Artificial intelligence (AI) is a branch of computer science concerned with building smart machines capable of performing tasks that normally necessitate human intelligence. In other words, students of AI learn how to develop artificial intelligence applications that are inspired by the ways people learn, reason, and make decisions.

\n

Students study advanced mathematics, engineering, computing, programming, and data structures to envision and create the AI technologies and systems that continue to transform so many areas of our lives \u2013 from agriculture, construction, and transportation to healthcare, human resources, manufacturing, marketing, and more.

\n

Once the subject matter of science fiction, artificial intelligence is no longer an alien concept. Today it is commonplace, streamlining business processes and enhancing consumer experiences.

", "display_order": 1, "created_at": "2019-10-01T11:36:05.561713-07:00", "updated_at": "2021-11-18T13:55:40.389194-08:00"}, {"degree_id": 602, "page": 1, "title": "Program Options", "summary_markdown": "**Bachelor\u2019s Degree in Artificial Intelligence \u2013 Four Year Duration** \r\nWhile they do exist, bachelor\u2019s programs in AI are not all that common, because most jobs in the field call for a master\u2019s. The AI bachelor\u2019s curriculum starts with an introduction to the concepts of artificial intelligence, machine learning, and data analysis. With these foundations, students go on to explore areas of AI research including big data and natural language processing, deep and reinforcement learning, computer vision, decision analysis, and robotics. The final requirement of AI programs offered at the undergrad level is typically a bachelor\u2019s thesis or capstone research project. \r\n\r\nHere is an example of a bachelor\u2019s program in artificial intelligence: \r\n\r\n- Introduction to Mathematics and Computer Science \r\n- Calculus \r\n- Introduction to Artificial Intelligence \r\n- Discrete Mathematics \r\n- Introduction to Programming \r\n- Introduction to Computing \r\n- Artificial Life with Cognitive Sciences \r\n- Linear Algebra \r\n- Introduction to Probability \r\n- Computer Architecture with Low-Level Programming \r\n- Algorithms and Data Structures \r\n- Operating Systems with Concurrency Programming (with multiple computations happening at the same time) \r\n- Statistics \r\n- Information Theory", "content_markdown": "- Data Compression Methods (methods to reduce the size of a file by re-encoding the file data to use fewer bits of storage than the original file) \r\n- Object Programming (makes code organized, reusable, and easy to maintain) \r\n- Data Base Systems \r\n- Combinational Optimization \r\n- Discrete Optimization \r\n- Software Engineering \r\n- Computer Networks \r\n- Machine Learning (an application of AI that provides systems the ability to automatically learn and improve from experience without being explicitly programmed) \r\n- Elements of Convex Optimization \r\n- Optimization Methods for Data Analysis \r\n- Data Mining \r\n- Data Visualization / Graphics \r\n- Robotics \r\n- Deep Learning (an AI function that mimics the workings of the human brain in processing data for use in detecting objects, recognizing speech, translating languages, and making decisions) \r\n- Internet Applications \r\n- Operational Research / Industrial Engineering \r\n- Information Retrieval \r\n- Problem Classes: Data Analysis and Artificial Intelligence \r\n- Computer Vision (enables computers to understand the content of images and videos) \r\n- Signal Processing \r\n- Natural Language Processing (setting up computers that can understand and process language) \r\n- Decision Analysis / Decision Support \r\n- Big Data and Distributed Processing \r\n- Theory and Practice of Processing Big Data \r\n- Reinforcement Learning and Multi-Agent Systems \r\n- Computational Intelligence \r\n- Problem Classes: Machine Learning and Artificial Intelligence \r\n- Ethics and Research \r\n- Scientific Writing Methodology \r\n- Vocational Internship \r\n- Cybersecurity \r\n- Semantic Web and Social Networks \r\n- Man-Machine Interaction \r\n- Declarative Programming and Expert Systems \r\n- AI and Games \r\n- Evolutionary Computation \r\n- Internet of Things \r\n- Spiking Neural Networks (a system software or hardware that works similarly to the tasks performed by neurons of the human brain) \r\n- Preparation for Scientific Research\r\n\r\n**Master\u2019s Degree in Artificial Intelligence \u2013 Two to Three Year Duration** \r\nThe master\u2019s degree is the most common credential in the field. While the bachelor\u2019s curriculum in artificial intelligence provides a foundation made up of core courses, the master\u2019s program is much more pointed. Students focus on a concentration of their choice and conduct research in that area, leading to their thesis. The AI master\u2019s curriculum often includes an internship. To be admitted to a master\u2019s program in artificial intelligence, students must have completed a bachelor\u2019s degree in AI or a related field such as computer science, robotics, or engineering. \r\n\r\nSchools may require that all AI master\u2019s students, regardless of their area of focus, take some basic graduate level courses in the discipline. Here are some examples: \r\n\r\n- Foundations of Logic and Model Theory \r\n- Statistics for Engineers \r\n- Fundamentals of Artificial Intelligence \r\n- Artificial Intelligence \u2013 Methods and Applications \r\n- Advanced Concepts in Machine Learning \r\n- Design of Interactive Intelligent Systems \r\n- Advanced Natural Language Processing \r\n\r\nAfter fulfilling compulsory course requirements, grad students proceed to concentrate their studies and research in a particular area. Here are some of the most common focus areas: \r\n\r\n- Reasoning and Decision Making \r\n- Machine Learning \r\n- Human-AI Interaction \r\n- Intelligent Robotics \r\n- Computational Linguistics / Speech Recognition and Processing \r\n- Computer Vision \r\n\r\n**Doctoral Degree in Artificial Intelligence \u2013 Two to Three Year Duration** \r\nDoctoral degree programs in artificial intelligence are relatively uncommon. Those that exist are aimed at individuals who wish to pursue a career in research and/or teaching at the university level. Ph.D. graduates in the field have deep knowledge in all important areas of theoretical computer science and artificial intelligence, including design and analysis of algorithms and data structures, processing big data, and solving complex problems.", "content_html": "\n

Master\u2019s Degree in Artificial Intelligence \u2013 Two to Three Year Duration
\nThe master\u2019s degree is the most common credential in the field. While the bachelor\u2019s curriculum in artificial intelligence provides a foundation made up of core courses, the master\u2019s program is much more pointed. Students focus on a concentration of their choice and conduct research in that area, leading to their thesis. The AI master\u2019s curriculum often includes an internship. To be admitted to a master\u2019s program in artificial intelligence, students must have completed a bachelor\u2019s degree in AI or a related field such as computer science, robotics, or engineering.

\n

Schools may require that all AI master\u2019s students, regardless of their area of focus, take some basic graduate level courses in the discipline. Here are some examples:

\n\n

After fulfilling compulsory course requirements, grad students proceed to concentrate their studies and research in a particular area. Here are some of the most common focus areas:

\n\n

Doctoral Degree in Artificial Intelligence \u2013 Two to Three Year Duration
\nDoctoral degree programs in artificial intelligence are relatively uncommon. Those that exist are aimed at individuals who wish to pursue a career in research and/or teaching at the university level. Ph.D. graduates in the field have deep knowledge in all important areas of theoretical computer science and artificial intelligence, including design and analysis of algorithms and data structures, processing big data, and solving complex problems.

", "display_order": 2, "created_at": "2019-10-01T11:36:05.562862-07:00", "updated_at": "2021-12-06T14:03:37.142493-08:00"}, {"degree_id": 602, "page": 1, "title": "Degrees Similar to Artificial Intelligence", "summary_markdown": "**[Computer Engineering](/degrees/computer-engineering-degree/)** \r\nThis degree field integrates electrical engineering and computer science. It teaches students how to develop computer hardware and software. The curriculum includes course in calculus, physics, computer system architecture and networking, digital-logic design, data structures, and programming languages. \r\n\r\n**[Computer Science](/degrees/computer-science-degree/)** \r\nThe field of computer science is focused on computer systems and how humans interact with them. Courses cover mathematics for computer science, artificial intelligence, data structures and algorithms, and introduction to program design. \r\n\r\n**[Computer Software Engineering](/degrees/computer-software-engineering-degree/)** \r\nDegree programs in computer software engineering teach students how to apply engineering principles to software development. Students learn how to design, build, test, implement, and maintain computer operating systems, as well as applications that allow end users to accomplish tasks on their computers, smartphones, and other electronic devices. Most programs begin with core engineering classes like mathematics, chemistry, and physics. \r\n\r\n**[Robotics Engineering](/degrees/robotics-engineering-degree/)** \r\nRobotics engineering is focused on designing robots and robotic systems than can perform duties that humans are either unable or prefer not to perform.", "content_markdown": "**[Robotics Technology](/degrees/robotics-technology-degree/)** \r\nDegree programs in robotics technology prepare students to work with engineers who design robots and robotic systems that can perform duties that humans are either unable or prefer not to perform. \r\n\r\n**[Simulation Programming](/degrees/simulation-programming-degree/)** \r\nSimulation programmers develop computer *simulations* that allow us to predict, see, think about, test, and manipulate real-world products, services, systems, processes, conditions, situations, and issues, without taking the risk and incurring the costs of doing so *in* the real world. Math, engineering, and computer science are the overlapping disciplines that simulation relies on. \r\n\r\nDegree programs in the field are made up of courses in these technical and scientific areas, but they are also focused on teaching the skills of abstracting, theorizing, hypothesizing, and intellectualizing. In other words, simulation programming students learn everything they need to conceptualize the world into models that are designed to reach solutions to many of the world\u2019s challenges and problems.", "content_html": "

Robotics Technology
\nDegree programs in robotics technology prepare students to work with engineers who design robots and robotic systems that can perform duties that humans are either unable or prefer not to perform.

\n

Simulation Programming
\nSimulation programmers develop computer simulations that allow us to predict, see, think about, test, and manipulate real-world products, services, systems, processes, conditions, situations, and issues, without taking the risk and incurring the costs of doing so in the real world. Math, engineering, and computer science are the overlapping disciplines that simulation relies on.

\n

Degree programs in the field are made up of courses in these technical and scientific areas, but they are also focused on teaching the skills of abstracting, theorizing, hypothesizing, and intellectualizing. In other words, simulation programming students learn everything they need to conceptualize the world into models that are designed to reach solutions to many of the world\u2019s challenges and problems.

", "display_order": 3, "created_at": "2019-10-01T11:36:05.563935-07:00", "updated_at": "2021-12-06T13:56:34.633654-08:00"}, {"degree_id": 602, "page": 1, "title": "Skills You’ll Learn", "summary_markdown": "Students of artificial intelligence come away from their studies with a considerable set of transferable skills: \r\n\r\n- Adaptability \r\n- Capacity for ongoing learning and grasping new concepts quickly \r\n- Communication and Collaboration / Teamwork \r\n- Conceptualization, Research, and Project Planning \r\n- Critical Thinking \r\n- Curiosity and Creativity \r\n- Judgement and Decision Making \r\n- Leadership \r\n- Mentoring \r\n- Monitoring \r\n- Perseverance and Patience \r\n- Self-Motivation and Inspiration \r\n- Systems Analysis \r\n- Systems Design \r\n- Systems Evaluation \r\n- Time Management \r\n- Work Ethic", "content_markdown": "", "content_html": "", "display_order": 4, "created_at": "2019-10-01T11:36:05.565002-07:00", "updated_at": "2021-11-30T13:56:45.221508-08:00"}, {"degree_id": 602, "page": 1, "title": "What Can You Do with an Artificial Intelligence Degree?", "summary_markdown": "Graduates of artificial intelligence apply their skills in data analytics, user experience, natural language processing, software engineering, programming, robotics, and machine learning in an ever-growing variety of sectors. Here are some examples of how AI-based systems are being developed for and used in many fields: \r\n\r\n**Agriculture** \r\n- Use of computer vision and machine learning to detect soil defects and nutrient deficiencies and identify where weeds are growing \r\n- AI-based drones and tractors \r\n- Weather monitoring systems \r\n- Use of AI robots to harvest crops \r\n\r\n**Automotive** \r\n- Development of self-driving vehicles \u2013 emergency braking, blind-spot monitoring, driver-assist steering \r\n- Predictive vehicle maintenance \r\n\r\n**Construction** \r\n- Predicting and preventing cost overruns based on project size, contract type, and competence of project managers \r\n- 3D building information modeling for efficient planning, design, construction, and management of buildings \r\n- Self-driving construction machinery to perform repetitive tasks such as pouring concrete, bricklaying, and demolition \r\n\r\n**Education** \r\n- Development of intelligent instruction design and digital platforms that use AI to provide learning, testing, and feedback to students \r\n- Real-time translation of what a teacher is saying \r\n- AI-supported tutoring and study programs \r\n- Automation of administrative tasks \r\n\r\n**Finance** \r\n- Automated financial investing", "content_markdown": "**Gaming** \r\n- AI-based drones and tractors \r\n- Creation of smart human-like non-player characters (NPCs) to interact with players \r\n- Prediction of human behavior leading to better game design and testing \r\n\r\n**Healthcare** \r\n- Disease detection and mapping in the field of radiology \r\n- Analysis of chronic conditions \r\n- Use of medical data to discover new drugs \r\n- Patient monitoring \r\n- AI powered robots move and carry goods and clean spaces and equipment \r\n\r\n**Human Resources** \r\n- Intelligent software to examine applications and resumes based on specific parameters \r\n\r\n**Manufacturing and Production** \r\n- Automated assembly lines \r\n- Manufacturing robots \r\n- AI powered robots move and carry goods and clean spaces and equipment \r\n\r\n**Marketing / Retail / E-Commerce** \r\n- Personalized shopping recommendation engines connect customers with marketing campaigns, conversational marketing bots, and potential purchases based on their browsing history and interests \r\n- Natural Language Processing is helping to create human sounding AI-powered virtual shopping assistants and chatbots \r\n- Fraud prevention \u2013 reducing credit card fraud by analyzing usage patterns; identifying fake customer reviews \r\n\r\n**Security and Surveillance** \r\n- Smart cities are using AI to manage energy usage and reduce crime \r\n- AI-based face recognition and biometric systems \r\n\r\n**Social Media** \r\n- AI considers user preferences to match them with posts \r\n- Automatic translation of posts from different languages \r\n- Fraud detection \r\n- Removal of propaganda and hate speech \r\n\r\n**Supply Chain Management** \r\n- Automated inventory, warehousing, and supply chain management \r\n\r\n**Transportation / Navigation** \r\n- GPS technology to improve safety \r\n- AI is detecting open and closed roads and analyzing traffic to optimize routes \r\n- Aircraft and train scheduling \r\n \r\n**Travel** \r\n- Virtual travel agents \r\n\r\n**Urban Planning** \r\n- Smart cities are using AI to manage energy usage and reduce crime \r\n\r\nThese are some common job titles in AI: \r\n- AI Architect \r\n- AI Ethicist \r\n- AI Interaction Designer \r\n- AI Product Engineer \r\n- AI Technology [Software Engineer](//www.chevelle-parts.com/careers/software-engineer/) \r\n- Big Data Engineer / Architect \r\n- Business Intelligence Developer \r\n- Computer Vision Engineer \r\n- [Data Scientist](//www.chevelle-parts.com/careers/data-scientist/) \r\n- Machine Learning Engineer \r\n- [Research Scientist](//www.chevelle-parts.com/careers/scientist/) \r\n- [Robotics Engineer](//www.chevelle-parts.com/careers/robotics-engineer/)", "content_html": "

Gaming
\n- AI-based drones and tractors
\n- Creation of smart human-like non-player characters (NPCs) to interact with players
\n- Prediction of human behavior leading to better game design and testing

\n

Healthcare
\n- Disease detection and mapping in the field of radiology
\n- Analysis of chronic conditions
\n- Use of medical data to discover new drugs
\n- Patient monitoring
\n- AI powered robots move and carry goods and clean spaces and equipment

\n

Human Resources
\n- Intelligent software to examine applications and resumes based on specific parameters

\n

Manufacturing and Production
\n- Automated assembly lines
\n- Manufacturing robots
\n- AI powered robots move and carry goods and clean spaces and equipment

\n

Marketing / Retail / E-Commerce
\n- Personalized shopping recommendation engines connect customers with marketing campaigns, conversational marketing bots, and potential purchases based on their browsing history and interests
\n- Natural Language Processing is helping to create human sounding AI-powered virtual shopping assistants and chatbots
\n- Fraud prevention \u2013 reducing credit card fraud by analyzing usage patterns; identifying fake customer reviews

\n

Security and Surveillance
\n- Smart cities are using AI to manage energy usage and reduce crime
\n- AI-based face recognition and biometric systems

\n

Social Media
\n- AI considers user preferences to match them with posts
\n- Automatic translation of posts from different languages
\n- Fraud detection
\n- Removal of propaganda and hate speech

\n

Supply Chain Management
\n- Automated inventory, warehousing, and supply chain management

\n

Transportation / Navigation
\n- GPS technology to improve safety
\n- AI is detecting open and closed roads and analyzing traffic to optimize routes
\n- Aircraft and train scheduling

\n

Travel
\n- Virtual travel agents

\n

Urban Planning
\n- Smart cities are using AI to manage energy usage and reduce crime

\n

These are some common job titles in AI:
\n- AI Architect
\n- AI Ethicist
\n- AI Interaction Designer
\n- AI Product Engineer
\n- AI Technology Software Engineer
\n- Big Data Engineer / Architect
\n- Business Intelligence Developer
\n- Computer Vision Engineer
\n- Data Scientist
\n- Machine Learning Engineer
\n- Research Scientist
\n- Robotics Engineer

", "display_order": 5, "created_at": "2019-10-01T11:36:05.566078-07:00", "updated_at": "2021-12-06T14:05:56.964977-08:00"}], "degree_specializations": []}">

什么是人工智能学位?

人工智能(AI)是计算机科学的一个分支,研究构建能够执行通常需要人类智能才能完成的任务的智能机器。换句话说,人工智能的学生学习如何开发人工智能应用程序,这些应用程序受到人们学习、推理和决策方式的启发。

学生们学习高等数学、工程、计算、编程和数据结构,以设想和创建人工智能技术和系统,这些技术和系统将继续改变我们生活的许多领域——从农业、建筑、交通到医疗保健、人力资源、制造、营销等等。

人工智能曾经是科幻小说的主题,如今它已不再是一个陌生的概念。如今,它已经很普遍,简化了业务流程,增强了消费者体验。

程序选项

人工智能学士学位-四年
虽然人工智能专业确实存在,但学士学位课程并不常见,因为该领域的大多数工作都需要硕士学位。人工智能学士课程从介绍人工智能、机器学习和数据分析的概念开始。有了这些基础,学生们将继续探索人工智能研究领域,包括大数据和自然语言处理、深度和强化学习、计算机视觉、决策分析和机器人技术。本科阶段提供的人工智能课程的最终要求通常是学士论文或顶点研究项目。

以下是人工智能学士课程的一个例子:

  • 数学与计算机科学概论“,
  • 微积分
  • 人工智能概论
  • 离散数学
  • 编程概论
  • 计算概论
  • 认知科学的人工生命
  • 线性代数
  • 概率论
  • 具有低级编程的计算机体系结构
  • 算法和数据结构
  • 具有并发编程的操作系统(同时进行多个计算)
  • 统计数据
  • 信息理论
  • 数据压缩方法(通过重新编码文件数据以使用比原始文件更少的存储位来减少文件大小的方法)
  • 对象编程(使代码有组织、可重用和易于维护)
  • 数据库系统
  • 组合优化
  • 离散优化
  • 软件工程
  • 计算机网络
  • 机器学习(人工智能的一种应用,为系统提供自动学习和从经验中改进的能力,而无需显式编程)
  • 凸优化要素
  • 数据分析的优化方法
  • 数据挖掘
  • 数据可视化/图形化
  • 机器人
  • 深度学习(一种人工智能功能,模仿人类大脑在处理数据时的工作方式,用于检测物体、识别语音、翻译语言和做出决定)
  • 互联网应用
  • 运筹学/工业工程
  • 信息检索
  • 问题类别:数据分析和人工智能
  • 计算机视觉(使计算机能够理解图像和视频的内容)
  • 信号处理
  • 自然语言处理(设置能够理解和处理语言的计算机)
  • 决策分析/决策支持
  • 大数据与分布式处理
  • 大数据处理理论与实践“,
  • 强化学习与多智能体系统
  • 计算智能
  • 问题类:机器学习和人工智能
  • 伦理与研究
  • 科学写作方法
  • 职业实习
  • 网络安全
  • 语义网和社会网络
  • 人机交互
  • 声明式编程和专家系统
  • AI与游戏
  • 进化计算
  • 物联网
  • 尖峰神经网络(一种系统软件或硬件,其工作原理类似于人脑神经元执行的任务)
  • 科研准备

人工智能硕士学位-两到三年的时间
硕士学位是该领域最常见的证书。虽然人工智能学士课程提供了由核心课程组成的基础,但硕士课程更有针对性。学生专注于他们的选择,并在该领域进行研究,从而完成他们的论文。人工智能硕士课程通常包括实习。要进入人工智能硕士课程,学生必须完成人工智能或相关领域的学士学位,如计算机科学、机器人或工程学。

学校可能会要求所有人工智能硕士的学生,无论他们的重点领域是什么,都要学习该学科的一些基础研究生水平的课程。下面是一些例子:

  • 逻辑学与模型理论基础“,
  • 工程师统计数字
  • 人工智能基础
  • 人工智能-方法与应用
  • 《机器学习的高级概念
  • 交互式智能系统设计“,
  • 高级自然语言处理

在完成必修课程要求后,研究生开始在特定领域集中学习和研究。以下是一些最常见的关注点:

  • 推理和决策
  • 机器学习
  • Human-AI交互
  • 智能机器人
  • 计算语言学/语音识别与处理
  • 计算机视觉

人工智能博士学位-两到三年的时间
人工智能方面的博士学位项目相对较少。现有的那些是针对那些希望在大学水平从事研究和/或教学事业的个人。该领域的博士毕业生在理论计算机科学和人工智能的所有重要领域都有深厚的知识,包括算法和数据结构的设计和分析,处理大数据以及解决复杂问题。

类似于人工智能的学位

计算机工程
该学位领域集成了电气工程和计算机科学。它教学生如何开发计算机硬件和软件。课程包括微积分、物理、计算机系统架构和网络、数字逻辑设计、数据结构和编程语言。

计算机科学
计算机科学领域的重点是计算机系统以及人类如何与它们交互。课程涵盖计算机科学、人工智能、数据结构和算法的数学,以及程序设计概论。

计算机软件工程
计算机软件工程学位课程教授学生如何将工程原理应用于软件开发。学生学习如何设计、构建、测试、实现和维护计算机操作系统,以及允许最终用户在其计算机、智能手机和其他电子设备上完成任务的应用程序。大多数课程都是从数学、化学和物理等核心工程课程开始的。

机器人技术工程学
机器人工程专注于设计能够执行人类不能或不愿执行的任务的机器人和机器人系统。

机器人技术
机器人技术学位课程使学生能够与工程师一起工作,这些工程师设计的机器人和机器人系统可以执行人类不能或不愿意执行的任务。

模拟编程
模拟程序员开发计算机模拟这使我们能够预测、观察、思考、测试和操作现实世界的产品、服务、系统、流程、条件、情况和问题,而无需承担风险和承担这样做的成本真实的世界。数学、工程学和计算机科学是模拟所依赖的交叉学科。

该领域的学位课程由这些技术和科学领域的课程组成,但它们也侧重于教授抽象、理论化、假设和智能化的技能。换句话说,模拟编程的学生学习他们需要的一切来将世界概念化到模型中,这些模型旨在解决世界上的许多挑战和问题。

你将学会的技能

学习人工智能的学生在毕业后会学到相当多的可转移技能:

  • 适应性
  • 持续学习和快速掌握新概念的能力
  • 沟通与协作/团队合作
  • 概念化、研究和项目规划
  • 批判性思维
  • 好奇心和创造力
  • 判断与决策
  • 领导
  • 指导
  • 监控
  • 毅力和耐心
  • 自我激励和灵感
  • 系统分析
  • 系统设计
  • 系统评价
  • 时间管理
  • 职业道德

有了人工智能学位你能做什么?

人工智能专业的毕业生将他们在数据分析、用户体验、自然语言处理、软件工程、编程、机器人和机器学习方面的技能应用于越来越多的领域。以下是一些基于人工智能的系统如何被开发和应用于许多领域的例子:

农业

  • 使用计算机视觉和机器学习来检测土壤缺陷和养分缺乏,并确定杂草生长的位置
  • 基于人工智能的无人机和拖拉机
  • 天气监测系统
  • 使用人工智能机器人收割庄稼

汽车

  • 自动驾驶汽车的发展——紧急制动、盲点监测、驾驶员辅助转向
  • 预测性车辆维修

建设

  • 根据项目规模、合同类型和项目经理的能力预测和防止成本超支
  • 用于高效规划、设计、施工和管理建筑物的三维建筑信息建模
  • 自动驾驶施工机械执行重复任务,如浇注混凝土、砌砖和拆除

教育

  • 开发智能教学设计和数字平台,使用人工智能为学生提供学习、测试和反馈
  • 实时翻译老师讲课内容
  • 人工智能支持的辅导和学习项目
  • 管理任务的自动化

金融

  • 自动理财投资

游戏

  • 基于人工智能的无人机和拖拉机
  • 创造类似人类的智能非玩家角色(npc)与玩家互动
  • 预测人类行为有助于更好的游戏设计和测试

医疗保健

  • 放射学领域的疾病检测和制图
  • 慢性病分析
  • 利用医疗数据发现新药
  • 病人监护
  • 人工智能驱动的机器人移动和搬运货物,清洁空间和设备

人力资源

  • 智能软件根据特定参数检查申请和简历

制造及生产

  • 自动化装配线
  • 制造机器人
  • 人工智能驱动的机器人移动和搬运货物,清洁空间和设备

营销/零售/电子商务

  • 个性化的购物推荐引擎根据客户的浏览历史和兴趣,将客户与营销活动、会话式营销机器人以及潜在的购买联系起来
  • 自然语言处理正在帮助创建听起来像人类的人工智能驱动的虚拟购物助手和聊天机器人
  • 欺诈预防-通过分析使用模式减少信用卡欺诈;识别虚假客户评论

保安及监察

  • 智能城市正在使用人工智能来管理能源使用和减少犯罪
  • 基于人工智能的人脸识别和生物识别系统

社交媒体

  • 人工智能会考虑用户的偏好,将其与帖子匹配
  • 自动翻译来自不同语言的帖子
  • 欺诈检测
  • 删除宣传和仇恨言论

供应链管理

  • 自动化库存、仓储和供应链管理

交通/航海

  • GPS技术提高安全性
  • 人工智能正在检测开放和封闭的道路,并分析交通状况以优化路线
  • 飞机和火车调度

旅行

  • 虚拟旅行社

城市规划

  • 智能城市正在使用人工智能来管理能源使用和减少犯罪

以下是人工智能领域常见的一些职位名称:

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