Introduction to AI and its domains.pptx
- 2. What is AI? Artificial Intelligence (AI) is an exciting field that focuses on creating intelligent machines capable of performing tasks that typically require human intelligence. This Photo by Unknown Author is licensed under CC BY-SA-NC
- 3. Decoding AI • It is a branch of computer science that aims to create intelligent machines that can mimic human intelligence. • It involves developing computer programs that can analyze, learn, and make decisions based on data and patterns. • AI encompasses various subfields such as machine learning, natural language processing, computer vision, and robotics.
- 4. Types of Artificial Intelligence •Artificial Narrow Intelligence (ANI): AI that is designed to perform a specific task, such as voice recognition or image classification. It excels in one area but lacks general intelligence. •Artificial General Intelligence (AGI): AI that possesses the ability to understand, learn, and apply knowledge across various domains. AGI has human-like intelligence. •Artificial Superintelligence (ASI): Hypothetical AI that surpasses human intelligence and capabilities. ASI is a topic of speculation and remains theoretical.
- 5. Artificial Intelligence, Machine Learning and Deep Learning Artificial Intelligence is the overarching field that encompasses various techniques and approaches for creating intelligent machines. Machine Learning is a subfield of AI that focuses on developing algorithms that enable computers to learn from data and make predictions or decisions. Deep Learning is a subset of ML that utilizes deep neural networks with multiple layers to automatically learn complex patterns and representations from data.
- 6. AI Domains With respect to the type of data fed in the AI model for training, AI models can be broadly categorized into three domains: Data Sciences Computer Vision Natural Language Processing Data sciences is a domain of AI related to data systems and processes, in which the system collects numerous data, maintains data sets and derives meaning/sense out of them. The information extracted through data science can be used to make decisions. Computer Vision, abbreviated as CV, is a domain of AI that depicts the capability of a machine to get and analyse visual information make predicions about it. The entire process involves image acquiring, screening, analysing, identifying and extracting information. NLP is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language. NLP attempts to extract information from the spoken and written words using algorithms. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable.
- 7. Examples of Data Science Price Comparison Websites :These websites are being driven by lots and lots of data. If you have ever used these websites, you would know, the convenience of comparing the price of a product from multiple vendors at one place. PriceGrabber, PriceRunner, Junglee, Shopzilla, DealTime are some examples of price comparison websites. Now a days, price comparison website can be found in almost every domain such as technology, hospitality, automobiles, durables, apparels etc.
- 8. Examples of Computer Vision Self-Driving cars/ Automatic Cars: CV systems scan live objects and analyse them, based on whether the car decides to keep running or to stop. Face Lock in Smartphones: Smartphones nowadays come with the feature of face locks in which the smartphone’s owner can set up his/her face as an unlocking mechanism for it. The front camera detects and captures the face and saves its features during initiation. Next time onwards, whenever the features match, the phone is unlocked. .
- 9. Examples of NLP Email filters: Email filters are one of the most basic and initial applications of NLP online. It started out with spam filters, uncovering certain words or phrases that signal a spam message Smart assistants: Smart assistants like Apple’s Siri and Amazon’s Alexa recognize patterns in speech, then infer meaning and provide a useful response.
- 10. Applications of AI Healthcare: AI can assist in medical diagnoses, drug discovery, personalized treatment plans, and monitoring patient data. •Transportation: AI is used in autonomous vehicles for navigation, collision avoidance, and traffic optimization. •Finance: AI algorithms are employed for fraud detection, stock market analysis, and risk assessment. •Education: AI can enhance learning experiences through personalized tutoring, adaptive learning platforms, and intelligent content creation. •Manufacturing: AI-powered robots automate assembly lines, quality control, and predictive maintenance. •Entertainment: AI is used in recommendation systems, content creation, and gaming.
- 11. AI Ethics Addressing AI ethics is crucial to ensure that AI technologies are aligned with human values, respect fundamental rights, and contribute positively to society and to create a responsible and an inclusive AI ecosystem.
- 12. AI Ethics: Key Aspects •Fairness and Bias: Addressing biases in AI algorithms and ensuring fairness in decision-making. •Transparency and Explain ability: Making AI systems transparent and understandable to build trust and accountability. •Privacy and Data Protection: Protecting personal data and ensuring compliance with privacy regulations. •Accountability and Responsibility: Holding individuals and organizations accountable for the actions and consequences of AI systems. •Safety and Robustness: Building AI systems that are safe, reliable, and resilient against failures. •Human Autonomy and Control: Preserving human decision-making and ensuring AI systems augment human capabilities. •Societal Impact: Assessing and mitigating the broader social impact of AI, including employment and economic implications. •Ethical Governance: Establishing guidelines and policies to govern the ethical development and use of AI technologies.
- 13. Jobs in AI AI may automate certain jobs, but it also creates new job opportunities that require human skills such as creativity, critical thinking, and problem-solving. Creative Jobs Management Jobs Tech oriented Jobs Jobs which will grow with the help of AI
- 14. Some Job Titles of the Future 1.AI Engineer/Developer 1.Data Scientist 1.Machine Learning Engineer 1.Robotics Engineer 1.AI Ethicist 1.AI Research Scientist 1.AI Consultant 1.Natural Language Processing (NLP) 1.AI Product Manager 1.AI Trainer/Annotator 1.AI User Experience (UX) Designer
- 15. Future of AI Artificial Intelligence is revolutionizing various aspects of our lives, from healthcare and transportation to education and entertainment. Its potential benefits are vast, but we must address ethical concerns and prepare for the changing job landscape. This Photo by Unknown Author is licensed under CC BY-SA-NC