3-Ant Intelligence
世界上最大的蚂蚁英语iq题
世界上最大的蚂蚁英语iq题The World's Largest Ant IQ TestAnts have long been a source of fascination for both scientists and the general public alike. These small, ubiquitous creatures have captivated our imagination with their intricate social structures, remarkable feats of engineering, and seemingly intelligent behavior. However, the notion of "ant intelligence" remains a topic of much debate and speculation.In a groundbreaking study conducted by a team of researchers from the University of Cambridge, a new approach was taken to assess the cognitive abilities of ants. Rather than relying on traditional measures of intelligence, such as problem-solving tasks or memory tests, the researchers decided to create the world's largest ant IQ test. The goal was to push the boundaries of our understanding of ant cognition and challenge the preconceptions that have long dominated the field.The test itself was a complex and multifaceted examination, designed to assess a wide range of cognitive skills in ants. It included tasks that tested their spatial awareness, pattern recognition, decision-making abilities, and even their capacity for abstractreasoning. The researchers painstakingly developed a series of intricate mazes, puzzles, and problem-solving scenarios, each carefully calibrated to push the ants to their cognitive limits.The process of administering the test was no easy feat. Ants, being the diminutive creatures they are, required specialized equipment and meticulous handling to ensure the integrity of the results. The researchers constructed a series of high-tech, ant-sized arenas equipped with advanced sensors and cameras to monitor the ants' every move. Each individual ant was carefully selected, marked, and tracked throughout the testing process, ensuring that the data collected was both comprehensive and reliable.As the study progressed, the researchers were astounded by the sheer complexity and diversity of the ants' responses. Rather than the expected uniformity of behavior, the ants demonstrated a remarkable degree of individual variation and adaptability. Some ants excelled at certain tasks, while others struggled, revealing a level of cognitive heterogeneity that had not been previously observed.One of the most surprising findings was the ants' ability to solve complex problems through innovative, and sometimes unexpected, strategies. In one particularly challenging maze, the researchers observed ants using their antennae to "feel" their way through the obstacles, demonstrating a level of spatial awareness and problem-solving skills that rivaled those of much larger, more cognitively advanced animals.Another intriguing discovery was the ants' capacity for abstract reasoning. In one task, the ants were presented with a series of shapes and patterns and asked to identify the "odd one out." To the researchers' amazement, the ants were able to consistently select the correct shape, suggesting a level of pattern recognition and conceptual understanding that challenged the traditional view of ant intelligence.As the study progressed, the researchers began to uncover a fascinating hierarchy of cognitive abilities within the ant colony. While some ants excelled at specific tasks, others demonstrated a more generalized intelligence, able to adapt and problem-solve across a wide range of scenarios. This discovery led the researchers to suggest that the concept of "ant intelligence" may be far more nuanced and complex than previously thought.The implications of this study are far-reaching, not only for our understanding of ant cognition but for the broader field of animal intelligence. The findings suggest that even the smallest and seemingly simplest of creatures may possess cognitive capacities that challenge our preconceptions and push the boundaries of what we consider to be "intelligent" behavior.Moreover, the study has sparked a renewed interest in the potential applications of ant-inspired problem-solving and decision-making strategies. The researchers believe that by better understanding the cognitive processes of ants, we may be able to develop new approaches to complex problem-solving, optimization, and even artificial intelligence.As the research continues, the world's largest ant IQ test remains a testament to the boundless curiosity and ingenuity of the human mind. By challenging our assumptions and pushing the limits of our understanding, this study has opened up new avenues of exploration, inviting us to look at the world through the eyes of these remarkable creatures and to uncover the secrets of the vast, complex, and often surprising world of ant intelligence.。
托福听力tpo46 lecture1、2、3、4 原文+题目+答案+译文
托福听力tpo46lecture1、2、3、4原文+题目+答案+译文Lecture1 (2)原文 (2)题目 (4)答案 (6)译文 (6)Lecture2 (8)原文 (8)题目 (10)答案 (12)译文 (12)Lecture3 (14)原文 (14)题目 (16)答案 (18)译文 (18)Lecture4 (19)原文 (19)题目 (22)答案 (24)译文 (24)Lecture1原文NARRATOR:Listen to part of a lecture in a biology class.FEMALE PROFESSOR:I'd like to continue our discussion of animal behavior and start off today's class by focusing on a concept we haven't yet touched upon—swarm intelligence.Swarm intelligence is a collective behavior that emerges from a group of animals,like a colony of termites,a school of fish,or a flock of birds.Let's first consider the principles behind swarm intelligence,and we'll use the ant as our model.Now,an ant on its own is not that smart.When you have a group of ants,however, there you have efficiency in action.You see,there's no leader running an ant colony. Each individual,each individual ant operates by instinctively following a simple set of rules when foraging for food.Rule number1:Deposit a chemical marker…called a pheromone.And rule2:Follow the strongest pheromone path.The strongest pheromone path is advantageous to ants seeking food.So,for example,when ants leave the nest,they deposit a pheromone trail along the route they take.If they find food,they return to the nest on the same path and the pheromone trail gets stronger—it's doubled in strength.Because an ant that took a shorter path returns first,its pheromone trail is stronger,and other ants will follow it, according to rule2.And as more ants travel that path,the pheromone trail gets even stronger.So,what's happening here?Each ant follows two very basic rules,and each ant acts on information it finds in its immediate local environment.And it's important to note: Even though none of the individual ants is aware of the bigger plan,they collectively choose the shortest path between the nest and a food source because it's the most reinforced path.By the way,a-a few of you have asked me about the relevance of what we're studying to everyday life.And swarm intelligence offers several good examples of how concepts in biology can be applied to other fields.Well,businesses have been able to use this approach of following simple rules when designing complex systems,for instance,in telephone networks.When a call is placed from one city to another,it has to connect through a number of nodes along the way.At each point,a decision has to be made:Which direction does the call go from here?Well,a computer program was developed to answer this question based on rules that are similar to the ones that ants use to find food.Remember,individual ants deposit pheromones,and they follow the path that is most reinforced.Now,in the phone network,a computer monitors the connection speed of each path, and identifies the paths that are currently the fastest—the least crowded parts of the network.And this information,converted into a numeric code,is deposited at the network nodes.This reinforces the paths that are least crowded at the moment. The rule the telephone network follows is to always select the path that is most reinforced.So,similar to the ant's behavior,at each intermediate node,the call follows the path that is most reinforced.This leads to an outcome which is beneficial to the network as a whole,and calls get through faster.But getting back to animal behavior,another example of swarm intelligence is the way flocks of birds are able to fly together so cohesively.How do they coordinate their movements and know where they're supposed to be?Well,it basically boils down to three rules that each bird seems to follow.Rule1:Stay close to nearby birds.Rule2:Avoid collision with nearby birds.And rule3:Move in the average speed and direction of nearby birds.Oh,and by the way,if you're wondering how this approach can be of practical use for humans:The movie industry had been trying to create computer-generated flocks of birds in movie scenes.The question was how to do it easily on a large scale?A researcher used these threerules in a computer graphics program,and it worked!There have also been attempts to create computer-generated crowds of people using this bird flocking model of swarm intelligence.However,I'm not surprised that more research is needed.The three rules I mentioned might be great for bird simulations,but they don't take into account the complexity and unpredictability of human behavior.So,if you want to create crowds of people in a realistic way,that computer model might be too limited.题目1.What is the lecture mainly about?A.Various methods that ants use to locate foodB.A collective behavior common to humans and animalsC.A type of animal behavior and its application by humansD.Strategies that flocks of birds use to stay in formation2.According to the professor,what behavior plays an important role in the way ants obtain food?A.Ants usually take a different path when they return to their nest.B.Ants leave chemical trails when they are outside the nest.C.Small groups of ants search in different locations.D.Ants leave pieces of food along the path as markers.3.What are two principles of swarm intelligence based on the ant example?[Click on2answers.]A.Individuals are aware of the group goal.B.Individuals act on information in their local environment.C.Individuals follow a leader's guidance.D.Individuals instinctively follow a set of rules.4.According to the professor,what path is followed by both telephone calls on a network and ants seeking food?A.The path with the least amount of activityB.The most crowded pathC.The path that is most reinforcedD.The path that has intermediate stopping points5.Why does the professor mention movies?A.To identify movie scenes with computer-simulated flocks of birdsB.To identify a good source of information about swarm intelligenceC.To emphasize how difficult it still is to simulate bird flightD.To explain that some special effects in movies are based on swarm intelligence6.What is the professor's attitude about attempts to create computer-generated crowds of people?A.She believes that the rules of birds'flocking behavior do not apply to group behavior in humans.B.She thinks that crowd scenes could be improved by using the behavior of ant colonies as a model.C.She is surprised by how realistic the computer-generated crowds are.D.She is impressed that computer graphics can create such a wide range of emotions.答案C B BD C D A译文下面听一段生物学讲座的片段。
Ant Intelligence_vocabulary
雅思7.3.1 Ant IntelligenceAnt Intelligence1. When we think of intelligent members of the animal kingdom, the creatures that spring immediately to mind are apes and monkeys. But in fact the social lives of some members of the insect kingdom are sufficiently complex to suggest more than a hint of intelligence. Among these, the world of the ant has come in for considerable scrutiny lately, and the idea that ants demonstrate sparks of cognition has certainly not been rejected by those involved in these investigations.2. Ants store food, repel attackers and use chemical signals to contact one another in case of attack. Such chemical communication can be compared to the human use of visual and auditory channels (as in religious chants, advertising images and jingles, political slogans and martial music) to arouse and propagate moods and attitudes. The biologist Lewis Thomas wrote, Ants are so much like human beings as to be an embarrassment. They farm fungi, raise aphids* as livestock, launch armies to war, use chemical sprays to alarm and confuse enemies, capture slaves, engage in child labour, exchange information ceaselessly. They do everything but watch television.3. However, in ants there is no cultural transmission - everything must be encoded in the genes - whereas in humans the opposite is true. Only basic instincts are carried in the genes of a newborn baby, other skills being learned from others in the community as the child grows up. It may seem that this cultural continuity gives us a huge advantage over ants. They have never mastered fire nor progressed. Their fungus farming and aphid herding crafts are sophisticated when compared to the agricultural skills of humans five thousand years ago but have been totally overtaken by modern human agribusiness.4. Or have they? The farming methods of ants are at least sustainable. They do not ruin environments or use enormous amounts of energy. Moreover, recent evidence suggests that the crop farming of ants may be more sophisticated and adaptable than was thought.5. Ants were farmers fifty million years before humans were. Ants can't digest the cellulose in leaves - but some fungi can. The ants therefore cultivate these fungi in their nests, bringing them leaves to feed on, and then* aphids (small insects of a different species from ants) use them asa source of food. Farmer ants secrete antibiotics to control other fungi that might act as 'weeds', and spread waste to fertilise the crop.6. It was once thought that the fungus that ants cultivate wasa single type that they had propagated, essentially unchangedfrom the distant past. Not so. Ulrich Mueller of Maryland and his colleagues genetically screened 862 different types of fungi taken from ants' nests. These turned out to be highly diverse: it seems that ants are continually domesticating new species. Even more impressively, DNA analysis of the fungi suggests that the ants improve or modify the fungi by regularly swapping and sharing strains with neighbouring ant colonies.7. Whereas prehistoric man had no exposure to urban lifestyles - the forcing house of intelligence - the evidence suggests that ants have lived in urban settings for close on a hundred million years, developing and maintaining underground cities of specialised chambers and tunnels.8. When we survey Mexico City, Tokyo, Los Angeles, we are amazed at what has been accomplished by humans. Y et Hoelldoblerand Wilson's magnificent work for ant lovers, The Ants, describes a super colony of the ant Formica yessensis on the Ishikari Coast of Hokkaido. This 'megalopolis' was reported to be composed of 360 million workers and a million queens living in 4,500 interconnected nests across a territory of2.7 square kilometres.9. Such enduring and intricately meshed levels of technical achievement outstrip by far anything achieved by our distant ancestors. We hail as masterpieces the cave paintings in southern France and elsewhere, dating back some 20,000 years. Ant societies existed in something like their present form more than seventy million years ago. Beside this, prehistoric man looks technologically primitive. Is this then some kind of intelligence, albeit of a different kind10. Research conducted at Oxford, Sussex and Zurich Universities has shown that when desert ants return from a foraging trip, they navigate by integrating bearings and distances, which they continuously update in their heads. They combine the evidence of visual landmarks with a mental library of local directions, all within a framework which is consulted and updated. So ants can learn too.11. And in a twelve-year programme of work, Ryabko and Reznikova have found evidence that ants can transmit very complex messages. Scouts who had located food in amaze returned to mobilise theirforaging teams. They engaged in contact sessions, at the end of which the scout was removed in order to observe what her team might do. Often the foragers proceeded to the exact spot in the maze where the food had been. Elaborate precautions were taken to prevent the foraging teamusing odour clues. Discussion now centres on whether the route through the maze is communicated as a 'left right' sequence of turns or as a 'compass bearing and distance' message.12. During the course of this exhaustive study, Reznikova has grown so attached to her laboratory ants that she feels she knows them as individuals - even without the paint spots used to mark them. It's no surprise that Edward Wilson, in his essay, 'In the company of ants', advises readers who ask what to do with the ants in their kitchen to: 'Watch where you step. Be careful of little lives.'I.Text structure and text summary:This is an expository essaythat explains why ant is more intelligent in some waythan humans. The reasons are listed as: firstly, thefarming method of ants are sophisticated, adaptable andmore sustainable; secondly, ants are living as a complexsystem in underground cities long before humans do;thirdly, prehistoric man looks technologically primitive;fourthly, desert ants’ navig ation skill shows that ashumans, ants can learn too; fifthly, ants can transmitevery complex messages.II.Words and phrases: The language is formal and academic.III.Cultural Items/ Technological terms: ant, intelligence, humanlike behaviour, gene, farming method, urbanlifestyle, navigate, transmit messageIV.Overall difficulty level(in terms of vocabulary, sentence length, article length, topic familiarity): ★★★V.Reading Skills to be addressed:1Reading for specific information: What,where, who, when, why, how?√2Reading for main ideas, inferring, linking ideas and ellipsis (cohesion/ reference)√3 Evaluating the text (purpose, textorganization)4 Figurative languages5 Humor through exaggeration, throughironyQuestions 1-6Do the following statements agree with the information given in Reading Passage I?In boxes I 6 on your answer sheet, writeTRUE if the statement agrees with the informationFALSE if the statement contradicts the informationNOT GIVEN if there is no information on this1Ants use the same channels of communication as humans do.False2City life is one factor that encourages the development of intelligence. True3Ants can build large cities more quickly than humans do.Not Given4Some ants can find their way by making calculations based on distance and position. True5In one experiment, foraging teams were able to use their sense of smell to find food. False6The essay, 'In the company of ants', explores ant communication. Not GivenQuestions 7-13Complete the summary using the list of words, A-O, below.Write the correct letter, A-O, in boxes 7 -13 on your answer sheet.Ants as farmersAnts have sophisticated methods of farming, including herding livestock and growing crops, which are in many ways similar to those used in human agriculture. The ants cultivate a large number of different species of edible fungi which convert7 into a form which they can digest. They use their own natural 8 as weed-killers and also use unwanted materials as 9 . Genetic analysis shows they constantly upgrade these fungi by developing new species and by 10 species with neighbouring ant colonies. In fact, the farming methods of ants could be said to be more advanced than human agribusiness, since they use 11 methods, they do not affect the 12 and do not waste 13 .A aphidsB agriculturalC celluloseD exchangingE energyF fertilizersG foodH fungiI growing J interbreeding K natural L other species M secretions N sustainable O environment7 C 8 M 9 F 10 D 11 N 12 O 13 EVocabulary and Sentences Excercises:ⅠWhat do the underlined pronouns in the following sentences refer to?1)They do everything but watch television.(Paragraph 2)2)The ants therefore cultivate these fungi in their nests,bringing them leaves to feed on, and then* aphids (small insects of a different species from ants) use them as a source of food. (Paragraph 5)3)Research conducted at Oxford, Sussex and ZurichUniversities has shown that when desert ants return from a foraging trip, they navigate by integrating bearings and distances, which they continuously update in their heads.(Paragraph 10)4)During the course of this exhaustive study, Reznikova hasgrown so attached to her laboratory ants that she feels she knows them as individuals - even without the paint spots used to mark them. (Paragraph 12)5)It's no surprise that Edward Wilson, in his essay, 'In thecompany of ants', advises readers who ask what to do with the ants in their kitchen to: 'Watch where you step. Be careful of little lives.'(Paragraph 12)Answer: 1) ants 2) the ants’; these fungi; leaves3) desert ants 4) Reznikova; her laboratory ants; her laboratory ants5) Edward Wilson’s; readers’ⅡStudy technical terms (words in the category of biology): Use the dictionary to learn these words below.1)ape (Para.1)2)fungi(Para.2)3)aphids(Para.2)4)instinct(Para.3)5)gene(Para.3)6)cellulose(Para.5)7)secrete(Para.5)8)antibiotic(Para.5)9)species(Para.6)10)strain(Para.6)11)Formica yessensis (Para.8)Answer:1)ape (Para.1) any of various primates with short tails orno tail at all ,[脊椎] 猿2)fungi(Para.2)英['fʌŋɡiː]美['fʌŋgai] n. 真菌；菌类；（fungus的复数）3)aphids(Para.2) n. 蚜虫类（aphid的复数）4)instinct(Para.3)inborn pattern of behavior often responsiveto specific stimuli, n. 本能，直觉；天性5)gene(Para.3) n. (genetics) a segment of DNA that isinvolved in producing a polypeptide chain; it can include regions preceding and following the coding DNA as well as introns between the exons; it is considered a unit of heredity, n. [遗] 基因，遗传因子6)cellulose(Para.5)['seljʊləʊz; -s] n. 纤维素；（植物的）细胞膜质7)secrete(Para.5)[sɪ'kriːt] generate and separate fromcells or bodily fluids；[生]分泌8)antibiotic(Para.5) n. 抗生素，抗菌素; adj. 抗生的；抗菌的9)species(Para.6)['spiːʃiːz; -ʃɪz; 'spiːs-], n. [生物] 物种；种类; adj. 物种上的[ 复数species ]10)strain(Para.6) (植物、动物的)品系，系；品种；种类，类型11)Formica yessensis (Para.8)Formica yessensis Forel 石狩红蚁ⅢGuess the meaning of the underlined words according to the contexts.1)Ants store food, repel attackers and use chemical signals tocontact one another in case of attack.(Para. 2)2)However, in ants there is no cultural transmission -everything must be encoded in the genes - whereas in humans the opposite is true. (Para. 3)3)The farming methods of ants are at least sustainable. They donot ruin environments or use enormous amounts of energy.(Para. 4)4)It was once thought that the fungus that ants cultivate was asingle type that they had propagated, essentially unchanged from the distant past. Not so. Ulrich Mueller of Maryland and his colleagues genetically screened 862 different types of fungi taken from ants' nests. These turned out to be highly diverse: it seems that ants are continually domesticating new species. (Para. 6)5)Even more impressively, DNA analysis of the fungi suggeststhat the ants improve or modify the fungi by regularly swapping and sharing strains with neighbouring ant colonies.(Para. 6)Answer:1)repel: cause to move back by force or influence (cue: attackers)同义词：drive; repulse; force back; push back; beat back2) whereas: while, but (cue: the opposite)3) sustainable:adj. capable of being prolonged for keeping sth, (cue: They do not ruin environments or use enormous amounts of energy.)sustainable development 可持续发展sustainable growth 可持续增长4) diverse: many and different; (cue: a single type-- Not so-- diverse)Domesticate: adapt (a wild plant or unclaimed land) to the environment; (cue: the fungus that ants cultivate was a single type-- ants are continually domesticating new species)同义词：cultivate5) modify: cause to change; make different; cause a transformation; (cue: improve or --)同义词：change; alterSwap: exchange; (cue: -- and sharing)ⅣPlease combine the following short sentences into a long and complex sentence.1)Research was conducted at Oxford, Sussex and Zurich Universities.2) Research has shown something.3) Desert ants return from a foraging trip.4) When desert ants do so, they navigate by integrating bearings and distances.5) Desert ants continuously update integrating bearings and distances in their heads.Answer:Research conducted at Oxford, Sussex and Zurich Universities has shown that when desert ants return from a foraging trip, they navigate by integrating bearings and distances, which they continuously update in their heads.ⅤUnderstand some sentences.1)They do everything but watch television. (Para.2)Q: What kind of attitude of the author towards human beings can be implied here?A: Negative. Watching television a lot is believed to cause a person to be lazy in thinking and inactive. This rhetorical device is sarcasm.2)It was once thought that the fungus that ants cultivate was asingle type that they had propagated, essentially unchanged from the distant past. (Para.6)Q: Please study the grammatical functions of “it” and three “that”s.A:It: the subject in form, the real subject is “that the fungus that ants cultivate was a single type that they had propagated, essentially unchanged from the distant past”.The first that: 主语从句“that the fungus that ants cultivate was a single type that they had propagated, essentially unchanged from the distant past”引导词The second that: 定语从句that ants cultivate引导词，指代the fungusThe third that: 定语从句that they had propagated引导词，指代a single type3)We hail as masterpieces the cave paintings in southernFrance and elsewhere, dating back some 20,000 years.(Para.9)Q: Please rewrite the sentence in the ordinary sentence order. A: We hail the cave paintings in southern France and elsewhere, dating back some 20,000 years as masterpieces.4)Discussion now centres on whether the route through themaze is communicated as a 'left right' sequence of turns or asa 'compass bearing and distance' message. (Para.11)Q: Simplify the sentence and find its topic.A: Discussion centres on the route. This is also the topic of the whole sentence. “Whether the route through the maze is communicated as a 'left right' sequence of turns or as a 'compass bearing and distance' message” is the detailed information regarding “the route”.。
群体智能 Swarm Intelligence
群体智能Swarm Intelligence一、概况：群体智能的定义：众多简单个体组成的群体通过相互之间的简单合作来实现来实现某一功能, 完成某一任务。
下面是不同的表述：1.群体智能这个概念来自对自然界中昆虫群体的观察，群居性生物通过协作表现出的宏观智能行为特征被称为群体智能。
（百度百科）2. 群体智能源于对以蚂蚁、蜜蜂等为代表的社会性昆虫的群体行为的研究。
最早被用在细胞机器人系统的描述中。
它的控制是分布式的，不存在中心控制。
群体具有自组织性。
（维基百科）3. 群集智能(SwaⅡn Intelligence)指的是众多无智能的简单个体组成群体，通过相互间的简单合作表现出智能行为的特性。
（论文《群体智能优化算法的研究进展与展望》）群体智能的发展历史和基本概念：群体智能（swarm intelligence）源于对自然界中存在的群集行为。
如大雁在飞行时自动排成人字形, 蝙蝠在洞穴中快速飞行却可以互不碰撞等，这是人类在很早以前就发现的。
群体中的每个个体都遵守一定的行为准则, 当它们按照这些准则相互作用时就会表现出上述的复杂行为。
Craig Reynolds 在1986 年提出一个仿真生物群体行为的模型BOID。
（这是一个人工鸟系统, 其中每只人工鸟被称为一个BOID, 它有三种行为: 分离、列队及聚集, 并且能够感知周围一定范围内其它BOID 的飞行信息。
BOID 根据该信息, 结合其自身当前的飞行状态, 并在那三条简单行为规则的指导下做出下一步的飞行决策。
）尽管这一模型出现在1986 年, 但是群体智能( Sw arm Intellig ence) 概念被正式提出的时间并不长。
一个显著的标志是1999 年由E Bonabeau 和M Dorigo 等人编写的一本专著群体智能: 《从自然到人工系统》( “Sw armIntelligence: From Natural to Art ificial System”) 。
英语Animal Intelligence
Comprehension of Text A
• Findings: (work in groups) • 1) Let’s make a deal (para.3-6) • Research subject 1: • Colo, a female gorilla • Events:
• Colo VS Conservationist
• Ape:
• Apes are Old World anthropoid mammals, more specifically a clade of tailless catarrhine primates, belonging to the biological superfamily Hominoidea. The apes are native to Africa and Southeast Asia. Apes are the world's largest primates
• Conclusion: (para.13) • Animals do have intelligence, but to serve
their survival.
Text organization
• The text can be roughly divided into 3 parts:
• Part I: An introduction; • Part II: 3 subheadings to give 3 supporting
如何成为人工智能工程师英语作文
如何成为人工智能工程师英语作文全文共5篇示例，供读者参考篇1How to Become an AI EngineerHi everyone! My name is Timmy and I'm 10 years old. Today I'm going to tell you all about how to become an AI engineer when you grow up. AI stands for artificial intelligence. It's really cool technology that allows computers to think and learn kind of like humans! An AI engineer is someone who designs and builds these super smart AI systems.Becoming an AI engineer is not easy. It takes a lot of hard work and you have to learn lots of difficult subjects. But I think it's a really exciting job and worth all the effort if you're interested in computers and technology. Here are the key steps you need to take:Step 1: Get Really Good at Math and ScienceMath and science are the building blocks for all technology, including AI. You need to master subjects like algebra, calculus, statistics, computer science, and physics. These provide the foundation for understanding how AI algorithms work under thehood. I know math can be really boring with all the numbers and formulas. But just think of it as learning the language that computers use to communicate!Step 2: Learn to Code Like a ProCoding means writing the instructions that tell computers what to do. It's like speaking in the computer's language. AI engineers have to be expert coders. The most important coding languages for AI are Python, R, Java, and C++. You should start learning to code as early as possible, maybe even now if you're really eager! It's just like learning a new language except you're talking to machines instead of people.Step 3: Study AI, Machine Learning, and Deep LearningThese are the specific fields within computer science that deal with artificial intelligence. AI is all about creating intelligent machines that can perceive, learn, reason, and assist humans. Machine learning uses huge amounts of data to find patterns and allow the computer to learn on its own without being explicitly programmed. Deep learning is a powerful type of machine learning that can process images, audio, and other complex data.Step 4: Get an AI DegreeAfter high school, you'll need to go to college and get at least a bachelor's degree related to AI. Good majors are computer science, data science, robotics, or computer engineering. Many AI engineers also get a master's degree for even more specialized training. Make sure the program you choose has lots of courses specifically focused on artificial intelligence.Step 5: Get Experience Through Internships and ProjectsLike any technical field, hands-on experience is really important for becoming an AI pro. You should look for internships at AI companies during your college years. And work on lots of AI projects on your own to build up your skills. Things like creating a chatbot, building a computer vision system to recognize objects, or making a recommendation engine. The more AI systems you build, the better!Step 6: Consider Getting a Ph.D.While not absolutely required, many leading AI engineers have a doctoral degree. A Ph.D. allows you to become a total expert through years of advanced research and training. If you want to work on cutting-edge AI at big tech companies or top universities, a doctorate is usually needed.Step 7: Keep Learning and Staying Up-to-DateBecause AI is such a fast-moving field, you'll need to be a lifelong learner. New technologies, tools, and approaches are constantly emerging. You'll need to continuously read articles, take courses, and work on personal projects using the latest AI techniques. Maybe someday you'll even develop a revolutionary new AI that changes the world!So in summary, becoming an AI engineer requires a lot of work mastering math, science, coding, and machine learning. But if you're passionate about technology and willing to stick with it, you can have a very cool and rewarding career creating super intelligent computer systems. Just follow these steps and keep working hard!Who knows, maybe someday AI will be so advanced that machines will be able to learn and grow smarter on their own without any human engineers needed. But for now, there's still a huge demand for talented people to design and build these cutting-edge systems. With dedication and effort, that brilliant AI creator could be you! Let me know if you have any other questions.篇2How to Become an AI EngineerHi friends! Today I wanted to tell you all about how to become an AI engineer. That means someone who helps create super smart computers that can think and learn just like humans! Isn't that the coolest job ever? AI stands for "artificial intelligence" which is a type of technology that tries to mimic human intelligence and capabilities. AI engineers are the ones who design and build these really amazing AI systems and technologies.I first learned about AI when my older brother showed me some funny AI chatbots online that could have natural conversations just like a real person. I thought that was so neat! Then in school, we started learning about coding and programming robots which got me even more interested in AI and machine learning.AI is used in so many awesome ways - from video games and smart home assistants to self-driving cars and robots that can do human jobs! AI is really taking over the world, in a fun and helpful way of course. I can't wait until we have robot maids that clean our rooms for us!So how can you become an AI engineer when you grow up? Let me break it down for you:First, you'll need to be really good at math, science, and especially computer programming and coding. AI is all about teaching computers and machines to think using advanced mathematics, data, algorithms, and coding languages. The better you are at those subjects, the easier AI will be for you!In elementary school, make sure you pay close attention in math class and try to get as good as possible at algebra and statistics. Those will be super important for AI later on. You should also try coding clubs or camps to start learning programming fundamentals early. Coding is like giving instructions to computers using special languages they understand.In middle and high school, load up on advanced math and computer science courses. Take all the calculus, statistics, and programming classes you can. Many AI engineers also get electrical engineering or robotics skills in high school through extracurriculars. The more you can learn about hardware, sensors, and robotics, the better for AI.After high school, you'll want to get a bachelor's degree in a field like computer science, math, statistics, data science, or computer engineering. Don't forget to take plenty of AI and machine learning specialized courses too! Getting an internshipat a tech company doing AI work is also really valuable experience.For the very best AI jobs, you'll likely need a master's degree or even a PhD focusing specifically on artificial intelligence, machine learning, data science, or robotics. The more elite education you can get in those AI areas, the further you'll go in that career path.While you're getting your advanced degrees, make sure you learn all the latest AI skills like machine learning models, neural networks, natural language processing, computer vision, and reinforcement learning algorithms. You should strive to get really good at programming languages for AI like Python, R, Java and C++.It's also crucial that you keep up with all the latest research, tools and technologies in the rapidly evolving AI field. Things are changing so quickly as AI continues developing at an incredible pace. You'll need to keep educating yourself through online courses, books, podcasts, and conferences about AI. Staying on top of all the new AI innovations and trends is a must.In addition to technical skills, you'll want to develop other strengths like creativity, problem-solving, curiosity, communication, and collaboration. AI requires a lot ofinnovation, experimenting, and working with cross-disciplinary teams. You have to be able to take on open-ended challenges and come up with unique solutions. Strong skills in research, documentation, and explaining complex topics is important as well.Overall, the path to becoming an AI engineer involves years of intense studying math, programming, data, engineering and emerging technologies. It's not easy, but for a fun and rewarding career working on the cutting-edge of transformative AI systems, it's totally worth all the hard work!Let me know if you have any other questions! I'm happy to provide more details about what it takes to get into the awesome field of artificial intelligence engineering. Just keep working super hard at your math and coding skills and who knows, maybe one day you'll be programming the world's smartest AI systems! How cool would that be?篇3How to Become an AI EngineerHi friends! Have you ever heard of artificial intelligence or AI? It's really cool technology where computers can think and learnjust like humans! My big brother wants to be an AI engineer when he grows up. Let me tell you all about it.AI engineers are the ones who create the smart computer programs and robots that can see, hear, learn, and make decisions. They teach the computers how to recognize patterns and objects, understand human language, and even move around! Just imagine a robot that can walk, talk, and do chores for you. How awesome is that?But becoming an AI engineer is not easy. You need to study really hard in school, especially math, science, and computer coding. Those are the most important subjects for an AI engineer.In math, you'll learn about algebra, geometry, calculus, and statistics. These help you understand all the math and numbers behind AI algorithms. Statistics is super important because AI has to analyze lots of data to spot patterns.For science, you'll need to take physics and computer science classes. Physics teaches you about the real world that AI models. And computer science is where you'll learn programming languages like Python and C++. Those let you write the code to create AI software and apps.My brother says coding is like giving instructions to the computer, kind of like a recipe for baking cookies. Except with coding, you have to be very precise. Even one tiny mistake can mess everything up! That's why it takes lots of practice to get good at coding.Of course, you can't just learn it all from books. You also have to get hands-on experience building AI models and systems. That could mean joining a coding club, entering science fairs, or interning at a tech company over summer break.Once you get to college, you'll dive even deeper into AI concepts like machine learning, neural networks, computer vision, natural language processing and more. Those all sound crazy complicated, but don't worry, you'll learn it step-by-step. Just take it slowly and ask questions if you're confused.A lot of AI engineers also get a master's degree after college. That's two more years of graduate school to become a true AI expert. The classes are smaller and more advanced. You'll take part in research projects too. My brother hopes to study robot intelligence for his master's.See, becoming an AI engineer requires tons of hard work and perseverance. You have to be passionate about math,technology and solving problems. It's not easy, but for those who stick with it, the rewards are amazing!As an AI engineer, you could have a hand in creatingself-driving cars, virtual assistants like Alexa and Siri, facial recognition systems, translation apps, and so much more. AI is changing everything in our world, from healthcare and science to entertainment and education. How cool would it be to be part of that revolution?You'd also get paid really well as an AI engineer. The average salary is over 100,000 per year at major tech companies like Google, Microsoft and IBM. My brother says the job security is great too since AI will only keep growing and advancing in the future.But more than the money, what excites me most is how AI can improve people's lives and maybe even save the world someday. Just think - AI could help find cures for diseases, solve the climate crisis, explore other planets, and help the disabled in so many ways. An AI engineer's work could literally change the course of humanity!Of course, that's still a long way off. We need to make sure AI systems are ethical, unbiased, and their immense power is usedfor good. That's another crucial part of the job that AI engineers have to get right.Either way, I'm super proud of my big brother for dreaming so big. Whenever he tries to explain neural networks to me, I get dizzy just thinking about all that math and coding. It's definitely not for the faint of heart!But if you're a curious kid who loves technology and wants to take on an exciting challenge, then AI engineering could be the perfect career path. Just be ready to study really hard, never stop learning, and code like crazy!Who knows, maybe someday you could create the nextC-3PO or R2-D2 that helps humans explore galaxies far, far away. As an AI engineer, you'll be building the future before our very eyes. How cool is that?! Let me know if you have any other questions. May the force be with you!篇4How to Become an AI EngineerHi friends! Today I want to tell you all about how to become an AI engineer when you grow up. AI stands for "artificial intelligence" and it's really cool technology that allows computers to think and learn kind of like humans! An AI engineeris someone who helps create and develop AI systems and applications. It's a super exciting job that lets you build really neat things using advanced math, computer science, and technology.So how can you become an AI engineer? Well, the first step is to start learning about computers, math, and coding from an early age. That's because AI requires a strong foundation in these areas. You'll want to take classes in math topics like algebra, statistics, and calculus. And for coding, learn programming languages like Python, Java, and C++. The more you practice coding, the better you'll get!It's also really important to have an understanding of data science and machine learning techniques. Machine learning is a type of AI that allows computers to learn from data without being explicitly programmed. You'll need to know about things like neural networks, decision trees, and clustering algorithms. Don't worry if some of those words don't make sense yet - you'll learn all about them later!In addition to the technical skills, AI engineers need to be creative problem solvers who can think outside the box. AI systems have to tackle really complex challenges, so you'll need to come up with innovative solutions. It's like being a detectivetrying to crack a tough case, except with math and code instead of clues!Another key part of being an AI engineer is stayingup-to-date on the latest research and advancements in the field of AI. Technology is changing so quickly, with new breakthroughs happening all the time. You'll need to read papers from experts, attend conferences and workshops, and always be eager to learn new things. AI is a constantly evolving area, so you have to be willing to keep learning for your whole career.Once you get older, a great way to get experience is to join an AI club at school or do internships at tech companies over the summer. That hands-on practice will give you a chance to apply what you've learned and work on real AI projects. You can build your skills and get a better sense of what working as an AI engineer is actually like.So in summary, here are the key steps to become an AI engineer when you grow up:Study a lot of math, computer science, and coding from an early ageLearn data science and machine learning techniquesPractice creative problem solvingStay up-to-date on the latest AI research and newsGet hands-on experience through clubs, internships, and projectsIt takes a lot of hard work and dedication, but being an AI engineer is such a rewarding career. You'll be helping shape the future and pushing the boundaries of what technology can do. And who knows - maybe someday you'll create a super intelligent AI system that could even outthink humans! Wouldn't that be amazing?Well, that's all I have to share today. Let me know if you have any other questions! I'm happy I could tell you all about this awesome job. Who's ready to start coding?篇5How to Become an AI EngineerHi everyone! Today I want to tell you all about how to become an AI engineer. AI stands for artificial intelligence, which means really smart computers and robots that can think like humans. Isn't that so cool? AI engineers are the people who getto build these incredible machines. I think it's the coolest job ever!First off, you have to be really good at math and science subjects like algebra, calculus, statistics, and computer programming. AI uses tons of math and coding to work. The robots have to study data and numbers to learn how to think and make decisions. As an AI engineer, you need to teach them all that math so they can become super geniuses!You should start practicing math and coding as early as possible. Maybe your parents can find you a fun computer programming camp or class over the summer. Scratch is a cool kid-friendly coding program to start with. You can make fun games and animations just by dragging and dropping code blocks! The more you practice, the better you'll get.In school, pay extra close attention in math class. Don't just learn the stuff – ask lots of questions until you really, truly understand it all. That curiosity will serve you well as an AI engineer who has to figure out complex math problems every day. And do your coding homework without complaining! Becoming a master coder takes tons of practice.When you get to college, you'll need to study a subject like computer science, computer engineering, math, or statistics.These majors will teach you the advanced math, programming, and machine learning skills to build AI systems. It will be really hard work, but just keep thinking about that amazing AI robot you get to create at the end!As a computer science student, make sure to take all the courses on artificial intelligence, machine learning, data mining, natural language processing, robotics, and neural networks. Those are hugely important topics that will teach you how to make AI think more like humans.Maybe you can even join an AI research team on campus to get some hands-on experience. Or do an internship at a cool AI company like Google, Microsoft, Amazon, or OpenAI. Getting to build real AI alongside the experts would be so much fun!After college, you can either get a job at one of those big tech companies or maybe join a startup that is doing really exciting new things with AI. The field is moving so fast with new developments all the time, so there are always fresh opportunities. Self-driving cars, home robots, video game characters, smart assistants like Alexa and Siri – AI will be used for so many amazing things in the future!No matter where you work, an AI engineer spends their days writing tons of complex code to drive the AI algorithms. Youhave to frequently test your code on huge data sets to fix any bugs or errors. AI engineers also have to understand the latest AI research to integrate new techniques. It's an amazing blend of math, coding, curiosity, and creativity!Some days, you might be teaching an AI language model how to understand human conversations and respond in a natural way. Other days, you're helping train a computer vision system to recognize objects from images or videos. Or maybe you're working on an AI that can make strategic decisions for a video game opponent. So many possibilities!The most rewarding part is when you finally get that AI system running smoothly and it can impressively handle tasks that used to be only possible for humans. Seeing an AI robot successfully navigate rooms and identify objects, or an AI art program generating beautiful imagery from just text descriptions – it's so cool to create something that can learn and think like a person!Of course, being an AI engineer also comes with big responsibilities. You have to careful about data privacy and make sure the AI can't be used for harmful purposes like surveillance or weapons. AI bias is another big issue, where the data used to train the AI causes it to make unfair decisions about certaingroups. AI engineers have to thoroughly test for bias and find ways to make AI systems ethical and trustworthy.There's still so much we don't understand about human intelligence and cognition. So in a way, every AI engineer is like a pioneer exploring a new frontier! We are slowly unraveling the mysteries of thinking and intelligence by recreating them in machines. How amazing is that?Well, I hope I was able to explain why a job in AI engineering is just about the most awesome career ever. You get to build super genius robot buddies that can endlessly expand human knowledge and capabilities. If you work really hard and never give up on your passion for math, coding, and problem-solving, you too could become an AI wizard when you grow up! The future of AI needs more bright young minds like all of you. So study hard, keep practicing, and maybe I'll see you pioneering the next great AI breakthrough!。
雅思阅读词汇C7-T3-P1 Ant Intelligence
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姓名： 特殊的屋子和渠道 对……感到惊奇 完成 宏伟的 由……组成 相互关联的 领土 持久的 超过 到目前为止 跟…打招呼；向…喊 杰作 追溯 原始的 尽管 做一个研究 觅(食) 导航 整合 更新 结合 里程碑 框架 咨询 将复杂的消息 迷宫 动员 一场；一节；一段时间 继续做(或从事、进行) 复杂的；详尽的；精心制作的 采取预防措施 气味线索 讨论的中心在…… 序列 详尽的；彻底的；全面的 连接到 进行计算 探讨
随着科技的发展人工智能英语作文
随着科技的发展人工智能英语作文全文共3篇示例，供读者参考篇1The Awesome World of AI!Hi there! My name is Jamie and I'm 10 years old. Today I want to tell you all about artificial intelligence, or AI for short. AI is something that's becoming a really big part of our lives thanks to lots of cool new technologies. My teacher says AI is like giving human intelligence to computers and machines so they can think and learn kind of like how we do. Isn't that amazing?I first learned about AI a couple years ago when I got a smart speaker for my room. You've probably seen them - they're those little devices you can talk to and ask questions, and a friendly computer voice will respond. My smart speaker is named Alexa and she's powered by AI. Whenever I say "Alexa" followed by a question or command, she uses artificial intelligence to try to understand me and give me a helpful answer or carry out what I asked.At first, I just asked Alexa silly things like jokes or random facts. But then I realized she could actually be really useful forhomework help. If I'm stuck on a math problem, I can read it out loud and Alexa will use AI to solve it for me and explain the steps. When I have to write a report, I can ask about the topic and Alexa will use AI to research it online and summarize the key information for me. It's like having a personal tutor! I've gotten way better grades since I started using Alexa's AI capabilities to help me study.But AI can do a lot more than just homework assistance. My dad has a smart security camera at our house that uses artificial intelligence for facial recognition. If someone shows up at our door, the camera's AI can identify if it's someone in our family or an unexpected visitor. That makes me feel really safe. My mom uses AI too for her work - she's a nurse and the hospital she works at now has an AI system that can review test results and patient scans to look for anything abnormal more accurately than humans can on their own. AI is helping save lives!Some of the coolest AI though is used to power robots, drones, and self-driving cars. At the science museum downtown, they have an AI robot that can have conversations with visitors and even crack jokes! The robot uses natural language processing which is an AI capability that allows it to understand human speech as well as context andnuance, just like we dowhen we communicate. I saw some demos of AI drones that can sense their environment with cameras and sensors, and then use AI artificial intelligence to navigate autonomously. They can adapt their flight paths in real-time to avoid obstacles. Apparently the AI is so advanced that the drones can even be trained for different tasks like search and rescue or delivery!Self-driving cars with AI capabilities are already being tested on some roads. The AI driving system uses sensors andcameras to "see" the road, while the artificial intelligence software makes decisions about steering, acceleration and braking. It can process all the different road conditions and obstacles way faster than a human driver's brain could. I'm really excited for whenself-driving cars become the norm, because thanks to AI they will be so much safer than human drivers. No more accidents from distracted or impaired driving! My parents are a little nervous about the idea of a computer being in full control, but I think it's going to be great.Of course, with AI becoming so incorporated into our lives, there are some concerns too. A lot of people are worried about things like privacy If AI systems are always recording video and audio data to better understand their environments, is that an invasion of privacy? What if the data gets hacked or misused?There are also worries that as AI gets really advanced and can learn toautomatically do a lot of jobs currently done by humans, it could cause massive unemployment. My dad's friend is a truck driver and he's scared his job could someday be replaced by self-driving truck AI!Those are definitely things society will need to figure out rules and guidelines for as AI keeps evolving and becoming more powerful. But overall, I think artificial intelligence is so awesome and beneficial! It's helping make our lives easier and better in so many ways. AI tutors can customize teaching for each individual student based on their needs. AI doctors can diagnose health issues earlier for faster treatment. AI robots can take on dangerous jobs that could harm humans. Self-driving cars will reduce accidents and traffic from human error. And that's just the start - AI will likely only continue getting smarter and more capable.Just think, the AI we have now is already extremely impressive. But in 10 or 15 years when I'm an adult, who knows how mind-blowing it will be? AI assistants could be doing our chores and cooking for us. Maybe we'll have AI personal trainers that use individualizeddata to customize workout plans. Or AI video game coaches that study gameplay and give real-timeadvice to up your skills. There might even be AI politicians that calculate theabsolutely optimal policies based on voter input and data analysis rather than just doing what gets them re-elected. The possibilities are endless when you have artificial intelligence that can constantly adapt, learn and solve problems better than humans.I can't wait to see what the future holds for AI. In the meantime, I'm going to keep using it to my advantage for school, fun, and maybe even business one day if I'm an AI entrepreneur when I grow up. Thanks for reading, and make sure to get yourselves some smart AI gadgets and assistants. They're seriously game-changing!篇2The Incredible World of Artificial IntelligenceHi there! My name is Sammy, and I'm a 10-year-old kid who loves learning about science and technology. Today, I want to share with you something that has been blowing my mind recently – artificial intelligence, or AI for short.AI is basically the idea of creating machines that can think and learn like humans. It's like having a really smart computer that can do amazing things! I know it might sound a bit likescience fiction, but AI is already a part of our everyday lives, and it's only going to get more and more incredible as time goes on.One of the coolest things about AI is that it can learn and adapt on its own. For example, there are AI systems that can look at millions of pictures and learn to recognize different objects, animals, and even people's faces! Imagine having a robot that can not only see you but also know who you are and remember your name. How cool is that?Another amazing thing about AI is that it can process huge amounts of data and information way faster than any human could. This means that AI can help us solve really complex problems or make important decisions by analyzing all the available information in a matter of seconds. AI is already being used in fields like medicine, finance, and even space exploration to help humans make better choices and discoveries.But AI doesn't just have to be about serious stuff – it can also be a lot of fun! There are AI systems that can play games, tell jokes, and even create art and music. I recently saw a video of an AI that could draw pictures based on what a person described to it. The results were so creative and imaginative, it was like having an artist living inside the computer!Of course, with great power comes great responsibility, and there are some concerns about AI too. Some people worry that AI might become too smart and powerful, and start making decisions that could be harmful to humans. There are also concerns about privacy and security, since AI systems need a lot of data to learn and function properly.However, I think the benefits of AI outweigh the risks, as long as we're careful and responsible about how we develop and use it. AI has the potential to help us solve some of the biggest challenges facing our world, like climate change, disease, and hunger. It can also make our lives easier and more convenient in countless ways.Imagine having a personal assistant that can help you with your homework, remind you of your chores, and even keep you company when you're feeling lonely. Or think about how AI could help people with disabilities by providing them with specialized support and assistance. The possibilities are endless!One thing is for sure – AI is going to play a huge role in shaping our future. As a kid, I find it all incredibly exciting and fascinating. I can't wait to see what other amazing things AI will be able to do in the years to come.Who knows, maybe one day I'll even be able to have a conversation with an AI that's just as smart and friendly as a real person! For now, I'll just keep learning and exploring this incredible world of artificial intelligence, one discovery at a time.So, what do you think about AI? Are you as excited about it as I am? Let me know in the comments below!篇3The Awesome World of AIHi there! My name is Emma and I'm 10 years old. Today I want to tell you all about artificial intelligence or AI for short. AI is really cool and it's changing the world in so many amazing ways!What is AI? Well, it's when super smart computers can think and learn just like humans. Instead of just following a set of instructions, AI can look at information, figure stuff out, and make decisions on its own. Pretty neat, right?One type of AI is called machine learning. That's when computers can study data and get smarter over time without being programmed for every single thing. It's like the computer is learning from experience! Machine learning helps AI get really good at things like recognizing objects, understanding speech, and even playing games.Another important part of AI is something called neural networks. They are kind of inspired by how human brains work with neurons all connected together. In a neural network for AI, there are lots of nodes that process information and send it to other nodes, similar to how our brain cells communicate. This allows the AI to learn and make decisions in a way that sort of mimics human intelligence. Mind-blowing stuff!So where do we see AI being used today? One major way is with digital assistants like Siri, Alexa and Google Assistant. You can talk to them and ask questions just like you would another person. The AI tries to understand what you're saying and provide a helpful answer. Some digital assistants can even carry on conversations!AI is also taking the world of technology by storm. Your smartphone camera uses AI to automatically focus and adjust settings. AI filters out spam emails for you. And AI algorithms power most search engines and social media platforms to understand what you're looking for and show you relevant content.But AI isn't just in our phones and computers. It's being used in driverless cars, robots, drones, and so much more! The AI allows these machines to sense their surroundings, make smartdecisions, and even learn from their mistakes over time. Robots with AI are working in factories, exploring other planets, and assisting people in all sorts of ways.AI is even helping in really important areas like medicine and science. Doctors use AI to study medical images and data to catch illnesses faster. Scientists are using AI in chemistry and biology to discover new materials and drugs that could change the world. And some AI systems can play games like chess and go better than any human!Of course, with anything this powerful and rapidly growing, there are concerns as well. Some people worry that AI could get so advanced that it becomes a threat to humanity if not developed safely and responsibly. Others are worried that AI could take over many human jobs as it gets smarter than us at more and more tasks. There are also privacy issues around AI companies collecting huge amounts of data to train their systems.Despite the challenges though, I think the future of AI is incredibly exciting! Imagine AI tutors that could provide personalized learning for every student. Or AI companions that are always there for you as a friend. What about AI doctors that never get tired and can analyze your health better than anyperson? Or AI scientists helping us solve the biggest mysteries of the universe?AI is being used in creative ways as well. There are already AI systems that can generate art, music, stories and even movie scripts. An AI may have helped write the next blockbuster you go see! Although I have to admit, I like using my own creativity and imagination without a computer's help for now.As you can probably tell, I'm a huge fan of AI and all the possibilities it has. But I also understand it needs to be developed carefully so that it remains a tool that serves humanity's best interests. I'm hopeful that the brilliant minds of today and the future can figure out how to make AI awesome and beneficial, while avoiding the risks.Well, that's my take on this fascinating world of AI! I could keep going for hours, but I've probably already worn you out with my rambling. Just wait though - AI is only going to get more mind-blowing and world-changing with each passing year.We're。
高中英语高考复习必背科普文章词汇(共四大类)
高考英语必背科普文章词汇（一）1.Data 数据data base 数据库statistics 统计2.identity 身份identify vt 识别辨认mon 普遍的共同的shared 共享的4.market technology 市场技术/科技5.fingerprint（指纹）scan（扫描）6.private 私人的privacy 隐私e-space 电子空间7.Researcher研究者expert 专家specialist 专家experimenter 实验者e up with提出想起9.low-cost 提出10.device（装置）11.smart 只能的12.Keyboard 键盘13.precisely 确切地14.measure 测量15.Type 种类/打字pattern 类型款型16.pressure 压力17.Apply….To 把…应用于….18.analyze 分析19.force 力量强迫er用户21.press 按压pressure 压力22.unique 独特的23.determine 决定determination 决心determined 坚决的24.extension--extend 延长拓展25.give access to 给…渠道/机会26.be connected to 被链接到27.regardless of 尽管28.password密码29.Be familiar with 对…熟悉30.volunteer 志愿者实验参与者=subject=participant31.collect 收集collective 集合的共同的32.recognize 辨认认可33.be based on 基于34.error 错误rate 比率error rate 错误率35.straightforward直白的清晰明了的mercialize vt,使…商业化commercial商业的37.be made of 由…组成=consist of38.inexpensive 实惠的39.plastic 塑料的40.make it 成功41.in the near future 在不久的未来（二）1.Accuracy准确性accurate adj,准确的2.replace 代替replacement n 替代品substitution3.system 系统4.cut the cost of剪掉成本5.Invention 发明=invent6.make ….possible 使…成为可能7.operate 运作操作-operationcooperate 共同运作合作-cooperation8.develop研发患病9.Vary（变化） from person to person.因人而异10.Data security数据安全性11.Guarantee 保证12.expect 期待13.environment-friendly 环境友好型14.consumer 消费者15.speed up 加速16.diary 日记17.Guidebook 指导书18.novel 小说19.Science report 科学报告20.science journal 科学杂志21.Fiction 科幻虚构non-fiction 现实22.consider 考虑considerable 大量的considerably 相当地considerate, 体贴的,考虑周全的23.luxury 奢侈品/ luxurious 奢侈品24.Essential 必要的25.wellbeing 健康幸福26.Insufficient 不足够的27.increase risk of ……增加…的风险28.severe 严重的29.medical condition 医疗条件30.obesity 肥胖high blood sugar levels 高血糖水平31.heart disease 心脏病32.improve academic performance 提高学术表现实验过程32.the relationship between A and BA…B之间的关系 = connection between A and Bstraight-line relationship between A and B A….B 成线性关系33.hand out 分发出去34.smart watch 智能手表35.track 追踪36.physical activity 生理活动psychological activity 心理活动37.academic achievement 学术成就38.While 虽然…39.factor 要素40.average平均的平庸的平均值41.amount 数量 amount to 相当于42.result 结果result in 导致result from 来源于43.course 课程44.quiz 测试midterm test中期测试the final exam期末测试45.Matter 物质vi,重要46.perform poorly表现糟糕/性能差47.outperform ,表现得更好outnumber 更多数量48.higher-performing student ,表现很好的学术49.Quantity 数量50.Perhaps 也许51.Impact 影响(sy :effect, influence) have …impact on对..产生影响pattern模式类型52.grade 级别分数53.overall 总体54.Similarly 相似地55.Regular 常规的56.extra额外的57.original 最初的58.Objective客观的---object vt 反对59.Accidental 意外的plete完成61.Convincing adj 有说服力的 convince vt 说服…62.Doubtful 怀疑的63.Chemistry 化学64.Volunteer 志愿者(sy: participant, subject) 65.Professor 教授66athlete 运动员67.normal test 常规测试68.Academically 学术（三）1.seek connections with sth .寻求….的关系2.emotional情感的3.Experience 体验经历经验4.Not all travel experiences, however, need to take place in the real world.不是所有的旅游体验都需要在真实的世界发生5.With the evolution of technology 随着科技的发展6.virtual reality (VR)7.increasingly 越来越….8.physical and virtual world 实体和虚拟世界9.even 甚至10.remove去除11.Need n,需求（sy, demand） meet the need for…满足…的需求12.entirely adv, 完全地13.equal平等的equal to…相当于14.expert 专家(sy, specialist )15.Inbuilt 内置的16.mechanism 机制17.Current 当前的 currency 货币18.process n, 过程in the process of 在…过程vt处理加工procession,n19.be engaged in 从事忙于某事20.mind wandering心理游走21.mental images心理表象22.Pathway通道,方法渠道23.receive 接受receiver 接收者reception 前台24.input 输入output 输出25.react to 反应26.critic 评论家27.Argue 坚持认为28.match 匹配搭配 n,比赛29.make a positive contribution 做出积极的贡献/促进30.historical event 历史事件31.ancient city 古城 32.Dinosaur 恐龙33.suffer from 遭受34.stress and depression 压力和抑郁35.due to 由于36.overwork 加班37.convenient 便利38.brief 简洁的39.otherwise 否则另外持此以外40.destination 目的地42.battery 电池41.recharge 重新充电charge 充电收费控诉free of charge 免费42.science fiction 科幻43.Demand 要求需求44.shared experience共享的体验45.physical world.实际的世界（四）1.Honeybee 蜜蜂ant 蚂蚁social社会的insect昆虫live in group 群居2.colony 殖民地栖息地.3.survive幸存4.by means of 用…方式/手段5.collective 集体的共同的6.Intelligence 智商智慧intelligent 聪明的高智商的7.decision-making power 决定权8.distribute 分布9.throughout贯穿10.Instead 相反11.have a lot in common 有很多共同点12.in terms of …..在…方面13.social behavior 社会行为14.Specifically 尤其（sy especially, particularly）munication 沟通通讯16.capacity for learning 学习能力17.Pheromone 荷尔蒙18.source 源头来源19.promising 充满前景的很有潜力的promise 承诺20.rest adj 剩下的 n,休息21.a trail of一系列23.pick up 随机学到的捡起接受到24.speed and movement 速度和运动25.indicate暗示表明（sy:suggest）26.concept 概念27.accomplish 完成28.certain 某个29.foraging skill 觅食技巧30.accompany 陪伴31.route 路线32.avoid 避免33.obstacle 阻碍物困难34.coordinate 协作35.crucial 关键的36.Cooperate 合作 cooperationoperate 操作37.consist of 由…组成（be made up of ）38.Individual n, 个体adj,个体的39.Unintelligent 不聪明的40.amazing 令人惊讶的41.brilliance 智慧光明42.leadership 领导力43.distance 距离44.direction方向45.potential 潜在的46.demonstrate 表明展现(sy,show, exhibit)46.statistic 统计 data 数据47.reference 参考引用(sy: quote)48.present study finding 呈现研究发现49.benefit vt 使…受益..n,好处50.collective intelligence 集体智慧51.reproduce 繁殖52.rapidly 快速地53.work cooperation工作的协作54.reduce 降低55.division 分别divide 分开bour 劳动力。
人工智能英汉
人工智能英汉Aβα-Pruning, βα-剪枝, (2) Acceleration Coefficient, 加速系数, (8) Activation Function, 激活函数, (4) Adaptive Linear Neuron, 自适应线性神经元,(4)Adenine, 腺嘌呤, (11)Agent, 智能体, (6)Agent Communication Language, 智能体通信语言, (11)Agent-Oriented Programming, 面向智能体的程序设计, (6)Agglomerative Hierarchical Clustering, 凝聚层次聚类, (5)Analogism, 类比推理, (5)And/Or Graph, 与或图, (2)Ant Colony Optimization (ACO), 蚁群优化算法, (8)Ant Colony System (ACS), 蚁群系统, (8) Ant-Cycle Model, 蚁周模型, (8)Ant-Density Model, 蚁密模型, (8)Ant-Quantity Model, 蚁量模型, (8)Ant Systems, 蚂蚁系统, (8)Applied Artificial Intelligence, 应用人工智能, (1)Approximate Nondeterministic Tree Search (ANTS), 近似非确定树搜索, (8) Artificial Ant, 人工蚂蚁, (8)Artificial Intelligence (AI), 人工智能, (1) Artificial Neural Network (ANN), 人工神经网络, (1), (3)Artificial Neural System, 人工神经系统，(3) Artificial Neuron, 人工神经元, (3) Associative Memory, 联想记忆, (4) Asynchronous Mode, 异步模式, (4) Attractor, 吸引子, (4)Automatic Theorem Proving, 自动定理证明,(1)Automatic Programming, 自动程序设计, (1) Average Reward, 平均收益, (6) Axon, 轴突, (4)Axon Hillock, 轴突丘, (4)BBackward Chain Reasoning, 逆向推理, (3) Bayesian Belief Network, 贝叶斯信念网, (5) Bayesian Decision, 贝叶斯决策, (3) Bayesian Learning, 贝叶斯学习, (5) Bayesian Network贝叶斯网, (5)Bayesian Rule, 贝叶斯规则, (3)Bayesian Statistics, 贝叶斯统计学, (3) Biconditional, 双条件, (3)Bi-Directional Reasoning, 双向推理, (3) Biological Neuron, 生物神经元, (4) Biological Neural System, 生物神经系统, (4) Blackboard System, 黑板系统, (8)Blind Search, 盲目搜索, (2)Boltzmann Machine, 波尔兹曼机, (3) Boltzmann-Gibbs Distribution, 波尔兹曼-吉布斯分布, (3)Bottom-Up, 自下而上, (4)Building Block Hypotheses, 构造块假说, (7) CCell Body, 细胞体, (3)Cell Membrane, 细胞膜, (3)Cell Nucleus, 细胞核, (3)Certainty Factor, 可信度, (3)Child Machine, 婴儿机器, (1)Chinese Room, 中文屋, (1) Chromosome, 染色体, (6)Class-conditional Probability, 类条件概率,(3), (5)Classifier System, 分类系统, (6)Clause, 子句, (3)Cluster, 簇, (5)Clustering Analysis, 聚类分析, (5) Cognitive Science, 认知科学, (1) Combination Function, 整合函数, (4) Combinatorial Optimization, 组合优化, (2) Competitive Learning, 竞争学习, (4) Complementary Base, 互补碱基, (11) Computer Games, 计算机博弈, (1) Computer Vision, 计算机视觉, (1)Conflict Resolution, 冲突消解, (3) Conjunction, 合取, (3)Conjunctive Normal Form (CNF), 合取范式,(3)Collapse, 坍缩, (11)Connectionism, 连接主义, (3) Connective, 连接词, (3)Content Addressable Memory, 联想记忆, (4) Control Policy, 控制策略, (6)Crossover, 交叉, (7)Cytosine, 胞嘧啶, (11)DData Mining, 数据挖掘, (1)Decision Tree, 决策树, (5) Decoherence, 消相干, (11)Deduction, 演绎, (3)Default Reasoning, 默认推理（缺省推理）,(3)Defining Length, 定义长度, (7)Rule (Delta Rule), 德尔塔规则, 18(3) Deliberative Agent, 慎思型智能体, (6) Dempster-Shafer Theory, 证据理论, (3) Dendrites, 树突, (4)Deoxyribonucleic Acid (DNA), 脱氧核糖核酸, (6), (11)Disjunction, 析取, (3)Distributed Artificial Intelligence (DAI), 分布式人工智能, (1)Distributed Expert Systems, 分布式专家系统,(9)Divisive Hierarchical Clustering, 分裂层次聚类, (5)DNA Computer, DNA计算机, (11)DNA Computing, DNA计算, (11) Discounted Cumulative Reward, 累计折扣收益, (6)Domain Expert, 领域专家, (10) Dominance Operation, 显性操作, (7) Double Helix, 双螺旋结构, (11)Dynamical Network, 动态网络, (3)E8-Puzzle Problem, 八数码问题, (2) Eletro-Optical Hybrid Computer, 光电混合机, (11)Elitist strategy for ant systems (EAS), 精化蚂蚁系统, (8)Energy Function, 能量函数, (3) Entailment, 永真蕴含, (3) Entanglement, 纠缠, (11)Entropy, 熵, (5)Equivalence, 等价式, (3)Error Back-Propagation, 误差反向传播, (4) Evaluation Function, 评估函数, (6) Evidence Theory, 证据理论, (3) Evolution, 进化, (7)Evolution Strategies (ES), 进化策略, (7) Evolutionary Algorithms (EA), 进化算法, (7) Evolutionary Computation (EC), 进化计算,(7)Evolutionary Programming (EP), 进化规划,(7)Existential Quantification, 存在量词, (3) Expert System, 专家系统, (1)Expert System Shell, 专家系统外壳, (9) Explanation-Based Learning, 解释学习, (5) Explanation Facility, 解释机构, (9)FFactoring, 因子分解, (11)Feedback Network, 反馈型网络, (4) Feedforward Network, 前馈型网络, (1) Feasible Solution, 可行解, (2)Finite Horizon Reward, 横向有限收益, (6) First-order Logic, 一阶谓词逻辑, (3) Fitness, 适应度, (7)Forward Chain Reasoning, 正向推理, (3) Frame Problem, 框架问题, (1)Framework Theory, 框架理论, (3)Free-Space Optical Interconnect, 自由空间光互连, (11)Fuzziness, 模糊性, (3)Fuzzy Logic, 模糊逻辑, (3)Fuzzy Reasoning, 模糊推理, (3)Fuzzy Relation, 模糊关系, (3)Fuzzy Set, 模糊集, (3)GGame Theory, 博弈论, (8)Gene, 基因, (7)Generation, 代, (6)Genetic Algorithms, 遗传算法, (7)Genetic Programming, 遗传规划（遗传编程）,(7)Global Search, 全局搜索, (2)Gradient Descent, 梯度下降, (4)Graph Search, 图搜索, (2)Group Rationality, 群体理性, (8) Guanine, 鸟嘌呤, (11)HHanoi Problem, 梵塔问题, (2)Hebbrian Learning, 赫伯学习, (4)Heuristic Information, 启发式信息, (2) Heuristic Search, 启发式搜索, (2)Hidden Layer, 隐含层, (4)Hierarchical Clustering, 层次聚类, (5) Holographic Memory, 全息存储, (11) Hopfield Network, 霍普菲尔德网络, (4) Hybrid Agent, 混合型智能体, (6)Hype-Cube Framework, 超立方体框架, (8)IImplication, 蕴含, (3)Implicit Parallelism, 隐并行性, (7) Individual, 个体, (6)Individual Rationality, 个体理性, (8) Induction, 归纳, (3)Inductive Learning, 归纳学习, (5) Inference Engine, 推理机, (9)Information Gain, 信息增益, (3)Input Layer, 输入层, (4)Interpolation, 插值, (4)Intelligence, 智能, (1)Intelligent Control, 智能控制, (1) Intelligent Decision Supporting System (IDSS), 智能决策支持系统，(1) Inversion Operation, 倒位操作, (7)JJoint Probability Distribution, 联合概率分布,(5) KK-means, K-均值, (5)K-medoids, K-中心点, (3)Knowledge, 知识, (3)Knowledge Acquisition, 知识获取, (9) Knowledge Base, 知识库, (9)Knowledge Discovery, 知识发现, (1) Knowledge Engineering, 知识工程, (1) Knowledge Engineer, 知识工程师, (9) Knowledge Engineering Language, 知识工程语言, (9)Knowledge Interchange Format (KIF), 知识交换格式, (8)Knowledge Query and ManipulationLanguage (KQML), 知识查询与操纵语言，(8)Knowledge Representation, 知识表示, (3)LLearning, 学习, (3)Learning by Analog, 类比学习, (5) Learning Factor, 学习因子, (8)Learning from Instruction, 指导式学习, (5) Learning Rate, 学习率, (6)Least Mean Squared (LSM), 最小均方误差,(4)Linear Function, 线性函数, (3)List Processing Language (LISP), 表处理语言, (10)Literal, 文字, (3)Local Search, 局部搜索, (2)Logic, 逻辑, (3)Lyapunov Theorem, 李亚普罗夫定理, (4) Lyapunov Function, 李亚普罗夫函数, (4)MMachine Learning, 机器学习, (1), (5) Markov Decision Process (MDP), 马尔科夫决策过程, (6)Markov Chain Model, 马尔科夫链模型, (7) Maximum A Posteriori (MAP), 极大后验概率估计, (5)Maxmin Search, 极大极小搜索, (2)MAX-MIN Ant Systems (MMAS), 最大最小蚂蚁系统, (8)Membership, 隶属度, (3)Membership Function, 隶属函数, (3) Metaheuristic Search, 元启发式搜索, (2) Metagame Theory, 元博弈理论, (8) Mexican Hat Function, 墨西哥草帽函数, (4) Migration Operation, 迁移操作, (7) Minimum Description Length (MDL), 最小描述长度, (5)Minimum Squared Error (MSE), 最小二乘法,(4)Mobile Agent, 移动智能体, (6)Model-based Methods, 基于模型的方法, (6) Model-free Methods, 模型无关方法, (6) Modern Heuristic Search, 现代启发式搜索,(2)Monotonic Reasoning, 单调推理, (3)Most General Unification (MGU), 最一般合一, (3)Multi-Agent Systems, 多智能体系统, (8) Multi-Layer Perceptron, 多层感知器, (4) Mutation, 突变, (6)Myelin Sheath, 髓鞘, (4)(μ+1)-ES, (μ+1) -进化规划, (7)(μ+λ)-ES, (μ+λ) -进化规划, (7) (μ,λ)-ES, (μ,λ) -进化规划, (7)NNaïve Bayesian Classifiers, 朴素贝叶斯分类器, (5)Natural Deduction, 自然演绎推理, (3) Natural Language Processing, 自然语言处理,(1)Negation, 否定, (3)Network Architecture, 网络结构, (6)Neural Cell, 神经细胞, (4)Neural Optimization, 神经优化, (4) Neuron, 神经元, (4)Neuron Computing, 神经计算, (4)Neuron Computation, 神经计算, (4)Neuron Computer, 神经计算机, (4) Niche Operation, 生态操作, (7) Nitrogenous base, 碱基, (11)Non-Linear Dynamical System, 非线性动力系统, (4)Non-Monotonic Reasoning, 非单调推理, (3) Nouvelle Artificial Intelligence, 行为智能,(6)OOccam’s Razor, 奥坎姆剃刀, (5)(1+1)-ES, (1+1) -进化规划, (7)Optical Computation, 光计算, (11)Optical Computing, 光计算, (11)Optical Computer, 光计算机, (11)Optical Fiber, 光纤, (11)Optical Waveguide, 光波导, (11)Optical Interconnect, 光互连, (11) Optimization, 优化, (2)Optimal Solution, 最优解, (2)Orthogonal Sum, 正交和, (3)Output Layer, 输出层, (4)Outer Product, 外积法, 23(4)PPanmictic Recombination, 混杂重组, (7) Particle, 粒子, (8)Particle Swarm, 粒子群, (8)Particle Swarm Optimization (PSO), 粒子群优化算法, (8)Partition Clustering, 划分聚类, (5) Partitioning Around Medoids, K-中心点, (3) Pattern Recognition, 模式识别, (1) Perceptron, 感知器, (4)Pheromone, 信息素, (8)Physical Symbol System Hypothesis, 物理符号系统假设, (1)Plausibility Function, 不可驳斥函数（似然函数）, (3)Population, 物种群体, (6)Posterior Probability, 后验概率, (3)Priori Probability, 先验概率, (3), (5) Probability, 随机性, (3)Probabilistic Reasoning, 概率推理, (3) Probability Assignment Function, 概率分配函数, (3)Problem Solving, 问题求解, (2)Problem Reduction, 问题归约, (2)Problem Decomposition, 问题分解, (2) Problem Transformation, 问题变换, (2) Product Rule, 产生式规则, (3)Product System, 产生式系统, (3) Programming in Logic (PROLOG), 逻辑编程, (10)Proposition, 命题, (3)Propositional Logic, 命题逻辑, (3)Pure Optical Computer, 全光计算机, (11)QQ-Function, Q-函数, (6)Q-learning, Q-学习, (6)Quantifier, 量词, (3)Quantum Circuit, 量子电路, (11)Quantum Fourier Transform, 量子傅立叶变换, (11)Quantum Gate, 量子门, (11)Quantum Mechanics, 量子力学, (11) Quantum Parallelism, 量子并行性, (11) Qubit, 量子比特, (11)RRadial Basis Function (RBF), 径向基函数,(4)Rank based ant systems (ASrank), 基于排列的蚂蚁系统, (8)Reactive Agent, 反应型智能体, (6) Recombination, 重组, (6)Recurrent Network, 循环网络, (3) Reinforcement Learning, 强化学习, (3) Resolution, 归结, (3)Resolution Proof, 归结反演, (3) Resolution Strategy, 归结策略, (3) Reasoning, 推理, (3)Reward Function, 奖励函数, (6) Robotics, 机器人学, (1)Rote Learning, 机械式学习, (5)SSchema Theorem, 模板定理, (6) Search, 搜索, (2)Selection, 选择, (7)Self-organizing Maps, 自组织特征映射, (4) Semantic Network, 语义网络, (3)Sexual Differentiation, 性别区分, (7) Shor’s algorithm, 绍尔算法, (11)Sigmoid Function, Sigmoid 函数（S型函数）,(4)Signal Function, 信号函数, (3)Situated Artificial Intelligence, 现场式人工智能, (1)Spatial Light Modulator (SLM), 空间光调制器, (11)Speech Act Theory, 言语行为理论, (8) Stable State, 稳定状态, (4)Stability Analysis, 稳定性分析, (4)State Space, 状态空间, (2)State Transfer Function, 状态转移函数,(6)Substitution, 置换, (3)Stochastic Learning, 随机型学习, (4) Strong Artificial Intelligence (AI), 强人工智能, (1)Subsumption Architecture, 包容结构, (6) Superposition, 叠加, (11)Supervised Learning, 监督学习, (4), (5) Swarm Intelligence, 群智能, (8)Symbolic Artificial Intelligence (AI), 符号式人工智能（符号主义）, (3) Synapse, 突触, (4)Synaptic Terminals, 突触末梢, (4) Synchronous Mode, 同步模式, (4)TThreshold, 阈值, (4)Threshold Function, 阈值函数, (4) Thymine, 胸腺嘧啶, (11)Topological Structure, 拓扑结构, (4)Top-Down, 自上而下, (4)Transfer Function, 转移函数, (4)Travel Salesman Problem, 旅行商问题, (4) Turing Test, 图灵测试, (1)UUncertain Reasoning, 不确定性推理, (3)Uncertainty, 不确定性, (3)Unification, 合一, (3)Universal Quantification, 全称量词, (4) Unsupervised Learning, 非监督学习, (4), (5)WWeak Artificial Intelligence (Weak AI), 弱人工智能, (1)Weight, 权值, (4)Widrow-Hoff Rule, 维德诺-霍夫规则, (4)。
(完整版)人工智能介绍PPT课件
智能模拟
机器视、听、触、感觉及思维方式的模拟：指纹识别，人脸识别，视网膜识别， 虹膜识别，掌纹识别，专家系统，智能搜索，定理证明，逻辑推理，博弈，信 息感应与辨证处理。
谢谢
主条目：GOFAI
基于逻辑不像艾伦 纽厄尔和赫伯特 西蒙，JOHN MCCARTHY认为机器不需要模拟 人类的思想，而应尝试找到抽象推理和解决问题的本质，不管人们是否使用同样的 算法。他在斯坦福大学的实验室致力于使用形式化逻辑解决多种问题，包括知识表 示，智能规划和机器学习。致力于逻辑方法的还有爱丁堡大学，而促成欧洲的其他 地方开发编程语言PROLOG和逻辑编程科学。“反逻辑”斯坦福大学的研究者 (如 马文 闵斯基和西摩尔 派普特)发现要解决计算机视觉和自然语言处理的困难问题， 需要专门的方案-他们主张不存在简单和通用原理（如逻辑）能够达到所有的智能行 为。ROGER SCHANK 描述他们的“反逻辑”方法为 "SCRUFFY" 。常识知识库 (如DOUG LENAT的CYC)就是"SCRUFFY"AI的例子，因为他们必须人工一次编写一 个复杂的概念。
大脑模拟
主条目：控制论和计算神经科学 20世纪40年代到50年代，许多研究者探索神经病学，信息理论及控 制论之间的联系。其中还造出一些使用电子网络构造的初步智能， 如W. GREY WALTER的TURTLES和JOHNS HOPKINS BEAST。这 些研究者还经常在普林斯顿大学和英国的RATIO CLUB举行技术协 会会议。直到1960，大部分人已经放弃这个方法，尽管在80年代再 次提出这些原理。 符号处理
集成方法
智能AGENT范式智能AGENT是一个会感知环境并作出行动以达致目标的系统。最简单的智能AGENT是 那些可以解决特定问题的程序。更复杂的AGENT包括人类和人类组织（如公司）。这些范式可以让研究 者研究单独的问题和找出有用且可验证的方案，而不需考虑单一的方法。一个解决特定问题的AGENT可 以使用任何可行的方法-一些AGENT用符号方法和逻辑方法，一些则是子符号神经网络或其他新的方法。 范式同时也给研究者提供一个与其他领域沟通的共同语言--如决策论和经济学（也使用ABSTRACT AGENTS的概念）。90年代智能AGENT范式被广泛接受。AGENT体系结构和认知体系结构研究者设计出 一些系统来处理多ANGENT系统中智能AGENT之间的相互作用。一个系统中包含符号和子符号部分的系 统称为混合智能系统，而对这种系统的研究则是人工智能系统集成。分级控制系统则给反应级别的子符号 AI和最高级别的传统符号AI提供桥梁，同时放宽了规划和世界建模的时间。RODNEY BROOKS的 SUBSUMPTION ARCHITECTURE就是一个早期的分级系统计划。
英语世界上最大的蚂蚁脑筋急转弯
英语世界上最大的蚂蚁脑筋急转弯The world's largest ant brain teasersAnts may be small in size, but their collective intelligence is truly remarkable. In the world of English brain teasers, the mention of ants often brings to mind some of the most challenging and thought-provoking puzzles. These brain teasers are not only fun to solve, but they also provide great insight into the fascinating world of these tiny creatures. Let's take a look at some of the most interesting and challenging ant-themed brain teasers.1. The ant and the sugar cubeOne of the most classic ant-themed brain teasers involves an ant and a sugar cube. The puzzle goes like this: an ant finds a sugar cube in a room, and it wants to take the sugar cube out of the room to its anthill. However, the ant can only carry the sugar cube halfway before it gets tired. How can the ant manage to take the sugar cube to its anthill?2. The ant colony's escapeIn this brain teaser, you are tasked with helping an entire ant colony make its way out of a dangerous situation. The ant colony is trapped in a room that is slowly filling up with water. The onlyway out is through a small hole in the wall. How can you help the entire ant colony escape before the room fills up with water?3. The ant's journeyIn this brain teaser, an ant is placed at the center of a circular table. The ant wants to walk to the edge of the table, but it is only allowed to walk along the table's edge. How can the ant make its way to the edge of the table?4. The ant's dilemmaIn this brain teaser, an ant finds itself trapped in a maze. The ant needs to find its way out of the maze in the shortest amount of time possible. Can you help the ant navigate through the maze and find its way out?5. The ant's mathematical challengeThis brain teaser involves a group of ants that are tasked with counting the number of ants in their colony. The ants decide to count themselves one by one. The first ant says "1", the second ant says "2", and so on. However, when the 100th ant speaks, it says the wrong number. Can you figure out which ant made the mistake and why?6. The ant's food storageIn this brain teaser, an ant is tasked with storing food in its anthill for the winter. The ant can only carry one piece of food at a time, and it needs to store a total of 10 pieces of food. However, if the ant's load is ever heavier than the sum of the weights of the food it has already stored, the ant will be unable to carry the food back to the anthill. Can you help the ant figure out a way to store all 10 pieces of food without running into this problem?These are just a few examples of the many interesting and challenging brain teasers that involve ants. Solving these brain teasers not only provides great enjoyment and mental stimulation, but it also offers a unique perspective on the intelligence and problem-solving abilities of these fascinating insects. Next time you come across an ant-themed brain teaser, remember that these tiny creatures are capable of surprising us with their cleverness and resourcefulness.。
小学生常见英文缩写
常用英文缩写(英语星期月份等)作者:xxhai星期星期一：Mon.=Monday星期二：Tues.=Tuesday星期三：Wed.=Wednesday星期四：Thur.=Thurday星期五： Fri.=Friday星期六：Sat.=Saturday星期天：Sun.=Sunday月份一月份＝JAN. Jan.=January二月份＝FEB. Feb.=February三月份＝MAR. Mar.=March四月份＝APR. Apr.=April五月份＝MAY May=May六月份＝JUN. Jun.=June七月份＝JUL. Jul.=July八月份＝AUG. Aug.=August九月份＝SEP. Sept.=September十月份＝OCT. Oct.=October十一月份＝NOV. Nov.=November十二月份＝DEC. Dec.=December注意：“.”不能省略这里给大家个例子，比如今天2007年3月20日Mar.20，2007写日期时，可以用基数词（避免出现不必要的失误）1，2，3，4，5，。
28，29，30，31等。
怎样用英语表达年、月、日一、年份在英语中,年份一般用阿拉伯数字写出,其读。
写方法有以下几种:1、四位数的年份,一般前两个数为一个单位,后两个数为一个单位,依次按基数词读出。
如:1763年写作:1763读作:seventeen sixty-three或seventeen hundred and sixty-three2006年写作:2006。
读作:two thousand and six2063年写作:2063。
读作:twenty sixtythree或twenty hundred andsixty-three1050年写作:1050。
读作:ten fifty或ten hundred and fifty2、三位数的年份,可以按基数词读出,或者第一个数字为一个单位,后两个数字为一个单位,按基数词读出。
IELTS雅思阅读真题
蚂蚁智力Collective intelligence:：Ants and brain's neuronsSTANFORD - An individual ant is not very bright, but ants in a colony, operating as a collective, do remarkable things.A single neuron in the human brain can respond only to what the neurons connected to it are doing, but all of them together can be Immanuel Kant.That resemblance is why Deborah M. Gordon, StanfordUniversity assistant professor of biological sciences, studies ants."I'm interested in the kind of system where simple units together do behave in complicated ways," she said.No one gives orders in an ant colony, yet each ant decides what to do next.For instance, an ant may have several job descriptions. When the colony discovers a new source of food, an ant doing housekeeping duty may suddenly become a forager. Or if the colony's territory size expands or contracts, patroller ants change the shape of their reconnaissance pattern to conform to the new realities. Since no one is in charge of an ant colony - including the misnamed "queen," which is simply a breeder - how does each ant decide what to do?This kind of undirected behavior is not unique to ants, Gordon said. How do birds flying in a flock know when to make a collective right turn? All anchovies and other schooling fish seem to turn in unison, yet no one fish is the leader.Gordon studies harvester ants in Arizona and, both in the field and in her lab, the so-called Argentine ants that are ubiquitous to coastal California.Argentine ants came to Louisiana in a sugar shipment in 1908. They were driven out of the Gulf states by the fire ant and invaded California, where they have displaced most of the native ant species. One of the things Gordon is studying is how they did so. No one has ever seen an ant war involving the Argentine species and the native species, so it's not clear whether they are quietly aggressive or just find ways of taking over food resources and territory.The Argentine ants in her lab also are being studied to help her understand how they change behavior as the size of the space they are exploring varies."The ants are good at finding new places to live in and good at finding food," Gordon said. "We're interested in finding out how they do it."Her ants are confined by Plexiglas walls and a nasty glue-like substance along the tops of the boards that keeps the ants inside. She moves the walls in and out to change the arena and videotapes the ants' movements. A computer tracks each ant from its image on the tape and reads its position so she has a diagram of the ants' activities.The motions of the ants confirm the existence of a collective."A colony is analogous to a brain where there are lots of neurons, each of which can only do something very simple, but together the whole brain can think. None of the neurons can think ant, but the brain can think ant, though nothing in the brain told that neuron to think ant."For instance, ants scout for food in a precise pattern. What happens when that pattern no longer fits the circumstances, such as when Gordon moves the walls?"Ants communicate by chemicals," she said. "That's how they mostly perceive theworld; they don't see very well. They use their antennae to smell. So to smell something, they have to get very close to it."The best possible way for ants to find everything - if you think of the colony as an individual that is trying to do this - is to have an ant everywhere all the time, because if it doesn't happen close to an ant, they're not going to know about it. Of course, there are not enough ants in the colony to do that, so somehow the ants have to move around in a pattern that allows them to cover space efficiently."Keeping in mind that no one is in charge of a colony and that there is no central plan, how do the ants adjust their reconnaissance if their territory expands or shrinks?"No ant told them, 'OK, guys, if the arena is 20 by 20. . . .' Somehow there has to be some rule that individual ants use in deciding to change the shape of their paths so they cover the areas effectively. I think that that rule is the rate in which they bump into each other."The more crowded they are, the more often each ant will bump into another ant. If the area of their territory is expanded, the frequency of contact decreases. Perhaps, Gordon thinks, each ant has a threshold for normality and adjusts its path shape depending on how often the number of encounters exceeds or falls short of that threshold.If the territory shrinks, the number of contacts increases and the ant alters its search pattern. If it expands, contact decreases and it alters the pattern a different way.In the Arizona harvester ants, Gordon studies tasks besides patrolling. Each ant has a job."I divide the tasks into four: foraging, nest maintenance, midden [piling refuse, including husks of seeds] and patrolling - patrollers are the ones that come out first in the morning and look for food. The foragers go where the patrollers find food."The colony has about eight different foraging paths. Every day it uses several of them. The patrollers go out first on the trails and they attract each other when they find food. By the end of an hour's patrolling, most patrollers are on just a few trails. . . . All the foragers have to do is go where there are the most patrollers."Each ant has its prescribed task, but the ants can switch tasks if the collective needs it. An ant on housekeeping duty will decide to forage. No one told it to do so and Gordon and other entomologists don't know how that happens."No ant can possibly know how much food everybody is collecting, how many foragers are needed," she said. "An ant has to have very simple rules that tell it, 'OK, switch and start foraging.' But an ant can't assess globally how much food the colony needs."I've done perturbation experiments in which I marked ants according to what task they're doing on a given day. The ants that were foraging for food were green, those that were cleaning the nest were blue and so on. Then I created some new situation in the environment; for example, I create a mess that the nest maintenance workers have to clean up or I'll put out extra food that attracts more foragers."It turns out that ants that were marked doing a certain task one day switch to do a different task when conditions change."Of about 8,000 species of ants, only about 10 percent have been studied thus far."It's hard to generalize anything about the behavior of ants," Gordon said. "Most of what we know about ants is true of a very, very small number of species compared to thenumber of species out there."天才儿童TIME: 5-7'HOW IQ BECOMES IQIn 1904 the French minister of education, facing limited resources for schooling, sought a way to separate the unable from the merely lazy. Alfred Binet got the job of devising selection principles and his brilliant solution put a stamp on the study of intelligence and was the forerunner of intelligence tests still used today. He developed a thirty-problem test in 1905, which tapped several abilities related to intellect, such as judgment and reasoning. The test determined a given child's mental age'. The test previously established a norm for children of a given physical age. For example, five-year-olds on average get ten items correct, therefore, a child with a mental age of five should score 10, which would mean that he or she was functioning pretty much as others of that age. The child's mental age was then compared to his physical age.A large disparity in the wrong direction (e.g., a child of nine with a mental age of four) might suggest inability rather than laziness and means that he or she was earmarked for special schooling. Binet, however, denied that the test was measuring intelligence and said that its purpose was simply diagnostic, for selection only. This message was however lost and caused many problems and misunderstandings later.Although Binet's test was popular, it was a bit inconvenient to deal with a variety of physical and mental ages. So, in 1912, Wilhelm Stern suggested simplifying this by reducing the two to a single number. He divided the mental age by the physical age and multiplied the result by 100. An average child, irrespective of age, would score 100. a number much lower than 100 would suggest the need for help and one much higher would suggest a child well ahead of his peer.This measurement is what is now termed the IQ (intelligence quotient) score and it has evolved to be used to show how a person, adult or child, performed in relation to others. The term IQ was coined by Lewis m. Terman, professor of psychology and education of Stanford University, in 1916. He had constructed an enormously influential revision of Binet's test, called the Stanford-Binet test, versions of which are still given extensively.The field studying intelligence and developing tests eventually coalesced into a sub-field of psychology called psychometrics (psycho for ‘mind' and metrics for 'measurements'). The practical side of psychometrics (the development and use of tests) became widespread quite early, by 1917, when Einstein published his grand theory of relativity, mass-scale testing was already in use.Germany's unrestricted submarine warfare (which led to the sinking of the Lusitania in 1915) provoked the United States to finally enter the first world war in the same year. The military had to build up an army very quickly and it had two million inductees to sort out. Who would become officers and who enlisted men? Psychometricians developed two intelligence tests that helped sort all these people out, at least to some extent. This was the first major use of testing to decide who lived and who died since officers were a lot safer on the battlefield. The tests themselves were given under horrendously bad conditions and the examiners seemed to lack common sense. A lot of recruits simply had no idea what to do and in several sessions most inductees scored zero! The examiners also came up with thequite astounding conclusion from the testing that the average American adult's intelligence was equal to that of a thirteen-year-old!Nevertheless, the ability for various authorities to classify people on scientifically justifiable premises was too convenient and significant to be dismissed lightly, so with all good astounding intentions and often over enthusiasm, society's affinity for psychological testing proliferated.Back in Europe, Sir Cyril Burt, professor of psychology at University College London from 1931 to 1950, was a prominent figure for his contribution to the field. He was a firm advocate of intelligence testing and his ideas fitted in well with English cultural ideas of elitism. A government committee in 1943 used some of Burt's ideas in devising a rather primitive typology on children's intellectual behavior. All were tested at age eleven and the top 15 or 20 per cent went to grammar schools with good teachers and a fast pace of work to prepare for the few university places available. A lot of very bright working-class children, who otherwise would never have succeeded, made it to grammar schools and universities.The system for the rest was however disastrous. These children attended lesser secondary or technical schools and faced the prospect of eventual education oblivion. They felt like dumb failures, which having been officially and scientifically branded. No wonder their motivation to study plummeted. It was not until 1974 that the public education system was finally reformed. Nowadays it is believed that Burt has fabricated a lot of his data. Having an obsession that intelligence is largely genetic, he apparently made up twin studies, which supported this idea, at the same time inventing two co-workers who were supposed to have gathered the results.Intelligence testing enforced political and social prejudice and their results were used to argue that Jews ought to be kept out of the United States because they were so intelligently inferior that they would pollute the racial mix. And blacks ought not to be allowed to breed at all. Abuse and test bias controversies continued to plaque psychometrics.Measurement is fundamental to science and technology. Science often advances in leaps and bounds when measurement devices improve. Psychometrics has long tried to develop ways to gauge psychological qualities such as intelligence and more specific abilities, anxiety, extroversion, emotional stability, compatibility with marriage partner and so on. Their scores are often given enormous weight. A single IQ measurement can take on a life of its own if teachers and parents see it as definitive. It became a major issue in the 70s when court cases were launched to stop anyone from making important decisions based on IQ test scores. the main criticism was and still is that current tests don't really measure intelligence. Whether intelligence can be measured at all is still controversial. some say it cannot while others say that IQ tests are psychology's greatest accomplishments.全球变暖A Canary in the Coal MineThe Arctic seems to be getting warmer. So what?A. “Climate change in the Arctic is a reality now!”So insists Robert Corell, an oceanographer with the American Meteorological Society. Wild-eyed proclamations are all too common when it comes to global warming, but in this case his assertion seems well founded.B. At first sight, the ACIA’s (American Construction Inspectors Association) report’s conclusions are not so surprising. After all, scientists have long suspected that several factors lead to greater temperature swings at the poles than elsewhere on the planet. One is albedo —the posh scientific name for how much sunlight is absorbed by a planet’s surface, and how much is reflected. Most of the Polar Regions are covered in snow and ice, which are much more reflective than soil or ocean. If that snow melts, the exposure of dark earth (which absorbs heat) acts as a feedback loop that accelerates warming. A second factor that makes the poles special is that the atmosphere is thinner there than at the equator, and so less energy is required to warm it up. A third factor is that less solar energy is lost in evaporation at the frigid poles than in the steamy tropics.C. And yet the language of this week’s report is still eye-catching: “the Arctic is now experiencing some of the most rapid and severe climate change on Earth.”The last authoritative assessment of the topic was done by the UN’s Intergovernmental Panel on Climate Change (IPCC) in 2001. That report made headlines by predicting a rise in sea level of between 10cm (four inches) and 90cm, and a temperature rise of between 1.4°C and 5.8°C over this century. However, its authors did not feel confident in predicting either rapid polar warming or the speedy demise of the Greenland ice sheet. Pointing to evidence gathered since the IPCC report, this week’s report suggests trouble lies ahead.D. The ACIA reckons that in recent decades average temperatures have increased almost twice as fast in the Arctic as they have in the rest of the world. Skeptics argue that there are places, such as the high latitudes of the Greenland ice sheet and some buoys at sea, where temperatures seem to have fallen. On the other hand, there are also places, such as parts of Alaska, where they have risen far faster than average. Robin Bell, a geophysicist at Columbia University who was not involved in the report’s compilation, believes that such conflicting local trends point to the value of the international, interdisciplinary approach of this week’s report. As he observes, “climate change, like the weather, can be patchy and you can get fooled unless you look at the whole picture.”E. And there is other evidence of warming to bolster the ACIA’s case. For example, the report documents the widespread melting of glaciers and of sea ice, a trend already making life miserable for the polar bears and seals that depend on that ice. It also notes a shortening of the snow season. The most worrying finding, however, is the evidence — still preliminary — that the Greenland ice sheet may be melting faster than previously thought.F. That points to one reason the world should pay attention to this week’s report. Like a canary in a coal mine, the hypersensitive Polar Regions may well experience the full force of global warming before the rest of the planet does. However, there is a second and bigger reason to pay attention. An unexpectedly rapid warming of the Arctic could also lead directly to greater climate change elsewhere on the planet.G. Arctic warming may influence the global climate in several ways. One is that huge amounts of methane, a particularly potent greenhouse gas, are stored in the permafrost of the tundra. Although a thaw would allow forests to invade the tundra, which would tend to ameliorate any global warming that is going on (since trees capture carbon dioxide, the greenhouse gas most talked about in the context of climate change), a melting of the permafrost might also lead to a lot of trapped methane being released into the atmosphere, more than offsetting the cooling effects of the new forests.H. Another worry is that Arctic warming will influence ocean circulation in ways that are not fully understood. One link in the chain is the salinity of seawater, which is decreasing in the north Atlantic thanks to an increase in glacial melt waters. “Because fresh water and salt water have different densities, this ‘freshening’ of the ocean could change circulation patterns.” said Dr. Thomson, a British climate expert. “The most celebrated risk is to the mid-Atlantic Conveyor Belt, a current which brings warm water from the tropics to north-western Europe, and which is responsible for that region’s unusually mild winters,”he added. Some of the ACIA’s experts are fretting over evidence of reduced density and salinity in waters near the Arctic that could adversely affect this current.I. The biggest popular worry, though, is that melting Arctic ice could lead to a dramatic rise in sea level. Here, a few caveats are needed. For a start, much of the ice in the Arctic is floating in the sea already. Archimedes’s principle shows that the melting of this ice will make no immediate difference to the sea’s level, although it would change its albedo. Second, if land ice, such as that covering Greenland, does melt in large quantities, the process will take centuries. And third, although the experts are indeed worried that global warming might cause the oceans to rise, the main way they believe this will happen is by thermal expansion of the water itself.J. Nevertheless, there is some cause for nervousness. As the ACIA researchers document, there are signs that the massive Greenland ice sheet might be melting more rapidly than was thought a few years ago. Cracks in the sheet appear to be allowing melt water to trickle to its base, explains Michael Oppenheimer, a climatologist at Princeton University who was not one of the report’s authors. That water may act as a lubricant, speeding up the sheet’s movement into the sea. If the entire sheet melted, the sea might rise by 6-7 meters. But when will this kind of disastrous ice disintegration really happen? While acknowledging it this century is still an unlikely outcome, Dr. Oppenheimer argues that the evidence of the past few years suggests it is more likely to happen over the next few centuries if the world does not reduce emissions of greenhouse gases. He worries that an accelerating Arctic warming trend may yet push the ice melt beyond an “irreversible on / off switch”.K. That is scary stuff, but some scientists remain unimpressed. Patrick Michaels, a climatologist at the University of Virginia, complains about the ACIA’s data selection, which he believes may have produced evidence of “spurious warming”. He also points out, in a new book, that even if Arctic temperatures are rising, that need not lead directly to the ice melting. As he puts it, “Under global warming, Greenland’s ice indeed might grow, especially if the warming occurs mostly in winter. After all, warming the air ten degrees when the temperature is dozens of degrees below freezing is likely to increase snowfall, since warmer air is generally moister and precipitates more water.”L. Nils-Axel Morner, a Swedish climate expert based at Stockholm University, points out that observed rises in sea levels have not matched the IPCC’s forecasts. Since this week’s report relies on many such IPCC assumptions, he concludes it must be wrong. Others acknowledge that there is a warming trend in the Arctic, but insist that the cause is natural variability and not the burning of fossil fuels. Such folk point to the extraordinarily volatile history of Arctic temperatures. These varied, often suddenly, long before sport-utility vehicles were invented. However, some evidence also shows that the past few millenniahave been a period of unusual stability in the Arctic. It is just possible that the current period of warming could tip the delicate Arctic climate system out of balance, and so drag the rest of the planet with it.M. Not everybody wants to hear a story like that. But what people truly believe is happening can be seen in their actions better than in their words. One of the report’s most confident predictions is that the breakup of Arctic ice will open the region to long-distance shipping and, ironically, to drilling for oil and gas. It is surely no coincidence, then, that the Danish government, which controls Greenland, has just declared its intention to claim the mineral rights under the North Pole. It, at least, clearly believes that the Arctic ocean may soon be i人类文字进化史History of WritingWriting was first invented by the Sumerians in ancient Mesopotamia before 3,000 BC. It was also independently invented in Meso-America before 600 BC and probably independently invented in China before 1,300 BC. It may have been independently invented in Egypt around 3,000 BC although given the geographical proximity between Egypt and Mesopotamia the Egyptians may have learnt writing from the Sumerians.There are three basic types of writing systems. The written signs used by the writing system could represent either a whole word, a syllable or an individual sound. Where the written sign represents a word the system is known as logographic as it uses logograms which are written signs that represent a word. The earliest writing systems such as the Sumerian cuneiform, Egyptian hieroglyphics and Mayan glyphs are predominantly logographics as are modern Chinese and Japanese writing systems. Where the written sign represents a syllable the writing system is known as syllabic. Syllabic writing systems were more common in the ancient world than they are today. The Linear A and B writing systems of Minoan Crete and Mycenaean Greece are syllabic. The most common writing systems today are alphabetical. These involve the written sign (a letter) representing a single sound (known as a phoneme). The earliest known alphabetical systems were developed by speakers of semetic languages around 1700 BC in the area of modern day Israel and Palestine. All written languages will predominately use one or other of the above systems. They may however partly use the other systems. No written language is purely alphabetic, syllabic or logographic but may use elements from any or all systems.Such fully developed writing only emerged after development from simplier systems. Talley sticks with notches on them to represent a number of sheep or to record a debt have been used in the past. Knotted strings have been used as a form of record keeping particularly in the area around the Pacific rim. They reached their greatest development with the Inca quipus where they were used to record payment of tribute and to record commercial transactions. A specially trained group of quipu makers and readers managed the whole system. The use of pictures for the purpose of communication was used by native Americans and by the Ashanti and Ewe people in Africa. Pictures can show qualities and characteristics which can not be shown by tally sticks and knot records. They do not however amount to writing as they do not bear a conventional relationship to language. Even so, the Gelb dictum (from its originator Ignace Gelb), that “At the basis of all writing stands the picture” has been widely accepted.An alternative idea was that a system by which tokens, which represented objects likesheep, were placed in containers and the containers were marked on the outside indicating the number and type of tokens within the container gave rise to writing in Mesopotamia. The marks on the outside of the container were a direct symbolic representation of the tokens inside the container and an indirect symbolic representation of the object the token represented. The marks on the outside of the containers were graphically identical to some of the earliest pictograms used in Sumerian cuneiform, the worlds first written language. However cuneiform has approximately 1,500 signs and the marks on the ouside of the containers can only explain the origins of a few of those signs.The first written language was the Sumerian cuneiform. Writing mainly consisted of records of numbers of sheep, goats and cattle and quantites of grain. Eventually clay tablets were used as a writing surface and were marked with a reed stylus to produce the writing. Thousands of such clay tablets have been found in the Sumerian city of Uruk. The earliest Sumerian writing consists of pictures of the objects mentioned such as sheep or cattle. Eventually the pictures became more abstract and were to consist of straight lines that looked like wedgesce-free.阅读常用词组：1. abide by(=be faithful to ; obey)忠于;遵守。
小学生常见英文缩写
常用英文缩写(英语星期月份等)作者:xxhai星期星期一：Mon.=Monday星期二：Tues.=Tuesday星期三：Wed.=Wednesday星期四：Thur.=Thurday星期五： Fri.=Friday星期六：Sat.=Saturday星期天：Sun.=Sunday月份一月份＝JAN. Jan.=January二月份＝FEB. Feb.=February三月份＝MAR. Mar.=March四月份＝APR. Apr.=April五月份＝MAY May=May六月份＝JUN. Jun.=June七月份＝JUL. Jul.=July八月份＝AUG. Aug.=August九月份＝SEP. Sept.=September十月份＝OCT. Oct.=October十一月份＝NOV. Nov.=November十二月份＝DEC. Dec.=December注意：“.”不能省略这里给大家个例子，比如今天2007年3月20日Mar.20，2007写日期时，可以用基数词（避免出现不必要的失误）1，2，3，4，5，。
28，29，30，31等。
怎样用英语表达年、月、日一、年份在英语中,年份一般用阿拉伯数字写出,其读。
写方法有以下几种:1、四位数的年份,一般前两个数为一个单位,后两个数为一个单位,依次按基数词读出。
如:1763年写作:1763读作:seventeen sixty-three或seventeen hundred and sixty-three2006年写作:2006。
读作:two thousand and six2063年写作:2063。
读作:twenty sixtythree或twenty hundred andsixty-three1050年写作:1050。
读作:ten fifty或ten hundred and fifty2、三位数的年份,可以按基数词读出,或者第一个数字为一个单位,后两个数字为一个单位,按基数词读出。
科技英语综合教程(第二版)课件unit 3 Artificial Intelligence and
The Past, Present and Future of Big Data in Marketing
Academic Skills
Translating skills
Translation of idioms——切 忌望文生义
Intensive Reading Lead-in
Unit 3 Artificial Intelligence and Big Data
Watch the video clip and fill in the blanks with the words you have heard in video.
machines.
2. Machine learning is the technology that's responsible for most of this d2)isruption. 3. It allows machines to learn from data and m3)imic some of the things that humans can do. 4. We bring together hundreds of thousands of experts to solve important problems for
seen before.
8. The future state of any single job lies in the answer to a single question: To what extent is that job reducible to 8f)requent, high-volume tasks, and to what extent does it involve tackling novel situations?
ant intelligence译文
ant intelligence译文蚂蚁是众所周知的智慧生物之一，它们拥有令人惊叹的智力和组织能力。
在这篇文章中，我们将探索蚂蚁的智慧，以及它们是如何利用这种智慧来生活和繁衍的。
蚂蚁的智慧可以从它们的沟通和协作能力中看出。
蚂蚁通过释放一种称为信息素的化学物质来与其他蚂蚁沟通。
信息素可以用来标记食物源、告诉其他蚂蚁该去哪里或警告危险。
蚂蚁通过这种沟通方式能够高效地组织和协调行动，从而将复杂的任务分解为简单的步骤并完成。
除了沟通，蚂蚁还展示了学习和适应的能力。
当蚂蚁面临新的环境或问题时，它们能够通过尝试和错误来学习并找到解决方案。
蚂蚁会记住哪些食物源是最有价值的，哪些路径是最短的，以及如何避开危险。
这种学习能力使蚂蚁能够适应不同的环境，并在面临困难时找到最佳的解决方案。
蚂蚁还展示了集体智慧的概念。
集体智慧是指一个群体中的每个成员都做出智慧决策，从而使整个群体受益。
蚂蚁的殖民地是一个充满集体智慧的例子。
每只蚂蚁都根据自己沟通收到的信息和个人经验做出决策，但这些决策始终是为了整个殖民地的最大利益。
蚂蚁可以调整自己的行动以适应整体目标，并相互之间进行协作，使整个殖民地发挥最大的效益。
蚂蚁的智慧还可以在它们解决复杂问题时体现出来。
许多蚂蚁物种有能力构建复杂的巢穴和结构。
它们能够选择最佳的材料和位置来建造巢穴，并根据巢穴的需要进行修复和扩建。
此外，一些蚂蚁物种还能够利用自己的体形和力量来搬运和运输重物。
这些活动需要良好的规划、协作和执行能力，而蚂蚁完全能够胜任。
蚂蚁的智慧还可以从它们的决策过程中看出。
蚂蚁在做出决策时会综合考虑多种因素，包括个人经验、地理环境和所获得的信息。
蚂蚁在做出决策之前会进行一系列的评估和权衡，以找到最佳的解决方案。
这种决策过程几乎是无声无息的，但它确实存在，并且在蚂蚁的生活中起着重要的作用。
总的来说，蚂蚁拥有令人惊叹的智慧和组织能力。
它们通过沟通、学习、适应、集体智慧、解决复杂问题和决策等方式展示了它们的智慧。
世界上最大的ant英语脑筋急转弯
世界上最大的ant英语脑筋急转弯全文共3篇示例，供读者参考篇1The world's largest ant brain teaser:There is a famous riddle that asks: "What is the world's largest ant?" Many people may assume that the answer is the largest physical ant in the world, but in this brain teaser, the answer is a bit more abstract.In this brain teaser, the answer to the riddle is the "Elephant." This may confuse some individuals, as an elephant is not known for being a small insect like an ant. However, the key to solving this riddle lies in the characteristics of ants and elephants.Ants are known for their strength in numbers and their ability to work together in a highly organized and efficient manner. They are able to lift objects many times their weight and create complex tunnels and structures. On the other hand, elephants are known for their intelligence and memory. They have the largest brains of any land animal and are capable of forming strong social bonds with other elephants.In this brain teaser, the answer "Elephant" is meant to highlight the idea that the world's largest ant is not a physical ant, but rather a metaphorical one. Just like ants, elephants also possess impressive qualities such as strength, teamwork, and organization. By thinking outside the box and considering the characteristics of both ants and elephants, we can arrive at the clever answer to this brain teaser.So, the next time you come across this riddle, remember that the world's largest ant is not a tiny insect, but rather a majestic creature with a big brain - the Elephant.篇2The World's Biggest AntOne day, a group of scientists was conducting a study on ants in the Amazon rainforest. As they were exploring the dense jungle, they stumbled upon a colony of ants unlike any they had ever seen before. These ants were massive - much larger than any normal ant. The scientists were amazed and couldn't believe their eyes.They decided to capture one of the giant ants to study it further. After careful observation and measurement, they concluded that this ant was indeed the largest ant in the world. Itwas nearly the size of a small dog and had enormous mandibles that could easily crush a human finger.The scientists were both fascinated and puzzled by the existence of such a gigantic ant. They wondered how it had grown to be so large and what implications this discovery could have for the world of entomology.As they continued their research, they discovered that this giant ant was not alone. There were several others of similar size living in the colony. The scientists observed their behavior and interactions, trying to understand how these ants had evolved to be so massive.After months of study, the scientists finally came to a conclusion. These giant ants were a result of a strange mutation that had occurred within the colony. Somehow, a genetic anomaly had caused these ants to grow to an enormous size, making them the largest ants in the world.The discovery of the world's biggest ant was a groundbreaking moment in the world of science. It opened up new avenues of research and sparked a renewed interest in the study of insects. Who knows what other surprises the natural world may hold, waiting to be discovered by curious minds and adventurous scientists.篇3The world's largest ant brain teaser:There is a famous riddle that goes like this: "What is the world's largest ant?" And the answer is: "Elephant!"This brain teaser may seem simple at first glance, but it actually requires a bit of creative thinking to solve. Let's break it down:1. The riddle mentions an ant, which is a small insect known for its strength and teamwork. Ants are tiny creatures that live in colonies and work together to build intricate underground tunnels, gather food, and protect their queen.2. Elephants, on the other hand, are giant mammals that roam the savannas and forests of Africa and Asia. They are known for their large ears, long trunks, and impressive tusks. Elephants are some of the largest land animals on Earth, weighing several tons and standing up to 13 feet tall at the shoulder.3. So, how does an elephant relate to the world's largest ant? The answer lies in the clever wordplay of the riddle. By asking "What is the world's largest ant?" the riddle tricks the listener into thinking of a type of ant that is physically large orsuper-sized. However, the answer is a surprising twist that plays on the dual meanings of the words "ant" and "elephant."4. In this riddle, the term "largest" does not refer to the size of the ant itself, but rather to the overall concept of size and scale in the animal kingdom. By choosing an elephant as the answer, the riddle challenges our assumptions and forces us to think outside the box.5. This brain teaser is a fun and lighthearted way to exercise our critical thinking skills and appreciate the cleverness of language and riddles. It reminds us that sometimes the most unexpected answers can be the most satisfying and entertaining.In conclusion, the world's largest ant brain teaser may be a simple riddle on the surface, but it contains hidden depths and surprises that make it a classic puzzle for all ages to enjoy. The next time you hear this riddle, remember that the answer may not be what it seems – and be prepared to think like an elephant to solve it!。
deepblue人工智能
deepblue人工智能DeepBlue人工智能一、引言人工智能（Artificial Intelligence）是指利用计算机科学、数学、心理学等相关领域的知识和技术，使计算机系统具有一定的智能和自我学习和适应能力的一门学科。
人工智能技术已经在很多领域得到了广泛的应用，对现代社会的生产、生活、科技、文化等方面产生了深刻的影响。
DeepBlue（深蓝）是一款由IBM公司开发的计算机系统，最早于1996年打败国际象棋世界冠军加里·卡斯帕罗夫（Garry Kasparov），被誉为人工智能领域的里程碑事件。
本文将详细描述DeepBlue人工智能的背景、技术、应用和前景等方面。
二、背景在20世纪80年代和90年代初期，人工智能领域的研究集中于知识表示、知识推理、自然语言处理等方面，但计算机在复杂的游戏中胜过人类一直是人工智能领域的一个重要目标。
国际象棋是一个非常复杂的游戏，它的状态空间（即可能的棋盘布局）非常大，将近10的120次方，远大于宇宙中的原子数。
因此，要开发能够在国际象棋中战胜人类的计算机程序是一项非常有挑战性的任务。
从20世纪60年代开始，计算机科学家们就开始尝试编写能够下国际象棋的程序，最早的成功只能下三到四层（即下到第三或第四步）的棋。
到20世纪80年代初期，计算机程序的性能已经有了很大的提升，可以下五层甚至六层的棋，但仍然不能和顶尖棋手相提并论。
为了提高计算机在国际象棋中的跟人类比赛的实力，IBM公司于1985年开始开发DeepBlue计算机，目标是把计算机的性能提高到可以战胜国际象棋世界冠军的水平。
在经过多次升级和改进后，DeepBlue在1996年终于达到了这个目标，战胜了国际象棋世界冠军加里·卡斯帕罗夫。
三、技术DeepBlue是一台超级计算机，它使用了大量的处理器和内存，以及专门为国际象棋开发的算法和策略。
下面将分别介绍DeepBlue的硬件和软件技术。
1. 硬件DeepBlue使用了一个名为RS/6000的计算机体系结构，这是一种由IBM公司研发的高性能计算机体系结构。
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Ant Intelligence1. When we think of intelligent members of the animal kingdom, the creatures that spring immediately to mind are apes and monkeys. Butin fact the social lives ofsome members of the insectkingdom are sufficientlycomplex to suggest morethan a hint of intelligence.Among these, the world of the ant has comein for considerable scrutiny lately, and theidea that ants demonstrate sparks ofcognition has certainly not been rejected bythose involved in these investigations.2. Ants store food, repel attackers and usechemical signals to contact one another incase of attack. Such chemicalcommunication can be compared to thehuman use of visual and auditory channels(as in religious chants, advertising imagesand jingles, political slogans and martialmusic) to arouse and propagate moods andattitudes. The biologist Lewis Thomas wrote,Ants are so much like human beings as tobe an embarrassment. They farm fungi, raiseaphids* as livestock, launch armies to war,use chemical sprays to alarm and confuseenemies, capture slaves, engage in childlabour, exchange information ceaselessly. They do everything but watch television.3. However, in ants there is nocultural transmission -everything must be encodedin the genes - whereas inhumans the opposite istrue. Only basic instincts arecarried in the genes of anewborn baby, other skillsbeing learned from others inthe community as the childgrows up. It may seem that this culturalcontinuity gives us a huge advantage overants. They have never mastered firenorprogressed. Their fungus farming and aphidherding crafts are sophisticated whencompared to the agricultural skills ofhumans five thousand years ago but havebeen totally overtaken by modern humanagribusiness.4. Or have they? The farming methods of antsare at least sustainable. They do not ruinenvironments or use enormous amounts ofenergy. Moreover, recent evidence suggeststhat the crop farming of ants may be moresophisticated and adaptable than wasthought.5. Ants were farmers fifty million years beforehumans were. Ants can't digest the cellulosein leaves - but some fungi can. The antstherefore cultivate these fungi in their nests,bringing them leaves to feed on, and then、use them as a source of food. Farmer antssecrete antibiotics to control other fungi thatmight act as 'weeds', and spread waste tofertilise the crop.6. It was once thought that the fungus thatants cultivate was a single type that theyhad propagated, essentially unchanged fromthe distant past. Not so. Ulrich Mueller ofMaryland and his colleagues geneticallyscreened 862 different types of fungi takenfrom ants' nests. These turned out to behighly diverse: it seems that ants arecontinually domesticating new species. Evenmore impressively, DNA analysis of the fungisuggests that the ants improve or modify thefungi by regularly swapping and sharingstrains with neighbouring ant colonies.7. Whereas prehistoric man had no exposure tourban lifestyles - the forcing house ofintelligence - the evidence suggests thatants have lived in urban settings for close ona hundred million years, developing andmaintaining undergroundcities ofspecialised chambers and tunnels.8. When we survey Mexico City, Tokyo, LosAngeles, we are amazed at what has beenaccomplished by humans. Yet Hoelldoblerand Wilson's magnificent work for ant lovers,The Ants, describes a supercolony of the ant Formica yessensis on the Ishikari Coast ofHokkaido. This 'megalopolis' was reported tobe composed of 360 million workers and amillion queens living in 4,500interconnected nests across a territory of2.7 square kilometres.9. Such enduring and intricately meshed levelsof technical achievement outstrip by faranything achieved by our distant ancestors.We hail as masterpieces the cave paintingsin southern France and elsewhere, datingback some 20,000 years. Ant societiesexisted in something like their present formmore than seventy million years ago. Besidethis, prehistoric man looks technologicallyprimitive. Is this then some kind ofintelligence, albeit of a different kind10. Research conducted at Oxford, Sussex andZurich Universities has shown that whendesert ants return from a foraging trip, theynavigate by integrating bearings anddistances, which they continuously update intheir heads. They combine the evidence ofvisual landmarks with a mental library oflocal directions, all within a framework whichis consulted and updated. So ants can learntoo.11. And in a twelve-year programme of work,Ryabko and Reznikova have found evidencethat ants can transmit very complexmessages. Scouts who had located food in amaze returned to mobilise their foragingteams. They engaged incontact sessions, atthe end of which the scout was removed inorder to observe what her team might do.Often the foragers proceeded to the exactspot in the maze where the food had been.Elaborate precautions were taken to preventthe foraging team using odour clues.Discussion now centres on whether the routethrough the maze is communicated as a 'leftright'sequence of turns or as a 'compassbearing and distance' message.12. During the course of this exhaustive study,Reznikova has grown so attached to herlaboratory ants that she feels she knowsthem as individuals - even without the paintspots used to mark them. It's no surprisethat Edward Wilson, in his essay, 'In thecompany of ants', advises readers who askwhat to do with the ants in their kitchen to:'Watch where you step. Be careful of littlelives.'Questions 1-6Do the following statements agree with the information given in Reading Passage I?In boxes I 6 on your answer sheet, writeTRUE if the statement agrees with the informationFALSE if the statement contradicts the informationNOT GIVEN if there is no information on this1Ants use the same channels of communication as humans do.2City life is one factor that encourages the development of intelligence.3Ants can build large cities more quickly than humans do.4Some ants can find their way by making calculations based on distance and position.5In one experiment, foraging teams were able to use their sense of smell to find food.6The essay, 'In the company of ants', explores ant communication.Questions 7-13Complete the summary using the list of words, A-O, below.Write the correct letter, A-O, in boxes 7 -13 on your answer sheet.Ants as farmersAnts have sophisticated methods of farming, including herding livestock and growingcrops, which are in many ways similar to those used in human agriculture. The antscultivate a large number of different species of edible fungi which convert7into a form which they can digest. They use their own natural8 as weed-killers and also use unwanted materials as 9. Genetic analysis shows they constantly upgrade these fungi by developing new speciesand by 10 species with neighbouring ant colonies. In fact, the farmingmethods of ants could be said to be more advanced than human agribusiness, since theyuse11 methods, they do not affect the12and do notwaste13.A aphidsB agriculturalC celluloseD exchangingE energyF fertilizersG foodH fungiI growing J interbreeding K natural L other species M secretions N sustainable O environment。