1. Review of Previous Topics
2. AI Development Process
- Data Collection
- Gathering information that AI systems need to learn.
- Data Pre-processing
- Cleaning and organizing data for effective use.
- Training
- Teaching AI models using the prepared data.
- Deployment
- Making AI systems available for practical use.
3. Understanding of Data Types
- Audio
- Understanding that AI can interpret and process sound data.
- Video
- Learning that AI can analyze moving images or video frames.
4. Types of Problems AI Needs to Solve
- Natural Language Understanding
- Understanding that AI can comprehend human language.
- Translation
- Learning that AI can convert text or speech from one language to another.
- Transliteration
- Understanding that AI can convert text from one script to another.
- Speech Recognition
- Learning that AI can convert spoken language into text.
- Speech Synthesis
- Understanding that AI can convert text into spoken language.
- Face Detection/Recognition
- Discovering that AI can identify or verify a person from a digital image.
5. Safe and Fair AI
- Accountability
- Ensuring AI actions can be explained and are responsible.
- AI and the Future of Work
- Exploring potential changes in employment due to AI advancements.
- AI Misuse
- Weapons
- Ethical concerns regarding AI in weaponry.
- Surveillance
- Balancing security needs with privacy rights.