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": []}">

一个人工智能的学位是什么?

人工智能(AI)是计算机科学的一个分支关心建筑智能机器执行任务,通常需要人类智慧的能力。换句话说,AI的学生学习如何开发人工智能应用程序受到人们学习的方式,原因,并做决策。

学生学习高等数学、工程计算、编程和数据结构想象和创造的人工智能技术和系统将继续改变我们生活的许多领域——从农业、建筑、医疗、交通、人力资源、生产、市场营销等等。

一旦科幻小说的主题,人工智能已不再是一个陌生的概念。今天是司空见惯,简化业务流程,提高用户体验。

程序选项

人工智能-学士学位四年时间
虽然他们确实存在,AI的学士项目并不那么常见,因为大部分的工作在该领域要求硕士。AI学士课程从介绍人工智能的概念开始,机器学习和数据分析。与这些基础,学生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。最后提供的人工智能程序要求在本科阶段通常是学士论文或总结性的研究项目。

这是一个学士课程人工智能的例子:

  • 介绍数学和计算机科学
  • 微积分
  • 人工智能导论
  • 离散数学
  • 介绍编程
  • 介绍计算
  • 人工生命与认知科学
  • 线性代数
  • 介绍概率
  • 计算机体系结构与低级编程
  • 算法和数据结构
  • 操作系统并发性编程(具有多个计算同时发生)
  • 统计数据
  • 信息理论
  • 数据压缩方法(方法减少文件的大小重新编码的存储文件数据使用少于原始文件)
  • 对象编程(使得代码组织、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(AI的应用程序,提供了系统自动从经验中学习和提高的能力没有被显式地编程)
  • 凸优化的元素
  • 优化的数据分析方法
  • 数据挖掘
  • 数据可视化、图形
  • 机器人
  • 深度学习(一个AI函数,模拟人类大脑的运作处理数据用于检测对象,认识到演讲,翻译语言,和决策)
  • 互联网应用
  • 运筹学/工业工程
  • 信息检索
  • 问题类:数据分析和人工智能
  • 计算机视觉(使计算机理解图像和视频的内容)
  • 信号处理
  • 自然语言处理(建立计算机能够理解和处理语言)
  • 决策分析/决策支持
  • 大数据和分布式处理
  • 理论和实践的处理大数据
  • 强化学习和多主体系统
  • 计算智能
  • 问题类:机器学习和人工智能
  • 道德和研究
  • 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
  • 声明性编程和专家系统
  • 人工智能和游戏
  • 进化计算
  • 物联网
  • 强化神经网络(系统软件或硬件的工作原理类似于人类大脑的神经元执行的任务)
  • 科学研究做准备

人工智能——硕士学位两到三年时间
硕士学位是最常见的凭证。而人工智能的学士课程提供了基础核心课程、硕士项目更尖。学生专注于他们的选择的浓度和在这一领域进行研究,导致他们的论点。AI硕士课程通常包括实习。承认的硕士项目在人工智能,学生必须完成学士学位AI或相关专业如计算机科学、机器人或工程。

学校可能要求所有AI硕士学生,不管他们的重点领域,采取一些基本学科的研究生课程。下面是一些例子:

  • 逻辑和模型理论的基础
  • 统计工程师
  • 人工智能原理
  • 人工智能——方法与应用
  • 先进的机器学习的概念
  • 交互式智能系统的设计
  • 先进的自然语言处理

后完成必修课程要求,研究生继续学习和研究集中在一个特定的区域。这里是一些最常见的重点领域:

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

博士学位在人工智能-两到三年时间
人工智能的博士学位项目相对少见。那些存在旨在人希望从事研究和/或大学教学水平。博士毕业生在该领域有深入了解的重要方面的理论计算机科学与人工智能,包括算法和数据结构的设计与分析、处理大数据和解决复杂的问题。

度类似于人工智能

计算机工程
这个学位领域集成电气工程和计算机科学。它教导学生如何开发计算机硬件和软件。课程包括微积分课程,物理,计算机系统体系结构和网络、数字逻辑设计,数据结构,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和人类如何与它们进行交互。课程涵盖数学对于计算机科学、人工智能、数据结构和算法,并介绍了程序设计。

计算机软件工程
计算机软件工程学位课程教导学生如何应用软件开发工程的原则。学生们学习如何设计、构建、测试、实施、和维护计算机操作系统,以及应用程序允许最终用户在电脑上完成任务,智能手机和其他电子设备。大多数程序开始核心工程类,像数学,化学,物理。

机器人技术工程学
机器人技术工程学侧重于设计机器人和机器人系统可以执行职责,人类是不能或不愿意执行。

机器人技术
学位在机器人技术培养学生与工程师合作设计机器人和机器人系统能够进行职责,人类也不能或不愿意执行。

模拟编程
模拟计算机程序员开发模拟允许我们预测,考虑,测试,和操作真实的产品、服务、系统、流程、条件情况下,和问题,不承担风险,承担的成本真实的世界。数学、工程和计算机科学的交叉学科,模拟依赖。

该领域的学位课程由课程在这些技术和科学领域,但他们也关注教学技能的抽象,理论,假设和推理。换句话说,仿真编程学生学习一切他们需要概念化世界模型,旨在达到解决世界上的许多挑战和问题。

技能You’学习

人工智能的学生来远离他们的研究相当大的可转让的技能:

  • 适应性
  • 持续的快速学习和掌握新概念的能力
  • 沟通和协作/团队合作
  • 概念化、研究和项目计划
  • 批判性思维
  • 好奇心和创造力
  • 判断和决策
  • 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

你能做什么和一个人工智能的学位?

毕业生的人工智能应用他们的技能在数据分析,用户体验,自然语言处理,软件工程,编程,机器人和机器学习在一个日益增长的各种行业。这里有一些例子如何基于ai系统正在开发和使用在许多领域:

农业

  • 使用计算机视觉和机器学习来检测土壤缺陷和营养不足和识别杂草仍在增长的地区
  • 基于ai无人机和拖拉机
  • 气象监测系统
  • 使用人工智能的机器人来收获庄稼

汽车

  • 开发无人驾驶车辆紧急制动、盲点监控、驾驶员辅助操舵
  • 预测车辆维修

建设

  • 预测和预防成本超支项目规模的基础上,合同类型,和项目经理的能力
  • 三维建筑信息建模为有效的规划、设计、建设和管理的建筑
  • 无人驾驶工程机械执行重复任务如浇注混凝土,砌砖,拆迁

教育

  • 开发智能教学设计和数字平台,使用人工智能提供学习、测试和反馈给学生
  • 实时翻译老师说什么
  • AI-supported辅导和研究项目
  • 自动化的管理任务

金融

  • 自动化的金融投资

游戏

  • 基于ai无人机和拖拉机
  • 创建智能人形非玩家角色(npc)来与玩家互动
  • 预测人类行为导致更好的游戏设计和测试

医疗保健

  • 疾病检测和放射学领域的映射
  • 分析慢性疾病
  • 使用的医疗数据来发现新的药物
  • 病人监护
  • 人工智能驱动机器人移动和携带物品和清洁的空间和设备

人力资源

  • 智能软件来检查应用程序和简历基于特定的参数

制造和生产

  • 自动化的生产线
  • 制造机器人
  • 人工智能驱动机器人移动和携带物品和清洁的空间和设备

市场营销/零售/电子商务

  • 个性化的购物推荐引擎连接客户和营销活动,会话营销机器人,根据他们的浏览历史和潜在的购买和利益
  • 自然语言处理是人类测深AI-powered帮助创造虚拟购物助理和聊天机器人
  • 欺诈防范——减少信用卡欺诈分析使用模式;识别假的顾客评论

安全与监测

  • 智能城市是使用人工智能管理能源使用和减少犯罪
  • 基于ai人脸识别和生物识别系统

社交媒体

  • 艾未未认为用户首选项来匹配他们的帖子
  • 从不同的语言自动翻译的职位
  • 欺诈检测
  • 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

运输/导航

  • GPS技术来提高安全性
  • 人工智能是打开和关闭的道路检测和分析交通优化路线
  • 飞机和火车调度

旅行

  • 虚拟旅游代理商

城市规划

  • 智能城市是使用人工智能管理能源使用和减少犯罪

这些都是一些常见的头衔在人工智能:

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