Week 13 Artificial Intelligence PDF

Artificial Intelligence LIVING IN THE IT ERA - WEEK 13 Prepared by: Mr. Joseph T. Bual Instructor Learning Objectives: 1.To understand and appreciate the role of AI; 2.To be familiar with AI terminologies; and 3.To compare AI with human intelligence and traditional information...

Artificial Intelligence LIVING IN THE IT ERA - WEEK 13 Prepared by: Mr. Joseph T. Bual Instructor Learning Objectives: 1.To understand and appreciate the role of AI; 2.To be familiar with AI terminologies; and 3.To compare AI with human intelligence and traditional information processing and discuss its strengths and limitations.  Artificial Intelligence (AI) is a branch of computer science concerned in making computers behave like humans do. It was still in the ancient times that they were dreaming to create intelligent machines that can engage on behaviors that humans consider intelligent. It was only in the later years that smart machines is becoming in reality. Many researchers now are creating systems that mimic human thought, understand speech, and beat the best human chess player and countless other feats never before possible.  Game playing refers to programming computers to play games such as chess and checkers. The most common AI for game playing is chess. IBM had developed a computer chess player named Deep Blue which won over the defending world champion Gary Kasparov in 1997. Speech recognition is a technology where computers recognize human language to perform such task. In later years, speech recognition reached a practical level for limited purposes. This technology supposedly will replace the use of keyboard because you will just give instructions to the computer. But human went back to the use of keyboard and mouse because of convenience in using them.  Understanding natural language allows computers to understand natural human languages. Research are still working in progress in developing systems that converse in natural language, perceive and respond to their surroundings, and encode and provide useful access to all human knowledge and expertise. Natural-language processing offers the greatest potential rewards because it would allow people to interact with computers without needing any specialized knowledge. You could simply walk up to a computer and talk to it. Unfortunately, programming computers to understand natural languages has proved to be more difficult than originally thought of. Computer vision makes useful decisions about real physical objects and scenes based on sensed images. This is to make images and objects as real as it can be. At present, there are only limited ways of representing three-dimensional information directly, and they are not as good as what humans evidently use.  Expert systems refer to programming computers to make decisions in real life situations such as helping doctors diagnose disease based on symptoms. In the early 1980s, expert systems were believed to represent the future of artificial intelligence and of computers in general. To date, however, they have not lived up to the expectations. Many expert systems help human experts in such fields as medicine and engineering, but they are very expensive to produce and are helpful only in special situations. Heuristic classification is one of the most feasible kinds of expert system given the present knowledge of AI. This will put some information in one of a fixed set of categories using several sources of information. An example is advising whether to accept a proposed credit card purchase. Information is available about the owner of the credit card, his record of payment and the item he is buying and about the establishment from which he is buying it (e.g., about whether there have been previous credit card frauds at this establishment).  AI History Turing’s Test is a test which analyzes or examines whether a computer has a humanlike intelligence. It was proposed by a British mathematician. The computer is said to pass the Turing’s test if the panel believes that the entity possesses humanlike intelligence. Turing’s test is sometimes referred to as behavioral tests for the presence of mind, or thought, or intelligence in putatively minded entities.  It was in a 1951 paper that Alan Turing proposed a test called “The Imitation Game” which he thought would settle the issue of machine intelligence. The first version of the game involved no computer intelligence whatsoever. Imagine three rooms, each connected via computer screen and keyboard. In one room sits a man, in the second a woman, and in the third sits a person who will serve as the "judge" who will decide as to which of the two people talking to him through the computer is the man. The man will attempt to help the judge, offering whatever evidence he can (the computer terminals are used so that physical clues cannot be used) to prove his man_x0002_hood. The woman's job is to trick the judge, so she will attempt to deceive him, and counteract her opponent's claims, in hopes that the judge will erroneously identify her as the male.  Later on, Turing proposed a modification of the game. Instead of a man and a woman as contestants, a human of either gender at one terminal, and/or a computer at the other terminal will participate. Now, the judge's responsibility is to decide which of the contestants is human, and which the machine is. Turing proposed that if, under these conditions, the judge were less than 50% accurate – that is, if a judge is as likely to pick either human or computer – then the computer must be a passable simulation of a human being and hence, intelligent. The game has recently been modified so that there is only one contestant, and the judge's job is not to choose between two contestants, but simply to decide whether the single contestant is human or machine.  The following are various types of web sites to choose and search from. Perplexity AI – offers unlimited basic searchers and up to 5 Pro searchers per day for free. It provides quick answers and detailed insights from a wide ranges of sources. Consensus offers a free plan that allows users to search through over 200 million research papers and get AI-generated insights and summaries. Quizgecko – allows the user to create and share quizzes easily. It uses AI to generate quiz questions from any text, making it a great tool for studying and test preparation. Gamma AI – offers a free tier that allows users to create and share presentations, documents, and web pages. It includes AI-powered features for content editing, image search, and reformatting. Edpuzzle– allows users to create interactive video lessons by embedding questions, notes, and audio into videos. Podcastle AI – converts text into high-quality audio, which is great for turning readings into podcasts that you can listen to on the go.  Mymap AI – generates mind maps from users notes and ideas, helping the user visualize and organize their thoughts more effectively. Socratic AI – designed by Google to help students with homework by providing explanations, videos, and step-by-step solutions. Fotor – allows the user to create images from text for free. FutureMe – is a unique tool that allows users to write letters, reminders or anything else to their future self. It can be a great way to set goals, reflect on your progress, and capture your thoughts for future reflection. The Rise of AI: Advancements and Adoption Rapid Progress Widespread Adoption Transformative Potential Breakthroughs in machine learning, natural language AI is now widely integrated into everyday AI has the power to revolutionize industries, processing, and computer vision have accelerated technologies, from virtual assistants to enhance decision-making, and solve complex global AI capabilities. autonomous vehicles. challenges. Machine Learning: Powering AI Applications 1 Data Acquisition Collecting and preprocessing large, diverse datasets to train machine learning models. 2 Model Training Applying advanced algorithms to enable machines to learn and improve from experience. 3 Deployment Integrating trained models into real-world applications to solve complex problems. Natural Language Processing: Improving Human- AI Interaction Language Understanding Conversational Abilities Enabling AI systems to comprehend and interpret Developing AI chatbots and virtual assistants human language, including context and nuance. that can engage in natural, intuitive dialogue. Multilingual Capabilities Personalized Interactions Advancing NLP techniques to support a diverse Tailoring AI responses to individual users' needs range of languages and cultural contexts. and preferences for a more personalized experience. Computer Vision: Revolutionizing Image and Video Analysis Image Recognition Video Analysis Enabling AI to identify and classify objects, people, and scenes Applying computer vision to understand and interpret the within digital images. content and context of video footage. Augmented Reality Medical Imaging Integrating computer vision with AR technology to overlay Leveraging computer vision to assist in the analysis and digital information on the physical world. diagnosis of medical scans and imagery. Autonomous Systems: From Vehicles to Robotics Perception Decision-Making Control Enabling autonomous systems to perceive and interpret Developing robust AI algorithms to make real-time Integrating autonomous control systems to precisely their surroundings through sensors and computer vision. decisions and navigate complex environments. operate vehicles, robots, and other automated machinery. Ethical Considerations: Ensuring Responsible AI Development 1 Bias and Fairness 2 Privacy and Security Addressing potential biases in AI systems to Safeguarding personal data and implementing ensure equitable and unbiased decision-making. robust security measures for AI-powered applications. 3 Transparency and Accountability 4 Human-AI Interaction Ensuring AI technologies enhance and empower Developing AI systems with clear decision-making human capabilities, rather than replace or displace processes and mechanisms for oversight and them. responsibility. AI and the Future of Work: Opportunities and Disruptions Automation and Augmentation Workforce Transformation New Job Creation AI is also enabling the emergence of novel job roles AI-powered automation can enhance productivity The integration of AI will require reskilling and and industries centered around its capabilities. and free up human workers for more strategic upskilling to adapt to changing job requirements. tasks. Data Privacy and Security in the Age of AI 1 Data Collection Ensuring transparency and obtaining informed consent for the collection of personal data. 2 Data Storage Implementing robust security measures to protect sensitive data from unauthorized access or breaches. 3 Data Usage Establishing clear guidelines and policies for the ethical and responsible use of AI-powered data analysis. The Road Ahead: Navigating the AI Landscape Continuous Innovation Persisting Challenges Collaborative Approach Breakthroughs in AI will Issues like bias, privacy, Interdisciplinary continue to push the and ethics require ongoing collaboration between boundaries of what's attention and mitigation. technologists, possible. policymakers, and ethicists is crucial.