AI is a fascinating topic that not only baffled but also inspired the minds of philosophers, scientists, technicians, and even movie-makers. Humans are intrigued by the topic, because the investigation of AI allows people to decipher the complexity of their own minds. By trying to create AI systems people create an insight into human intelligence as well as are able to understand the world that is surrounding them. New technologies enhance the possibilities to further meet human demands concerning computational systems. This reflects the ability of the systems to understand and analyze unstructured text. The largest part of information available is written in unstructured natural language. AI systems can be used to make different types of information available for present day demands.
Thoroughly examining Watson will reveal the similarities and differences of the way humans and computational systems understand natural language. This will create insight into the potential and further development of the AI systems. Natural language processing systems have a broad field of applications. The demand of these systems becomes instantly apparent, when investigating various industries such as financial services, call centers, and the medical industry.
Nevertheless, Watson is not the only research program that will influence the future of society. Various smaller software programs will benefit and advance the current development. Also, knowledge representation will have an impact in areas such as the World Wide Web.
One important aspect that should be considered when analyzing projects like Watson is the opportunities that arise with it. In the Art of War, Sun Tzu states: “Know thine enemy better than one knows thyself”. Investigating the Jeopardy! challenge characterizes the battle between man and machine. This leads to the conclusion that understanding Watson allows to look at aspects of human intelligence that are still unraveled.
Inhaltsverzeichnis (Table of Contents)
- 1. Introduction.
- 2. IBM's History and the Development of Watson.......
- 3. Jeopardy! and the Potential of QA systems.
- 4. Watson's Appearance..
- 4.1. Watson's Voice
- 4.2. Watson's Visual Appearance
- 4.3. Watson's Answer Panel
- 5. Aspects of Artificial Intelligence
- 5.1. Definition of Artificial Intelligence........
- 5.2. AI and Recursion........
- 5.3. AI and Problem Reduction......
- 5.4. AI and Human Intelligence
- 5.5. Computers and Learning ..
- 5.6. Knowledge and AI
- 5.7. AI and Natural Language
- 5.8. Originality of Programs..
- 5.9. Creativity and Randomness.
- 5.10. Turing Test .........
- 6. Understanding Watson.
- 6.1. Watson's Hardware.
- 6.2. Watson's Software
- 6.2.1. Software Foundations..
- 6.2.2. Apache UIMA.
- 6.2.3. Watson's System and Jeopardy!.\n.36
- 6.2.3.1. The Jeopardy! Challenge......\n.36
- 6.2.3.2. Jeopardy! Clues.
- 6.2.3.3. Watson's DeepQA Architecture........\n.42
- 6.3. Watson and Natural Language.
- 7. Critique on Watson and Jeopardy!.
- 8. Watson's Future
- 9. AI Research Programs and Knowledge Representation
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This bachelor thesis aims to explore the role of language in the development of Artificial Intelligence (AI) systems, focusing on IBM's Watson program and its performance in the game show Jeopardy!. The work seeks to understand the complexities of natural language processing and its implications for AI advancements.
- The development and capabilities of AI systems, particularly Watson.
- The role of natural language processing in AI development.
- The challenges and opportunities presented by AI systems in various industries.
- The comparison between human and artificial intelligence, particularly in understanding language.
- The future of AI research and its potential impact on society.
Zusammenfassung der Kapitel (Chapter Summaries)
The introductory chapter establishes the problem of information overload and the need for AI systems that can understand natural language to navigate this data deluge. It highlights the importance of natural language processing in AI development, emphasizing the complexities and ambiguities of language.
Chapter 2 provides a historical overview of IBM's involvement in computational advancements, tracing the development of their computers and their growing influence in areas like space exploration. It sets the stage for the introduction of Watson as the latest challenge in computer development and natural language processing.
Chapter 3 focuses on the game show Jeopardy! and its significance as a platform for showcasing the capabilities of AI systems. It emphasizes the potential of Question Answering (QA) systems, which can analyze and understand natural language questions, to revolutionize information retrieval.
Chapter 4 describes Watson's appearance, focusing on its voice, visual presentation, and answer panel. This chapter gives a concrete picture of how Watson interacts with its environment.
Chapter 5 delves into the key aspects of Artificial Intelligence, defining AI and exploring concepts like recursion, problem reduction, and the relationship between AI and human intelligence. It also examines the role of computers in learning, knowledge representation, and the relationship between AI and natural language.
Chapter 6 provides a detailed explanation of Watson's hardware and software components, including the Apache UIMA framework and the DeepQA architecture. It also discusses Watson's approach to the Jeopardy! challenge, highlighting its ability to understand and analyze natural language clues.
Chapter 7 presents a critical analysis of Watson and its performance in Jeopardy!, considering its strengths, weaknesses, and the implications of its success. This chapter will likely explore the nuances of Watson's understanding and application of natural language compared to human intelligence.
Schlüsselwörter (Keywords)
This thesis focuses on the intersection of artificial intelligence, natural language processing, and knowledge representation, using IBM's Watson program as a case study. Key terms include: AI, Natural Language Processing (NLP), Question Answering (QA), DeepQA, Jeopardy!, IBM, knowledge representation, computer science, human intelligence, computational systems, and information retrieval.
- Quote paper
- Frank Born (Author), 2011, The role of language in the development of AI systems, Munich, GRIN Verlag, https://www.grin.com/document/318595
