8.10: End of Chapter Resources
- Page ID
- 38322
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- It traces the rapid development of information systems since the 1950s, comparing modern handheld devices to early computers.
- The narrative unfolds the power of AI in processing information through algorithms and machine learning, showcasing its ability to mimic human behavior and impact businesses.
- The chapter covers significant achievements such as IBM's Deep Blue defeating a chess champion in 1997, speech recognition software, and recent successes like IBM's Watson winning "Jeopardy!" in 2011 and Google's AlphaGo defeating a Go champion in 2017.
- The chapter then delves into the intricate workings of AI systems, focusing on their development through machine learning and deep learning techniques.
- Deep learning, identified as a subset of machine learning, is presented as a technique requiring significantly less human involvement, utilizing artificial neural networks to independently extract features and classify data.
- The narrative extends to applications of AI, exploring autonomous technologies like medical nanobots, self-driving cars, and unmanned aerial vehicles (UAVs). The use of robots in manufacturing, medicine, education, and entertainment is discussed, emphasizing their potential impact on efficiency and mobility.
- The chapter concludes with an exploration of extended reality (XR) and emerging technology trends. XR, covering augmented reality (AR), virtual reality (VR), and mixed reality (MR), is examined for its applications in e-commerce, gaming, and training.
- Wearables, the Internet of Things (IoT), collaborative technologies, and supercomputing, including quantum computing, are discussed, highlighting their potential impact on various sectors.
Key Terms
Algorithms: which are a set of rules or processes to solve a specific problem or task.
Artificial Intelligence: The ability of a computer or machine to think and learn, and mimic human behavior.
Augmented reality (AR): Enhances one’s view of the real world with layers of digital information added to it. With AR there is no created scenario; instead, an actual event is being altered in real-time.
Autonomous Technologies: Autonomous robots and vehicles that work by combining software, sensors, and location technologies. Devices that can operate themselves.
Chat-bots: are computer programs that use AI and natural language processing (NLP) to understand customer questions and automate responses to them, simulating human conversation.
Collaborative Technology: To share data for mutual benefit. Some of this sharing can be done passively and other data can be reported actively.
Deep Learning (DL): A subset of Machine Learning – Deep Learning refers to when computers can solve more complex problems without human intervention.
Emerging technology: includes new technology and technology that is continuously evolving.
Expert Systems (ES): Designed to emulate the human ability to make decisions in specific contexts and have had a large impact in the world of AI.
Extended Reality or XR: XR is an umbrella term that covers all forms and combinations of real and virtual environments. This includes augmented reality (AR), virtual reality (VR), and a combination of the two or mixed reality (MR).
Intelligent Agents: Process the inputs it receives, and makes decisions/ takes action based on that information.
Internet of Things: The idea of physical objects being connected to the Internet, embedded with electronics, software, sensors, and network connectivity, which enables these objects to collect and exchange data.
Loop: a part of software code that allows a command to run again and again.
Machine Learning (ML): is a technique that is used by an AI system to analyze data, find patterns, and make decisions automatically or with minimal human support.
Nanobot: Is a robot whose components are on the scale of about a nanometer, which is one-billionth of a meter. While still an emerging field, it is showing promise for applications in the medical field.
Natural Language Processing (NLP): Allows computers to extract meaning from human language. Natural Language Processing’s goal by design is to read, decipher, and comprehend human language.
Reinforcement Learning: A form of Machine Learning in which a machine is given unlabeled data and must find its own connections through analysis, clustering, and identifying patterns.
Robots: These are automated machines that can execute specific tasks with very little or no human intervention and can accomplish tasks with both speed and precision.
Supervised Learning: A form of Machine Learning in which data is labeled and categorized into groups by humans and algorithms are used to classify data based on labels.
Unsupervised Learning: The trial and error-based Machine Learning method in which a machine learns from mistakes and improves upon them.
Virtual Reality (VR): Computer interaction in which a real or imagined environment is simulated. This allows users to both interact with and alter that reality within the environment.
Wearable Technology: A category of technology devices that can be worn by a consumer and often include tracking information related to health and fitness.
End of Chapter Discussions
- Reflecting on today’s technology landscape, what do you perceive as one of the most significant impacts?
- Considering the chapter’s content, what are the potential benefits and drawbacks associated with the integration of robots in business operations?
- Can you identify instances in the restaurant industry where technology is replacing human interaction?
- What is the difference between XR, AR, and VR?
- What is artificial intelligence, and what are some of the capabilities?