The Future is now Journey Through Artificial Intelligence
- 1. Journey Through Artificial Intelligence THE FUTURE IS NOW STARTELELOGIC 2024
- 2. AGENDA What is Artificial Intelligence? 1. Types of Artificial Intelligence 2. Examples of AI Applications 3. How a Machine Learns 4. Artificial Neural Networks 5. Ethics in Artificial Intelligence 6. Exciting Future of Artificial Intelligence 7. Conclusions 8.
- 3. What is Artificial Intelligence? Artificial Intelligence (AI) is a branch of computer science that focuses on creating systems capable of performing tasks that would normally require human intelligence. These tasks include learning from experience, understanding natural language, recognizing patterns, solving problems, and making decisions. AI aims to simulate human cognitive processes through machines, allowing them to operate autonomously in complex environments.
- 4. Types of Artificial Intelligence Narrow AI Narrow AI refers to AI systems designed and trained to perform a specific task. These systems operate within a limited context and cannot perform beyond their pre-defined functions. Examples of Narrow AI include virtual assistants like Siri, Alexa, and Google Assistant, which perform specific tasks such as setting reminders and answering queries. General AI General AI possesses generalized human cognitive abilities, enabling it to understand, learn, and apply knowledge across a wide range of tasks. Unlike Narrow AI, General AI can perform any intellectual task that a human can, with broad understanding and reasoning capabilities. Currently, General AI is theoretical and has not yet been achieved. Artificial Superintelligence (ASI) Artificial Superintelligence (ASI) refers to AI that surpasses human intelligence and can perform tasks better than humans in every aspect, including creativity, problem-solving, and decision-making. ASI possesses superior intelligence and has the potential to lead to revolutionary changes in society. This type of AI is hypothetical and often discussed in speculative fiction and theoretical discussions.
- 5. Examples of AI Applications Health AI is revolutionizing healthcare by improving diagnostic accuracy, personalizing treatment plans, and enhancing patient care. Machine learning algorithms analyze medical images to detect diseases such as cancer at early stages, often with greater accuracy than human doctors. Education AI is making education more personalized and accessible. Intelligent tutoring systems provide customized learning experiences by adapting to each student's strengths and weaknesses, offering targeted exercises and feedback. E-commerce In e-commerce, AI enhances the shopping experience by providing personalized recommendations and improving customer service. Machine learning algorithms analyze customer behavior and preferences to suggest products that are likely to be of interest, increasing sales and customer satisfaction. Communication In the field of communication, AI is transforming how we interact and exchange information. Natural Language Processing (NLP) technologies enable AI- powered chatbots and virtual assistants to understand and respond to human language, providing instant support and information.
- 6. How a Machine Learns? Machine learning is a process where machines learn from data and improve their performance over time without explicit programming. It starts with collecting and preparing data, selecting and engineering features, and choosing an appropriate algorithm. The model is trained on this data, learning the relationship between inputs and outputs by adjusting its parameters. Its performance is evaluated and optimized through hyperparameter tuning. Once the model is effective, it is deployed to make predictions on new data and continuously monitored for accuracy. Techniques include supervised learning with labeled data, unsupervised learning to find patterns, and reinforcement learning through feedback from the environment.
- 7. Artificial Neural Networks Artificial Neural Networks (ANNs) are computing systems inspired by the human brain, composed of interconnected nodes that process data. They consist of layers: an input layer, hidden layers, and an output layer. ANNs learn through training, adjusting the weights of connections between nodes based on errors in output. They are used in image and speech recognition, natural language processing, and more. While powerful for complex tasks, they require large datasets and computational resources, and their results can be difficult to interpret due to their complex nature. HOW THEY WORK?
- 8. Ethics in Artificial Intelligence Ethics in AI involves ensuring that AI systems are fair, transparent, and accountable. This includes addressing bias, ensuring transparency in decision- making, protecting privacy, and establishing accountability for any harm caused by AI systems. It also involves ensuring the safety and security of AI systems, maintaining human control, and considering the broader social impact of AI.
- 9. Exciting Future of Artificial Intelligence AI's future is bright, set to transform our lives across industries. In healthcare, it improves diagnostics and personalized treatment. In transportation, it drives safer autonomous vehicles. Finance benefits from AI in fraud detection and trading. Retail, manufacturing, and agriculture see increased efficiency. AI's evolution promises a profound societal impact, enhancing lives, boosting economies, and tackling challenges.