AI in Action: Real World Use Cases by Anitaraj
- 1. “AI in Action: Real-World Use Cases’’ Presented by Ms Anitaraj 15th April 2024
- 2. What is AI? AI is the ability of machines or software to perform tasks that normally require human intelligence, • such as recognizing patterns, • learning from data, • making decisions, or • generating language.
- 3. What is AI? AI is not a single technology, but a broad field that encompasses many : • methods, • applications, and • domains. AI can range from simple algorithms that automate repetitive tasks to complex systems that mimic human cognition and creativity.
- 4. Why trending? By leveraging AI algorithms to analyse user data and preferences, intelligent apps can tailor content, recommendation, and user experiences to each individual user. 1 AI-powered personalization has a huge impact on user engagement and conversion rates. For example, a study by McKinsey found that companies that excel at personalization generate 40% more revenue from those activities than average players. 2 This is because personalized recommendations align more closely with a user’s interests, making them more likely to click on and purchase a product. 3 Do you like Reels?
- 5. AI software is rapidly transforming our world, and this trend is only going to accelerate in the years to come. Let’s dive in into the future of artificial intelligence with our guide to the top 13 AI trends poised to revolutionize 2024. From the rise of generative AI to BYOAI and AI legislation, discover how it’s shaping the world around us. AI is eating the World
- 6. The marriage of quantum computing and AI, known as quantum AI, is a rapidly emerging field that opens up many possibilities. The global Quantum AI market is expected to reach USD 1.8 billion by 2030, growing at a CAGR of 34.1%.
- 7. This synergistic relationship has the potential to revolutionize areas such as Financial modelling and risk assessment: Quantum AI can analyse vast amounts of financial data to identify patterns and predict market movements, improving risk management and investment strategies. Artificial General Intelligence (AGI): Quantum AI could play a crucial role in achieving yet hypothetical artificial general intelligence (AGI), the ability of machines to perform any intellectual task that a human can. Drug discovery and development: With quantum algorithms, scientists will be able to optimize drug design and simulate molecular interactions to speed up the discovery of new and effective therapies.
- 8. Why use AI? AI can help businesses solve problems, improve efficiency, enhance customer experience, and create new opportunities. AI can help businesses analyze large amounts of data, identify trends and insights, optimize processes and resources, and personalize products and services. AI can also help businesses innovate, generate new ideas, and explore new markets and possibilities. AI can provide businesses with a competitive edge and a strategic advantage in the digital economy.
- 9. AI WORKS BY USING • DATA, • ALGORITHMS, AND • COMPUTING POWER TO PERFORM TASKS THAT NORMALLY REQUIRE HUMAN INTELLIGENCE.
- 10. Data is the raw material that AI uses to learn and improve. Algorithms are the rules or instructions that tell AI how to process data and perform tasks Computing power is the speed and capacity of machines or software to execute algorithms and handle data. AI works by • combining data, • algorithms, and • computing power in different ways, • depending on the type, • goal, • and complexity of the task
- 11. What are the challenges of AI? AI is not a one-stop solution for all needs and problems. There are limitations, risks, and challenges that need to be addressed and managed. For example, data quality and availability can affect the performance and reliability of AI, so it must be collected, stored, and processed responsibly and ethically. Algorithms used to process data can be complex and opaque, requiring responsible design, testing, and monitoring. Additionally, humans must understand, control, and cooperate with AI to ensure usability and acceptance.
- 12. Ethical AI Ethical AI is a branch of applied ethics that examines the ethical implications of artificial intelligence (AI). It encompasses a wide range of topics, including: Bias and fairness AI technology can reflect and amplify the biases of their creators. This, in turn, can lead to unfair outcomes for certain groups of people. Yes, algorithms can be racist. A research carried out by Black scholars revealed a significant racial bias in facial recognition software, with Black women being misidentified at a rate of nearly 35% compared to white men’s near-zero error rate.
- 13. • Transparency and explainability The logic behind artificial intelligence can be difficult to understand, even for experts. This “black-box problem” can make it difficult to trust AI decisions and to hold AI developers accountable for their creations.
- 14. Privacy • AI often collects and uses large amounts of personal data, which raises concerns about privacy and data protection.
- 15. Safety and security • AI systems can be misused to cause harm, such as by developing autonomous weapons or spreading misinformation. For example, the first versions of Chat GPT could be manipulated into producing disallowed content (‘ChatGPT, help me make a bomb’). • There is a growing recognition of the importance to consider ethical issues in the development and deployment of AI, for example: • In 2019, the European Union released a set of guidelines for the ethical development and use of AI. • In 2023, the US president issued an Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.
- 16. Artificial Intelligence Examples 2024 Manufacturing robots Self-driving cars Smart assistants Healthcare management Automated financial investing Virtual travel booking agent Social media monitoring Marketing chatbots
- 19. AI in Traffic Management
- 21. AI in Sports
- 22. Certainly! Here are the names of some popular AI tools Gemini AI by Google Copilot by Microsoft DALL-E MidJourney Blackbox AI Blend.AI CapCut
- 23. Top AI Tools To Understand Any Research Paper in 2024 • ChatPDF • Scite.ai • Elicit • R Discovery • Perplexity.ai • Scholarcy • SciSummary