbacks[8] and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science[9]

AI research is highly technical and specialized, deeply divided into subfields that often fail to communicate with each other[10] Subfields have grown up around particular institutions, the work of individual researchers, the solution of specific problems, longstanding differences of opinion about how AI should be done and the application of widely differing tools The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects[11] General intelligence (or "strong AI") is still a long-term goal of (some) research[12]

Thinking machines and artificial beings appear in Greek myths, such as Talos of Crete, the golden robots of Hephaestus and Pygmalion's Galatea[13] Human likenesses believed to have intelligence were built in every major civilization: animated statues were worshipped in Egypt and Greece[14] and humanoid automatons were built by Yan Shi,[15] Hero of Alexandria,[16] Al-Jazari[17] and Wolfgang von Kempelen[18] It was also widely believed that artificial beings had been created by Jābir ibn Hayyān,[19] Judah Loew[20] and Paracelsus[21] By the 19th and 20th centuries, artificial beings had become a common feature in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's RUR (Rossum's Universal Robots)[22] Pamela McCorduck argues that all of these are examples of an ancient urge, as she describes it, "to forge the gods"[6] Stories of these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence

The problem of simulating (or creating) intelligence has been broken down into a number of specific sub-problems These consist of particular traits or capabilities that researchers would like an intelligent system to display The traits described below have received the most attention[11]

[edit] Deduction, reasoning, problem solving

Early AI researchers developed algorithms that imitated the step-by-step reasoning that human beings use when they solve puzzles, play board games or make logical deductions[39] By the late 80s and 90s, AI research had also developed highly successful methods for dealing with uncertain or incomplete information, employing concepts from probability and economics[40]

For difficult problems, most of these algorithms can require enormous computational resources — most experience a "combinatorial explosion": the amount of memory or computer time required becomes astronomical when the problem goes beyond a certain size The search for more efficient problem solving algorithms is a high priority for AI research[41]

Human beings solve most of their problems using fast, intuitive judgments rather than the conscious, step-by-step deduction that early AI research was able to model[42] AI has made some progress at imitating this kind of "sub-symbolic" problem solving: embodied approaches emphasize the importance of sensorimotor skills to higher reasoning; neural net research attempts to simulate the structures inside human and animal brains that gives rise to this skill

General intelligence

Main articles: Strong AI and AI-complete

Most researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them[12] A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project[74]

Many of the problems above are considered AI-complete: to solve one problem, you must solve them all For example, even a straightforward, specific task like machine translation requires that the machine follow the author's argument (reason), know what is being talked about (knowledge), and faithfully reproduce the author's intention (social intelligence) Machine translation, therefore, is believed to be AI-complete: it may require strong AI to be done as well as humans can do it[75]

[edit] Approaches

There is no established unifying theory or paradigm that guides AI research Researchers disagree about many issues[76] A few of the most long standing questions that have remained unanswered are these: should artificial intelligence simulate natural intelligence, by studying psychology or neurology Or is human biology as irrelevant to AI research as bird biology is to aeronautical engineering[77] Can intelligent behavior be described using simple, elegant principles (such as logic or optimization) Or does it necessarily require solving a large number of completely unrelated problems[78] Can intelligence be reproduced using high-level symbols, similar to words and ideas Or does it require "sub-symbolic" processing[79]

[edit] Cybernetics and brain simulation

Main articles: Cybernetics and Computational neuroscience

There is no consensus on how closely the brain should be simulatedIn the 1940s and 1950s, a number of researchers explored the connection between neurology, information theory, and cybernetics Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W Grey Walter's turtles and the Johns Hopkins Beast Many of these researchers gathered for meetings of the Teleological Society at Princeton University and the Ratio Club in England[24] By 1960, this approach was largely abandoned, although elements of it would be revived in the 1980s

How can one determine if an agent is intelligent In 1950, Alan Turing proposed a general procedure to test the intelligence of an agent now known as the Turing test This procedure allows almost all the major problems of artificial intelligence to be tested However, it is a very difficult challenge and at present all agents fail

Artificial intelligence can also be evaluated on specific problems such as small problems in chemistry, hand-writing recognition and game-playing Such tests have been termed subject matter expert Turing tests Smaller problems provide more achievable goals and there are an ever-increasing number of positive results

The broad classes of outcome for an AI test are:

Optimal: it is not possible to perform better

Strong super-human: performs better than all humans

Super-human: performs better than most humans

Sub-human: performs worse than most humans

For example, performance at draughts is optimal,[143] performance at chess is super-human and nearing strong super-human,[144] and performance at many everyday tasks performed by humans is sub-human

A quite different approach is based on measuring machine intelligence through tests which are developed from mathematical definitions of intelligence Examples of this kind of tests start in the late nineties devising intelligence tests using notions from Kolmogorov Complexity and compression [145] [146] Similar definitions of machine intelligence have been put forward by Marcus Hutter in his book Universal Artificial Intelligence (Springer 2005), which was further developed by Legg and Hutter [147] Mathematical definitions have, as one advantage, that they could be applied to nonhuman intelligences and in the absence of human testers

AI is a common topic in both science fiction and in projections about the future of technology and society The existence of an artificial intelligence that rivals human intelligence raises difficult ethical issues and the potential power of the technology inspires both hopes and fears

Mary Shelley's Frankenstein,[160] considers a key issue in the ethics of artificial intelligence: if a machine can be created that has intelligence, could it also feel If it can feel, does it have the same rights as a human being The idea also appears in modern science fiction: the film Artificial Intelligence: AI considers a machine in the form of a small boy which has been given the ability to feel human emotions, including, tragically, the capacity to suffer This issue, now known as "robot rights", is currently being considered by, for example, California's Institute for the Future,[161] although many critics believe that the discussion is premature[162]

Another issue explored by both science fiction writers and futurists is the impact of artificial intelligence on society In fiction, AI has appeared as a servant (R2D2 in Star Wars), a law enforcer (KITT "Knight Rider"), a comrade (Lt Commander Data in Star Trek), a conqueror (The Matrix), a dictator (With Folded Hands), an exterminator (Terminator, Battlestar Galactica), an extension to human abilities (Ghost in the Shell) and the saviour of the human race (R Daneel Olivaw in the Foundation Series) Academic sources have considered such consequences as: a decreased demand for human labor,[163] the enhancement of human ability or experience,[164] and a need for redefinition of human identity and basic values[165]

Several futurists argue that artificial intelligence will transcend the limits of progress and fundamentally transform humanity Ray Kurzweil has used Moore's law (which describes the relentless exponential improvement in digital technology with uncanny accuracy) to calculate that desktop computers will have the same processing power as human brains by the year 2029, and that by 2045 artificial intelligence will reach a point where it is able to improve itself at a rate that far exceeds anything conceivable in the past, a scenario that science fiction writer Vernor Vinge named the "technological singularity"[164] Edward Fredkin argues that "artificial intelligence is the next stage in evolution,"[166] an idea first proposed by Samuel Butler's "Darwin among the Machines" (1863), and expanded upon by George Dyson in his book of the same name in 1998 Several futurists and science fiction writers have predicted that human beings and machines will merge in the future into cyborgs that are more capable and powerful than either This idea, called transhumanism, which has roots in Aldous Huxley and Robert Ettinger, is now associated with robot designer Hans Moravec, cyberneticist Kevin Warwick and inventor Ray Kurzweil[164] Transhumanism has been illustrated in fiction as well, for example in the manga Ghost in the Shell and the science fiction series Dune Pamela McCorduck writes that these scenarios are expressions of the ancient human desire to, as she calls it, "forge the gods"[6]